Predictive geo-temporal advertisement targeting
20 claims: 3 independent, 17 dependent
- 1予測されたデバイス位置に基づいて、移動体デバイスのユーザーに宛てる広告コンテンツを絞り込む方法を実行するためのコンピューター実行可能命令が具体化されている1つ又は複数のコンピューター読み取り可能媒体であって、前記方法が、前記移動体デバイスと関連のある位置情報を収集すべき複数のサンプリング時間期間を特定するための、動的に更新可能なサンプル設計を参照するステップと、前記サンプル設計に基づいて、前記複数のサンプリング時間期間の部分集合の各々における前記移動体デバイスとのユーザー対話処理のインスタンスを検出するステップと、前記移動体デバイスとのユーザー対話処理の各インスタンスを検出したことに応答して、前記移動体デバイスと関連のあるタイム・スタンプ付きデバイス位置データを収集するステップと、 複数の時間期間における前記移動体デバイスの複数の位置の表現を含む動的地理−時間モデルを更新するステップであって、前記動的地理−時間モデルの更新が、前記サンプル設計にしたがって収集された前記タイム・スタンプ付きデバイス位置データを組み込むことを含む、ステップと、 第1時間期間を指定するステップと、 前記動的地理−時間モデルを用いて前記第1時間期間における前記デバイスの位置を予測するステップと、 前記予測した位置に基づいて、前記デバイスに提供する広告を選択するステップと、 前記第1時間期間において前記広告をユーザーに提示できるように、前記広告を前記デバイスに提供するステップと、前記動的地理−時間モデルを参照することにより、ユーザーが前記移動体デバイスと対話処理を行う時間期間を予測するステップと、前記予測された時間期間においてユーザーが前記移動体デバイスと対話処理を行わなかった場合に前記サンプル設計を更新すべきであると判断するステップと、前記サンプル設計を更新すべきであると判断したことに応じて前記サンプル設計を更新するステップと、 を備えている、1つ又は複数のコンピューター読み取り可能媒体。
- 2請求項1記載の媒体において、前記動的地理−時間モデルが、前記デバイス位置データと関連のある少なくとも1つの確率密度関数を備えている、媒体。
- 3請求項1記載の媒体において、前記地理−時間モデルを更新するステップが、前記モデルと関連のある1つ又は複数のパラメータを変更するステップを含む、媒体。
- 4請求項1記載の媒体において、前記地理−時間モデルを更新するステップが、指定された時間期間の前に収集されたデータを破棄するステップを含む、媒体。
- 5請求項1記載の媒体において、広告を選択するステップが、ユーザーが前記移動体デバイスと予測された位置において対話処理を行ったときにユーザーに提示すべきことを示す属性が関連付けられている広告を特定するステップを含む、媒体。
- 6請求項5記載の媒体において、前記予測された位置が、指定された地理的領域を含む、媒体。
- 7請求項5記載の媒体において、前記広告を選択するステップが、更に、 前記移動体デバイス上に維持されているキャッシュと関連のある利用可能な記憶空間を判定するステップと、 広告を格納するために必要なメモリー量を示す属性を有する広告を選択するステップであって、前記広告を格納するために必要なメモリー量が、前記キャッシュと関連のある、利用可能と判定された記憶空間よりも少ない、ステップと、 を含む、媒体。
- 8請求項7記載の媒体において、前記第1時間期間においてユーザーに前記広告を提示できるように前記広告を提供するステップが、前記移動体デバイスが前記広告をキャッシュ内に格納するように、前記広告を移動体デバイスに提供するステップを含む、媒体。
- 9請求項8記載の媒体において、前記広告を提供するステップが、更に、ユーザーが前記移動体デバイスと対話処理したときに、前記第1時間期間において前記広告を提示すべきことの指示を含ませるステップを含む、媒体。
- 10請求項1記載の媒体において、前記サンプル設計を更新するステップが、更に、データ収集のインスタンスの頻度およびパターンの内少なくとも1つを変化させるステップを含む、媒体。
- 11予測されたデバイス位置に基づいて、移動体デバイスのユーザーに宛てる広告コンテンツを絞り込む方法を実行するためのコンピューター実行可能命令が具体化されている1つ又は複数のコンピューター読み取り可能媒体であって、前記方法が、前記移動体デバイスと関連のある位置情報を収集すべき複数のサンプリング時間期間を特定するための、動的に更新可能なサンプル設計を参照するステップと、前記サンプル設計に基づいて、前記複数のサンプリング時間期間の部分集合の各々における前記移動体デバイスとのユーザー対話処理のインスタンスを検出するステップと、前記移動体デバイスとのユーザー対話処理の各インスタンスを検出したことに応答して、前記移動体デバイスと関連のあるタイム・スタンプ付きデバイス位置データを収集するステップと、 前記移動体デバイスとのユーザー対話処理と、ユーザーが前記移動体デバイスと対話処理を行うときの前記移動体デバイスの位置との間において仮説を立てた関係を表す動的地理−時間モデルを更新するステップと、 第1時間期間を指定するステップと、前記動的地理−時間モデルを参照することにより、ユーザーが前記移動体デバイスと対話処理を行う時間期間を予測するステップと、 前記移動体デバイスが、前記第1時間期間において、第1の位置にあることを予測するステップと、 選択された広告を前記移動体デバイスに提供して、この広告を前記移動体デバイス上にあるキャッシュ内に格納することができるようにし、更に前記第1時間期間において前記広告をユーザーに提示することができるようにするステップであって、前記広告が前記第1の位置に基づいて選択される、ステップと、前記予測された時間期間においてユーザーが前記移動体デバイスと対話処理を行わなかった場合に前記サンプル設計を更新すべきであると判断するステップと、前記サンプル設計を更新すべきであると判断したことに応じて前記サンプル設計を更新するステップと、 を備えている、1つ又は複数の媒体。
- 12請求項11記載の媒体において、タイム・スタンプ付きデバイス位置データを収集するステップが、前記移動体デバイスとのユーザー対話処理の前記複数のインスタンスの各々の間に、前記移動体デバイスと関連のある位置情報を判定するステップを含む、媒体。
- 13請求項12記載の媒体において、位置情報がアドレシング情報を含む、媒体。
- 14請求項12記載の媒体において、位置情報が、指定された地理的位置を含む、媒体。
- 15請求項11記載の媒体において、前記広告を前記移動体デバイスに提供するステップが、更に、実行可能なスクリプトを前記移動体デバイスに供給するステップを含み、前記実行可能なスクリプトが、前記第1時間期間においてユーザーに前記広告を提示させるように構成されている、媒体。
- 16請求項11記載の媒体であって、更に、前記キャッシュと関連のある記憶空間の利用可能量に基づいて、前記広告を選択するステップを備えている、媒体。
- 17予測されたデバイス位置に基づいて、移動体デバイスのユーザーに宛てる広告コンテンツを絞り込む方法を実行するためのコンピューター実行可能命令が具体化されている1つ又は複数のコンピューター読み取り可能媒体であって、前記方法が、 前記移動体デバイスと関連のある位置情報を収集すべき複数のサンプリング時間期間を特定するための、動的に更新可能なサンプル設計を参照するステップと、前記サンプル設計に基づいて、前記複数のサンプリング時間期間の部分集合の各々における前記移動体デバイスとのユーザー対話処理のインスタンスを検出するステップと、 前記移動体デバイスとのユーザー対話処理の各インスタンスを検出したことに応答して、前記移動体デバイスと関連のあるタイム・スタンプ付きデバイス位置データを収集するステップと、 前記収集したタイム・スタンプ付きデバイス位置データから、動的地理−時間モデルを更新するステップと、 第1時間期間を指定するステップと、 前記第1時間期間に対応する前記移動体デバイスとのユーザー対話処理の予測に伴う第1信頼性レベルを判定するステップと、 前記第1時間期間における第1デバイス位置の予測に伴う第2信頼性レベルを判定するステップと、 前記第1および第2信頼性レベルを第1および第2所定の閾値と比較するステップと、 前記移動体デバイス上にあるキャッシュにおける記憶空間の可用性を判断するステップと、 前記第1および第2信頼度レベルの内少なくとも1つが対応する閾値を超過している場合、少なくとも前記第1デバイス位置および前記キャッシュにおける記憶空間に基づいて広告を決定するステップと、 前記広告が前記第1時間期間においてユーザーに提示することができるように、前記広告を提供するステップと、前記動的地理−時間モデルを参照することにより、ユーザーが前記移動体デバイスと対話処理を行う時間期間を予測するステップと、前記予測された時間期間においてユーザーが前記移動体デバイスと対話処理を行わなかった場合に前記サンプル設計を更新すべきであると判断するステップと、前記サンプル設計を更新すべきであると判断したことに応じて前記サンプル設計を更新するステップと、 を備えている、1つ又は複数の媒体。
- 18請求項17記載の媒体において、前記広告が前記第1時間期間においてユーザーに提示することができるように、前記広告を提供するステップが、前記広告を前記第1時間期間においてユーザーに提示すべきことを前記移動体デバイスに示す指示を、前記広告と共に含ませるステップを含む、媒体。
- 19請求項17記載の媒体において、前記広告が前記第1時間期間においてユーザーに提示することができるように、前記広告を提供するステップが、前記移動体デバイスに実行可能なスクリプトを供給するステップを含み、前記実行可能なスクリプトが、前記第1時間期間において前記広告をユーザーに提示させるように構成されている、媒体。
- 20請求項17記載の媒体において、前記第1および第2信頼性レベルの内少なくとも1つに基づいて、前記サンプル設計を更新するステップが、データ収集のインスタンスの頻度およびパターンの内少なくとも1つを変化させるステップを含む、媒体。
Independent claims20
83 paragraphs, as filed
[0001] Mobile communication devices and mobile media devices are rapidly becoming popular among consumers around the world. As mobile devices become more prevalent, so does the likelihood of narrowing down advertising content to users based on the information they can learn about their mobile devices. For example, information about the location of a mobile device is often available, and users of that mobile device can be narrowed down to advertising content that is relevant to that location in context.
[0002] Embodiments of the present invention are defined not by this abstract but by the following claims. Therefore, here, in order to show the whole picture of the present disclosure, the upper whole picture of the embodiment of the present invention is shown.
[0003] In a first exemplary embodiment, a set of computer-enabled instructions provides a method of narrowing down advertising content addressed to a user of a mobile device based on a predicted device position. In one embodiment, the method comprises collecting time stamped device location data associated with the mobile device. Data can be collected according to a dynamically updatable sample design. One embodiment of the method includes updating a dynamic geo-time model that represents geo-time data associated with the device. This geo-time model can be used to predict device locations over a specified time period, and ads can be selected based on this predicted location. The selected advertisement is served to the mobile device and can be configured to be presented to the user for a specified time period. In yet another embodiment of the invention, the sample design and geo-time models are dynamic so that the resulting high accuracy of modeling and prediction is achieved while minimizing processing load and network bandwidth usage. Can be updated to.
[0004] In the second aspect, a set of computer-enabled instructions is directed to the user of the mobile device based on the predicted device location and the predicted user interaction with the device over a specified time period. Provides a way to narrow down the content. A geo-time model can be used to predict instances of user interaction over a specified time period. The position of the mobile device over a specified time period can also be predicted. Based on this prediction, ads can be selected and served to mobile devices. In an embodiment of the invention, the advertisement can be cached on the mobile device for future presentation to the user.
[0005] Yet another embodiment of the invention comprises supplying a mobile device with a script or other executable software module to render an advertisement at a specified time. Other embodiments include periodically updating the sample scheme and periodically updating the geo-time model. Yet another embodiment of the present invention comprises maintaining the collected time stamped device location data for an amount of time and then discarding the old data to make room for new data. .. The decision to discard the data can be based on the efficiency and accuracy associated with the sample design and geo-time modeling aspects of the present invention.
An exemplary embodiment of the present invention will be described in detail below with reference to the accompanying drawings. The drawings are incorporated herein by reference. In the drawing<figref num="1">FIG. 1 is a block diagram showing an example of a computing device according to an embodiment of the present invention.</figref><figref num="2">FIG. 2 is a block diagram showing an example of a network environment suitable for realizing one embodiment of the present invention.</figref><figref num="3">FIG. 3 is a block diagram showing an example of a computing system suitable for realizing one embodiment of the present invention.</figref><figref num="4">FIG. 4 is a schematic diagram showing an example of an advertisement narrowing process according to an embodiment of the present invention.</figref><figref num="5">FIG. 5 is a flow chart showing an example of a method of narrowing down advertisements to users of mobile communication devices according to an embodiment of the present invention.</figref><figref num="6">FIG. 6 is another flow chart showing an example of a method of narrowing down advertisements to users of a mobile communication device according to an embodiment of the present invention.</figref><figref num="7">FIG. 7 is another flow chart showing an example of a method of narrowing down advertisements to users of a mobile communication device according to an embodiment of the present invention.</figref>
[0014] An embodiment of the present invention provides a system and method for narrowing down advertisements to users of a mobile communication device or a mobile media device based on a predicted device position in a specified time period. When narrowing down advertising content to users of mobile devices, it's more relevant by understanding where customers spend most of their time, or where they are likely to be at a particular time. It enables you to narrow down certain advertising content, which also increases the probability of getting compensation from advertising. Therefore, an embodiment of the present invention proposes to predict the position of the user at a specific time point and narrow down the advertising content to the user based on the predicted position. for). Information about the location of the mobile device at different times and at different days is collected over a period of time. The number of times the device location information is connected and the time period for collecting it can be specified by a dynamically updatable sample design. The sample design can also be modified to increase the usefulness of the collected information and can be referenced to determine exactly when the information should be collected. While collecting device location information, this information can be analyzed to create a mathematical model of the device location information at different time points, which can be used to predict the position of the mobile device over a specified time period. can do. This mathematical model is referred to herein as the "geo-temporal model". This reflects the fact that the model contains information about the location of the device ("geography") at a particular point in time ("temporal").
[0015] Embodiments of the present invention include, for example, when the user interacted with the mobile device, how long the user spent interacting with the mobile device, and the storage space available on the mobile device. It also includes a collection of other types of data, such as whether or not there is. This and other information can be incorporated into a mathematical model to enhance the predictive power of this model and provide additional context for consideration when choosing the advertising content to serve to users. it can. As information is gathered over time, this mathematical model can also be dynamically updated to maintain, and perhaps improve, the accuracy of the model. In addition, embodiments of the present invention also include a mechanism for dynamically updating the sample design. As information is collected over time, evaluate the sample design to determine if it can be improved to provide a sample of more useful information based on the collected information and the robustness of the geo-time model. be able to. By allowing the sample design to be dynamically updated to collect geo-time data, and further by allowing the geo-time model used to make predictions to be dynamically updated, the present invention. Embodiment promotes efficient and highly accurate filtering of advertisements to users of mobile communication devices.
[0016] Throughout the description of the invention, various acronyms and abbreviations are used to aid in understanding certain concepts of related systems and services. These acronyms and abbreviations are intended to help provide an easy way to convey the ideas expressed herein and are not meant to limit the scope of the invention. ..
The present invention is described in the general context of computer code or machine-enabled instructions. Machine-enabled instructions include computer-executable instructions, such as program modules, executed by a computer or other machine, such as a personal data assistant or other handheld device. Program modules generally refer to code that includes routines, programs, objects, components, data structures, etc., to perform a particular task, or to implement a particular abstract data type. The present invention can be implemented in a variety of system configurations, including handheld devices, consumer electronics, general purpose computers, and more specialized computing devices. The present invention can also be implemented in a distributed computing environment, in which tasks are performed by remote processing devices linked through a communication network.
Computer-readable media include both volatile and non-volatile, removable, and non-removable media, assuming media that can be read by databases, switches, and various other network devices. As an example, and without limitation, computer-readable media also include media realized in any method or technique for storing information. Examples of stored information include computer-enabled instructions, data structures, program modules, and other data representations. Examples of media include, but are not limited to, information distribution media, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROMs, digital versatile discs (DVDs), holographic media or other optical disc storage. , Magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices. These techniques can store data instantaneously, temporarily, or permanently.
[0019] In order to define a comprehensive context for the various aspects of the invention, an example of an operating environment in which the various aspects of the invention can be realized will be described below. First, with particular reference to FIG. 1, an example of an operating environment for carrying out an embodiment of the present invention is shown, which is generally referred to as a computing device 100. The computing device 100 is merely an example of a suitable computing environment and is not intended to imply any limitation on the scope of use or functionality of the present invention. In addition, the computing environment 100 must not be interpreted as having any dependency or essential requirement for any one or combination of the illustrated components.
[0020] The computing device 100 includes a bus 110 that directly or indirectly connects the following devices. Memory 112, one or more processors 114, one or more presentation components 116, I / O ports 118, I / O components 120, and an exemplary power supply 122. The bus 110 may represent one or more buses (address bus, data bus, or a combination thereof, etc.). The various blocks in FIG. 1 are shown with lines for clarity, but in reality the division of the various components is less clear, and figuratively, if these lines are shown more accurately. , Will be gray and ambiguous. For example, a presentation component, such as a display device, can also be considered an I / O component. Also, the processor has memory. This is the essence of the art, and the diagram of FIG. 1 merely illustrates an example of a computing device that can be used in conjunction with one or more embodiments of the present invention. The inventor is aware. No distinction is made between categories such as "workstation", "server", "laptop", "handheld device", etc. This is because everything is considered to fall within the scope of FIG. 1 and relates to "computers" or "computing devices".
[0021] The memory 112 includes a computer storage medium in the form of volatile and / or non-volatile memory. The memory can be removable, non-removable, or a combination thereof. Examples of hardware devices include solid state memory, hard drives, optical disk drives, and the like. The computing device 100 includes one or more processors that read data from various entities such as memory 112 or I / O component 120. The presentation component (s) 116 presents data instructions to the user or other device. Examples of presentation components include display devices, speakers, printing components, and the like.
[0022] The I / O port 118 allows the computing device 100 to be logically coupled to other devices including the I / O component 120. Some of the other devices may be built-in. Illustrative components include microphones, joysticks, gamepads, satellite dishes, scanners, printers, wireless devices, keyboards, pens, voice input devices, contact input devices, touch screen devices, interactive display devices, etc. Or a mouse is included.
[0023] Moving to FIG. 2, an example 200 of a network environment for realizing the embodiment of the present invention is shown. The network environment 200 includes an ad (AD) network 210, a content provider 212, and a mobile network 214, one or more of which may facilitate the narrowing down of advertisements to a large number of mobile devices 216. it can. The mobile device 216 communicates with the advertising network 210 and the content provider 212 through the mobile network 214, LAN 220, and / or network 222. Networks 210, 214, 220, and 222 are referred to as, for example, a local area network (LAN), wide area network (WAN), Internet, cellular network, peer-to-peer network, or a combination of networks. Any suitable network, such as, can be included. The network environment 200 is merely an example of a suitable network environment and is not intended to imply any limitation on the scope of use or functionality of the present invention. Also, the network environment 200 shall not be construed as having any dependency or requirement with respect to any one component or combination of components exemplified herein.
[0024] The mobile device 216 can be any type of mobile device capable of presenting content to the user, eg, periodically with the mobile network 214 or some other network 220, 210, or 222. It can include mobile devices that communicate and devices that periodically communicate with networks 210, 214, 220, or 222. In one embodiment, the mobile device 216 can be, for example, a computing device such as the computing device 100 described above with reference to FIG. According to embodiments of the present invention, the mobile device 216 is a type of mobile device such as, for example, a cellular phone, a personal digital assistant (PDA), a smartphone, a laptop computer, a handheld computing device, and the like. If so, any number can be included. In addition, in the embodiment, the mobile device 216 also includes a cache for storing information or other content.
[0025] In one embodiment, the mobile device 216 is a media content presentation device, which devices network 210, 214, 220, and / or 222, for downloading media content, etc. And / or can communicate with content provider 212. Examples of media content presentation devices include, but are not limited to, Zune music devices, portable video games and gaming systems available from Microsoft Corporation in Redmond, Washington. Is done. In another embodiment, the mobile device 216 is a removable memory device, such as, for example, a removable memory unit for XBOX available from Microsoft Corporation (Microsoft) in Redmond, Washington. Can be done.
[0026] Content provider 212 may include a server or other computing device capable of transmitting content to other devices, such as mobile device 216. In another embodiment, the content provider 212 includes a network. Content can include, for example, documents, files, search results, applications, music, videos, scripts, streaming multimedia and the like. In one embodiment, the content provider 212 can supply content to the mobile device 216 through or directly to the mobile network 214 or network 222. In some embodiments, the content provider 212 may be part of network 210, mobile network 214, or LAN 220. In other embodiments, the content provider 212 is independent of the other elements shown in FIG. 2 and described above.
[0027] The computing device 218 can be any computing device capable of communicating with networks 210, 214, 220, or 222, and / or content provider 212 according to various embodiments of the invention. Is. In one embodiment, for example, the computing device 218 is a computing device similar to the computing device 100 shown in FIG. The computing device 218 can be, for example, a personal computer (PC), a laptop computer, a notebook computer, a tablet computer, a PDA, a smartphone, a terminal, or the like.
[0028] In one embodiment, for example, the computing device 218 is a personal computer that the user has at home or at work. The user can connect the mobile device 216 to the computing device 218 so that they can communicate with each other. The computing device 218 can include software, hardware, firmware, and the like that can be used to communicate with the mobile device 216. For example, in one embodiment, the mobile device 216 is a portable media player, such as, for example, a ZUNE device or an MP3 player. The user can use an application for connecting the mobile device 216 to the computing device 218 and uploading media content such as music, video, etc. from the computing device 218 to the mobile device 216. In some embodiments, the computing device 218 uses an application programming interface (API) or application to communicate with the mobile device 216 to update files, folders, playlists, etc. on the mobile device 216. In some cases it can be done. In another embodiment, the computing device 218 can facilitate communication between the mobile device 216 and the network 210, 214, 220, or 2202, or the content provider 212. In this way, the mobile device 216 can derive content, updates, media content, and advertisements from content provider 212 or other entities associated with networks 210, 214, 220, or 222.
[0029] In another embodiment, the computing device 218 is described, for example, by Microsoft in Redmond, Washington. An XBOX-like video game system available from Corporation (Microsoft). The mobile device 216 stores user profiles, game data, media content, or other content, allowing the user to perform numerous computings such as other video game systems, computers, media players, etc. It can be a memory device that can be connected to any one of the devices 218. In yet another embodiment, the computing device 218 can communicate with a kiosk, a public network access terminal, a media management system that may be available on a TV in a hotel room, or a mobile device 216. It can be another device. According to embodiments of the present invention, the computing device 218 can communicate with one or more of the other elements shown in FIG. For example, in one embodiment, the computing device 218 can communicate with the advertising network 210 and / or the content provider 212 either directly or indirectly through LAN 220. In other embodiments, the computing device 218 can communicate with an advertising network 210, a content provider 212, a mobile device 216 (through mobile network 214), or another network node (not shown).
[0030] According to one embodiment of the invention, data can be obtained from the mobile device 216 that provides information about the current location of the mobile device 216. It should be acknowledged by those skilled in the art that location information about the mobile device 216 is also available in a number of different ways. For example, a component of the mobile network 214 (eg, location server, presence server, router, etc.) can determine the location associated with the mobile device 216 communicating through the mobile network 214. Depending on the embodiment, the position information may be extracted by PGS technology. In other embodiments, triangulation techniques with a large number of cell towers can also be used to determine device location information. In yet another embodiment, satellite position detection techniques can be used to determine position information associated with the mobile device 216. The mobile network 214 provides device location information to entities outside the mobile network 214, such as, for example, network 210, network 222, LAN 220, computing device 218, content provider 212, or mobile device 216. can do.
[0031] In one embodiment, the mobile device 216 includes a technique for determining its position, or a technique for confirming information related to its position. The mobile device 216 can then transmit the information to another entity, or the other entity can retrieve the data from the mobile device 216. In yet another embodiment, when the mobile device 216 communicates with another device, the mobile device 216 is associated with identification information such as addressing information, presence information, and the like. For example, in one embodiment, the mobile device 216 can be associated with an Internet Protocol (IP) address, MAC address, network port, or any number of other types of addressing or location detection information. .. Information about the location of the mobile device 216 can be confirmed by analyzing the IP address, MAC address, and so on. In some embodiments, the mobile device 216 can utilize addresses associated with computing devices 218, ISPs, LAN 220, and the like. Communication can be monitored to detect, record, and analyze addressing information, presence information, and other types of information associated with the location information of the mobile device 216.
[0032] Continuing with reference to FIG. 2, the advertising network 210 includes an advertising source 224, an advertising server 226, and a geo-time advertising server 228. In one embodiment of the invention, the ad network 210 is a component that facilitates the delivery and / or presentation of ads to various destinations, such as mobile device 216, computing device 218, and content provider 212. Includes servers, modules, or other technologies. The advertising network 210 is merely an example of a suitable advertising network environment and is not intended to imply any limitation on the scope of use or functionality of the present invention. Also, the advertising network 210 shall not be construed as having any dependency or requirement with respect to any one component or combination of components exemplified herein.
[0033] The advertising source 224, advertising server 226, and geo-time filtering server 228 can be implemented on any number of types of computing devices. In one embodiment, for example, the advertising source 224, the advertising server 226, and the geo-time filtering server 228 can be implemented on a computing device such as the computing device 100 shown in FIG. In one embodiment, the ad source 224, the ad server 226, and the geo-time refinement server 228 are each implemented on separate machines. In another embodiment, the ad source 224, the ad server 226, and the geo-time filtering server 228 are implemented on one machine or on a distributed processing system using various interconnected machines. In yet another embodiment, the combinations of components 224, 226, and 228 can be implemented on any number of machines and according to any number of different combinations.
[0034] The components of the advertising network 210 are also scalable. That is, in the embodiment of the present invention, the number of components can be changed. For example, in one embodiment, the ad network 210 includes one ad source 224, one ad server 226, and one geo-time refinement server 228. In another embodiment, the advertising network 210 may include only one or only two of the components 224, 226, and 228. In yet another embodiment, the ad source 224, the ad server 226, and / or the geo-time refinement server 228 can be maintained outside the ad network 210. Any number of configurations having geo-time narrowing capability as described below can be suitable for realizing the embodiments of the present invention.
[0035] The advertisement source 224 provides an advertisement for presentation to the user of the mobile device 216. In one embodiment, the ad source 224 is a content server with a storage 225 for storing ads, which also links to ads, information about ads, metadata, device location data, user profile information, and so on. Can include. In one embodiment, the ad source 224 can be a server, a computing device, or a software module that can provide the ad or a link to the ad to the mobile device 216. In embodiments, the ad source 224 may be a computing device associated with the company that produces the ad. In another embodiment, the ad source 224 can be a server that is associated with various originating entities and collects, maintains, and manages a large number of advertisements received from them. It should be acknowledged that the advertising source can be designed to operate in various business models, purchasing methods, etc.
[0036] In one embodiment, the advertising source 224 includes storage 225. In one embodiment, the storage 225 can support an advertising (AD) database 227. In other embodiments, the advertising database can be associated with advertising server 226, geo-time filtering server 228, or other components of advertising network 210 not shown in FIG. The advertising database 227 can be maintained on one device, or can be distributed across various devices, for example, as in an embodiment in which the advertising database 227 is a database cluster. The advertising database 227 can be constructed according to various techniques and is configured to be searchable. For example, in one embodiment, the advertising database 227 includes a table. In another embodiment, the advertising database 227 is a relational database. The relational database contains an advertisement identifier that identifies an advertisement stored in storage 225 and data associated with various attributes corresponding to the advertisement identifier. The advertising identifier can include a dynamically generated identification code, hyperlink, URL, or other addressing or identification information. In one embodiment, one attribute or the plurality of attributes can represent information indicating a geographical area in which an advertisement corresponding to a related advertisement identifier should be presented.
[0037] For example, in one embodiment, an advertising provider, such as advertising source 224, may specify a particular geographic area in which the advertisement should be presented to the user. Thus, for example, a local sandwich store can be designated to present an advertisement for the store to the user when the user is within a certain distance of the store. In another embodiment, the store may be designated to play ads to users in the same town, users in the same city block, and so on.
[0038] According to another embodiment, the advertising database 227 can include scripts, APIs, or other software modules that facilitate the presentation of advertisements to users of the mobile device 216. For example, in one embodiment, the advertisement can be cached on the mobile device 216 for later presentation. The advertisement may include a tag or other instruction that prompts the mobile device 216 to present the advertisement at a specific time point or when a specific event occurs. In one embodiment, the advertisement can be configured to be presented when the user interacts with the mobile device 216 in a particular geographic area.
[0039] According to one embodiment, the script is cached on the mobile device 216, and when the specified conditions are met, the script accesses the cached advertisement and advertises to the user. It can be presented. The specified conditions can include, for example, the occurrence of a specified time period, user interaction with the mobile device 216, and the like. In another embodiment, the script accesses the mobile device 216, or to the mobile device 216 for remote advertising, such as, for example, ad source 224, server 226, or geo-time refinement source 228. Can be accessed. According to another embodiment, the API is cached on the mobile device 216 or maintained on the ad network component 210, and when the specified conditions are met, the API is called to present the advertisement. Can also be facilitated.
[0040] Further, the advertisement database 227 can be configured to store information associated with various types of advertisements. In various embodiments, such information is not limited, and one or more unapparent advertisements, one or more image advertisements, one or more virus purification / warning advertisements, one or more. It can include multiple user feedback ads, advertiser and / or publisher identities, and so on. In some embodiments, the advertising database 227 is configured to search for one or more advertisements selected for presentation. This will be described in more detail below.
It should be noted that the information stored in the advertisement database 227 should be configurable, and it goes without saying that any information related to the advertisement may be included, which is recognized by those skilled in the art. Let's see. Further, although the ad database 227 is illustrated as one independent component, it may actually be a plurality of databases, such as a database cluster, some of which are with the ad source 224 or the ad server 226. It can be located in the relevant computing device, geo-time advertising server 228, mobile device 216, other external computing device (not shown), and / or any combination thereof.
[0042] Continuing with reference to FIG. 2, the advertising network 210 includes an advertising server 226. As shown above, in some embodiments, the ad server 226 can be implemented on the same machine as the ad source 224 and / or the geo-time refinement server 228. In another embodiment, the advertising server 226 can be implemented independently of the other components of the advertising network 210. The advertising server 226 can be any type of server, software module, computing device, etc. that can communicate with other devices. The advertising server 226 provides the advertisement or a link to the advertisement to other devices such as mobile device 216, content provider 212, computing device 218, and the like. In some embodiments, the advertisement may include hyperlinks or other types of references that allow users to access websites, information, databases, and the like. Ad server 226 facilitates user interaction with these ads by resolving references, mapping hyperlinks to addresses, pulling websites, searching for content, and rendering content. can do. In some embodiments, the advertising server 226 may be able to provide a click-through service to report the user's interaction with the content.
[0043] Advertising server 226 may include storage 229. The storage 229 may include, for example, an advertisement database 227, a cache for temporarily storing advertisements and / or other contents, and then providing these advertisements and / or other contents to users. In addition, in some embodiments, the advertising server 226 may be integrated with the advertising source 224. In other embodiments, the advertising server 226 may be integrated with the geo-time filtering server 228. According to another embodiment, the advertising server 226 can be configured to receive geographic-time filtering information from the geo-time filtering server 228 and use that information to select the appropriate advertisement. In one embodiment, the advertising server 226 generates a searchable index of advertising and related data stored in the advertising database 227. The advertising database 227 can be implemented on an advertising source 224, an advertising server 226, or a geo-time filtering server 228.
[0044] The index and / or advertisement database 227 can include a weighting scheme to facilitate the determination of which advertisement should be served in various situations. For example, ads can be ranked or weighted. In one embodiment, the information contained in the index may include annotations or attributes associated with the advertisement, which indicate the situation in which the annotations or attributes should serve the advertisement. In another embodiment, the advertising database 227 may include similar annotations or attributes. For example, a particular product or company can have a variety of ads related to it, of which a limited number of ads can be ranked higher than other ads. Therefore, in the appropriate circumstances, the higher ranked ads can be selected first, and if there is available bandwidth, memory, time, etc., additional ads, in the order indicated by the annotations or attributes. Can be provided. The ad server 226 can query the index using geo-time refinement information in the query definition to select the appropriate ad to present to the user at a particular point in time and at a specified geographic location.
[0045] Depending on the embodiment, the advertisement may be selected by another component of the advertisement network 210. In various embodiments, the advertising server 226 delivers selected advertising (or associated information) from any number of sources, such as, for example, advertising database 227, advertising source 224, content provider 212, and so on. Pull out. The advertising server 226 propagates the advertisement and related information to various devices such as the mobile device 216. Therefore, to the user by rendering the content provided by the advertising server 226, by selecting a hyperlink to the content, or by any other means of accessing the advertising material provided by the advertising server 226. Advertisements can be presented.
The geo-time filtering server 228 includes a mobile predictive filtering engine (MPTE) 236 and data storage 234. In one embodiment, data storage 234 includes a historical user behavior database. Data storage 234 can be configured to store information associated with multiple system users and their associated user behavior. This will be described in more detail below. In various embodiments, such information is not limited, but is limited to one or more user personal information, one or more probabilities about the user, one or more scores assigned to the user, related to the user. It can include a mobile device, location information with a time stamp, and so on. Depending on the embodiment, the data storage 234 may be configured to search for one or more user personal information and related information based on, for example, an IP address or the like. This will be described in more detail below.
It goes without saying that the information stored in the data storage 234 may be configurable and may include any information about the user and user behavior related to them. , Will be recognized by those skilled in the art. Further, although illustrated as one independent component, the data storage 234 may actually be a plurality of databases, eg, a database cluster, some of which are ad source 224, ad server 226, and so on. Geography-Time Advertising Server 228, Content Provider 212, Mobile Network 212, Computing Device 218, Mobile Device 216, Computing Devices Related to Other External Computing Devices (not shown), and / or theirs. It can be located in any combination.
[0048] According to one embodiment of the invention, the MPTE 236 collects time stamped location information associated with the mobile device 216. This information can include, for example, a description of the geographic area, time of day, day of the week indication, time since the last data was collected for the device, duration of connection with the device or user interaction, and the like. MPTE 236 includes a database 241 that can be used to store time stamped location information associated with the mobile device 216. In one embodiment, the database 241 can include a table, a relational database, or any other database construction method that can provide a searchable warehouse for time stamped location data.
In embodiments, the database 241 can include a number of unique mobile device identifiers (MDIDs), each of which corresponds to a particular mobile device 216. The information collected by the MPTE 236 can be associated with the MDID corresponding to the mobile device 216 to which the information is associated. The database 241 also includes information indicating the type of device for the mobile device 216, the amount of storage space available in the cache on the mobile device 216, and other user behavior data that can be used to filter advertisements. Can include. Other user behavior data that can be used to narrow down ads is, for example, data such as a user profile or device profile that includes demographic information, user preference information, device configuration and capability information, presence information, and the like. ..
[0050] The information stored and maintained in the database 241 can be updated periodically. In one embodiment, the time stamped device location information associated with the mobile device 216 can be maintained in database 241 for any amount of time desired. In one embodiment, this information is retained for days or weeks, after which this information is discarded. In this way, the database 241 can be configured to maintain a reasonable amount of available storage and only retain enough data to create and / or update user or device profiles. It can also be configured to do so. According to various embodiments, the user profile or device profile (collectively referred to herein) can include any type of information maintained by database 241. In addition, the profile is, for example, device location information, user behavior information (eg, information about the user's interaction with the mobile device 216), and any other type of information that may be relevant to advertising refinement. It is also possible to include a mathematical model representing such variables. According to one embodiment, the information maintained in the database 241 and updated by MPTE236 can be used to predict future device location information, user dialogue processing, and the like.
[0051] Continuing with reference to FIG. 2, Example 200 of this network architecture is merely an example of a suitable network environment that can be realized to carry out aspects of the invention, and what is the scope and functionality of the invention. It is not intended to imply any limitation of. Also, the illustrated network architecture example 200 or MPTE236 has some dependency on any one or combination of the illustrated components 210, 212, 214, 216, 218, 220, 222, 224, 226, or 228. Or it should not be interpreted as having requirements. Depending on the embodiment, one or more of the components 210, 212, 214, 216, 218, 220, 222, 224, 226, or 228 may be realized as a single device, a wireless network, or the like. In other embodiments, one or more of the components 210, 212, 214, 216, 218, 220, 222, 224, 226, or 228 may be integrated directly into the mobile device 216. It should be noted that the components 210, 212, 214, 216, 218, 220, 222, 224, 226, or 228 shown in FIG. 2 are exemplary in their essence and quantity and should not be construed as limitations. Needless to say to a person skilled in the art.
[0052] Therefore, any number of components can be used to achieve the desired function within the embodiments of the present invention. The various components in FIG. 2 are shown with lines for clarity, but in reality the division of the various components is less clear and, figuratively, if these lines are shown more accurately. , Will be gray and ambiguous. Further, although some of the components of FIG. 2 are illustrated as one block, this illustration is exemplary in nature and quantity and should not be construed as a limitation.
[0053] Moving to FIG. 3, a block diagram of an example 300 of a system embodiment of an embodiment of the present invention is shown. System Embodiment 300 is merely an example of a suitable network environment and is not intended to imply any limitation on the scope of use or functionality of the present invention. Also, system embodiment 300 shall not be construed as having any dependency or requirement with respect to any one component or combination of components exemplified herein.
[0054] An exemplary system embodiment 300 includes a mobile device 310, a third party source 312, a mobile predictive refinement engine (MPTE) 317, and an advertising network 318. The mobile device 310 includes a cache 315. As previously indicated, the cache 315 can be used to store advertisements and information related to advertisements, according to embodiments of the present invention. In one embodiment, the stored advertisement can be presented to the user of the mobile device 310 at a later time. In addition, the mobile device 210 can be configured to check the amount of space available for cache. The amount of space available can be propagated to other elements of System Example 300, such as MPTE 317, third party sources 312, and / or advertising network 318. In another embodiment, the external device can check the amount of space available on the cache. For example, the MPTE 317 can also be configured to check and / or withdraw cache availability from the mobile device 310.
[0055] According to one embodiment, as shown in FIG. 3, the ad network 318 includes an ad distribution component 320, an ad selection component 322, and an ad store 324. It goes without saying that each of these components 320, 322, and / or 324 can be implemented in one machine, many machines, or a distributed computing environment.
[0056] MPTE317 includes sampling component 326, modeling component 336, prediction component 346, update component 348, data store 334, sample design store 340, and geo-time model store 344. Depending on the embodiment, one or more of the components 326, 336, 346, 348, 334, 340, and 344 may be implemented as a single application. In other embodiments, the components 326, 336, 346, 348, 334, 340, and 344 are the geo-time advertising server 228, advertising server 226, advertising source 224, content provider 212, or mobile device of FIG. In some cases it may be desirable to integrate directly into the 216 operating system. As an example only, MPTE317 can be accommodated in association with the advertising database 225 of FIG. In the case of a large number of servers, the present invention considers providing a load balancer to federate incoming queries to these servers. It goes without saying to those skilled in the art that the components 326, 336, 346, 348, 334, 340, and 344 shown in FIG. 3 are examples in their essence and quantity and should not be construed as a limitation. is there. Any number of components or modules can be used to achieve the desired function within the embodiments of the present invention.
[0057] The sampling component 326 is configured to facilitate the collection of information associated with the mobile device 310. In one embodiment, the sampling component 326 collects information according to a dynamically updatable sample design maintained in the sample design store 340. A unique sample design can be associated with each mobile device 310. In addition, the sample design store 340 can include a total sample design associated with more than one mobile device 310. The sample design can include lists, tables, sampling distributions, equations, algorithms, and the like.
[0058] The sample design can also be dynamically updated. As shown in FIG. 3, the modeling component 336 includes a sample design engine 338. The sample design engine 338 creates, updates, replaces, and otherwise manages sample designs. According to this sample design, the sampling component 326 collects data associated with various mobile devices 310. The sample design engine 338 communicates with the sample design store 340. In another embodiment, the sample design store 340 can be integrated with the sample design engine 338. In these and other embodiments, the sample design engine can create a new sample design associated with the mobile device 310 and store that design in the sample design store 340. The sample design engine 338 can update the design in the sample design store 340.
[0059] According to one embodiment of the present invention, the sample design engine 338 can update the sample design by exchanging the sample design with an updated version. In another embodiment, the sample design engine 338 can derive the sample design or otherwise access the sample design and modify the design. In the latter embodiment, the processing power associated with the sample design engine 338 can be minimized. In the former embodiment, the sample design engine 338 can utilize templates that facilitate quick and structured changes in the sample design.
[0060] The sample design engine 338 can update the sample design periodically or continuously. Updates can be user-defined, depending on the embodiment. In addition, the sample design engine 338 can automatically create updates. In one embodiment, the sample design engine 338 receives instructions from the update component 348 to update the sample design. For example, update component 348 can receive information related to other processes within MPTE317. In one embodiment, the update component 348 takes in a geo-time model as input. This geo-time model is maintained in the geo-time store 344 and can be created, updated, and otherwise managed by the data modeling engine 342. The update component 348 can also take as input the predictions identified by the prediction component 346 and the data associated with the accuracy of the predictions. In one embodiment, the data associated with the accuracy of the prediction can be obtained from the sampling component 326. In one embodiment, the update component 348 can generate a statistical model using, for example, a Bayesian network, a neural network, a probability distribution function, and the like. This statistical model can be used to estimate the probabilities associated with obtaining highly accurate predictions from geo-time models given the data collected according to the current sample design. Based on the resulting probability assessment, the update component 348 can determine that a new sample design is guaranteed.
[0061] In other embodiments, the update component 348 can generate a simpler model to determine when to update the sample design. For example, the prediction component 346 is based on a geo-time model in which User A uses a specified time period mobile device 310, for example, between 3 pm and 4:30 pm on September 26, 2008. It can be predicted that the dialogue processing will be performed with. During this designated time period, the sampling component 326 may attempt to determine whether the user interacts with the mobile device 310. If the user interacts with the mobile device 310 during this specified time period, the update component 348 may determine that no refinement or modification of the corresponding geo-time model is required. On the other hand, if the user does not interact with the mobile device 310 during this specified time, the update component 348 should update either the sample design or the geo-time model to improve the accuracy of the prediction. Can be judged. In addition, in some embodiments, both the sample design and the geo-time model can be updated.
[0062] As shown in FIG. 3, the mobile network can be a third party content source 312. As described above, the third party content source 312 is an interactive data source 314 that provides information related to user interaction with the mobile device 310 and the mobile device 310 at various time points. It can include a location data source 316 that provides information related to the location of. In some embodiments, the mobile device 310 can be a mobile media presentation device, such as a portable video game system, a portable music player, and the like. The user can occasionally connect the mobile device 310 to a computing device or a distant entity over a network to retrieve updates, content, etc. In this case, the third party source 312 is the computing device to which the mobile device 310 is connected, the content provider that communicates with the mobile device 310, or data about user interaction and location associated with the mobile device 310. Can include any other device, machine, software module, etc. that can collect and report. In yet another embodiment, the third party source 312 may be absent and user interaction data and location data can be sourced from the mobile device 310, from the addressing information associated with the mobile device 310, and from the mobile device 310. It can be directly extracted by monitoring network traffic including communication of the above.
[0063] The sampling component 326 includes a position detection module 328, a cache module 330, and an interactive processing module 332. The position detection module 328 and the dialogue processing module 332 facilitate the acquisition of the position information and the user dialogue processing information, respectively. In one embodiment, the position detection module 328 can interface with the position data source 316 to extract location information, and the dialogue processing module 332 interfaces with the dialogue processing data source 314 to provide user dialogue processing information. Can be pulled out. In another embodiment, the sampling component 326 receives the data through a more generalized communication port, and the location detection module 328 and the dialogue processing module 332 identify and separate the location information and the user dialogue processing information, respectively. And facilitate aggregation. In embodiments, the information collected by the sampling component 326 can be maintained in the data store 334. In some embodiments, the information associated with the particular mobile device 310 is retained for a period of time (eg, days, weeks, etc.) in the data store 334. The update component 348 can determine whether everything related to the mobile device 310 in the stored data needs to be retained in order to maintain a high-precision map-time model. If it is not needed, the data can be discarded from the data store 334 and new data can be collected to facilitate further improvement of the geo-time model.
[0064] The cache module 330 can facilitate determining the storage space availability associated with the cache 315 on the mobile device 310. In one embodiment, the mobile device 310 includes a cache management component capable of checking and reporting storage space availability within the cache 315. In another embodiment, the cache module 330 can be configured to check the amount of storage available in the cache 315. The storage and related information available in cache 315 is also directly to the data store 334, ad selection component 322, and / or any other component or combination of components implemented within Example 300 of the system environment. Can be communicated. In this way, ads can be selected based on information from the geo-time model and the availability of storage space in cache 315. As described above, during a specified time period based on information obtained from the corresponding geo-time model, other behavioral information, user profiles, user preferences, device type of mobile device 310, etc. A set of advertisements can be identified as suitable for presentation to the user of the mobile device 310. If sufficient storage space is available in cache 315 to accommodate the first subset of higher ranked advertisements, these can be selected for presentation. In addition, if extra space still remains in the cache 315, a second subset of advertisements can also be selected for presentation, and so on.
[0065] With reference to FIG. 3, MPTE 317 also includes modeling component 336. Modeling component 336 includes a sample design engine 338 and a data modeling engine 342, as previously indicated. The sample design engine 338 creates, updates, and manages sample designs for the mobile device 310. The data modeling engine 342 generates, updates, and manages the geo-time model corresponding to the mobile device 310. The data modeling engine 342 can also organize, sort, classify, and otherwise analyze data such as time-stamped device location data. The data modeling engine 342 can utilize any number of model types to model the geo-time information associated with the mobile device 310. For example, the data modeling engine 342 can be used to estimate the probability density function associated with the distribution of the data collected by the sampling component 326. In other embodiments, the data modeling engine 342 can be used for regression analysis, ANOVA analysis, and / or other techniques that can be used to model geo-time data associated with the mobile device 310. Any number can be executed. In some embodiments, the data modeling engine 342 may be able to use different techniques for different mobile devices 310, depending on the pattern of behavior associated with the mobile device 310. In addition, the data modeling engine models weighted graphing techniques, Bayesian networks, neural networks, machine learning, multivariate regression analysis, and data associated with mobile device 310. Other techniques can be used.
[0066] On the other hand, the update component 348 can abstract various types of inspections, models, etc. to determine a measure of the accuracy of the geo-time model associated with the mobile device 310, if necessary. , Can work with the data modeling engine 342 to update the geo-time model. Similarly, the update component 348 can determine the efficiency and accuracy attributes associated with the sample design corresponding to the mobile device 310. If necessary, the update component 348 can work with the sample design engine 338 to update the sample design. In addition, in some embodiments, the update component 348 uses information from the sample design engine 338, sample design store 340, data modeling engine 342, and / or geography-time model store 344 to design or geography the sample. -Can determine if any of the time models should be improved. It should be acknowledged by those skilled in the art that, in some circumstances, simultaneous improvement of both the sample design and the geo-time model can be guaranteed.
[0067] The prediction component 346 can use the geo-time model maintained in the geo-time model store 344 to predict the geographic location of the mobile device 310 over a specified time period. In addition, the prediction component 346 can be used to predict an instance of user interaction with the mobile device 310 at a specified time and at a specified geographic location. In some embodiments, the prediction component 346 supplies a designated input to a geo-time model such as a regression equation, probability density function, etc., and uses the model to calculate a probability prediction of future behavior to make a prediction. be able to. In other embodiments, the prediction component 346 can identify the reliability level associated with the various specified time periods and the corresponding potential geographic or user interaction data. The reliability level can be represented, for example, by an index or attribute that provides information about how well a user meets a set of criteria established by an advertising provider. The prediction component 346 compares the reliability level or index with a predetermined reliability level threshold or a predetermined index threshold to determine which location prediction and user dialogue processing prediction are likely to be the most accurate. Can be done. In one embodiment, a predetermined threshold is selected so that the spending of the advertisement is maximized with respect to user exposure to the advertisement. For example, in one embodiment, if the corresponding reliability level is higher than 80%, the advertisement is selected for presentation at the predicted location. Here, 80% is the reliability level threshold. In another embodiment, if the corresponding index is greater than the threshold index, the ad is selected for presentation at the predicted position. For example, in other embodiments where the presentation of the advertisement is costly, a high reliability level threshold such as 90% can be utilized as the cost increases.
[0068] For example, the predictive component 346 utilizes a geo-time model associated with the mobile device 310 so that on the afternoon of September 26, 2008, the mobile device 310 will be in position 1 during that specified time period. It can be determined that the reliability level associated with the prediction is 30%, and the reliability level that the mobile device 310 is in position 2 during the specified time period is 90%. Therefore, the prediction component 346 can supply the advertisement selection component 322 with data related to the prediction regarding the position 2, and then the advertisement selection component 322 can select an advertisement suitable for presentation at the position 2.
[0069] Further referring to FIG. 3, example 300 of the system embodiment includes an advertising network 318. The ad network 318 includes an ad distribution component 320, an ad selection component 322, and an ad store 324. In various embodiments, any one or more of the ad distribution component 320, the ad selection 322, and the ad store 324 can be implemented on one machine. In other embodiments, each component 320, 322, and 324 can be implemented independently of the other components. In one embodiment, for example, the ad distribution component 320, the ad selection component 322, and / or the ad store 324 can be maintained on the ad server 226 shown in FIG. In another embodiment, for example, the ad distribution component 322 is implemented on the ad server 226, the ad store 324 is implemented on the ad source 224, and the ad selection component 322 is implemented on the geo-time refinement server 228. In some embodiments, any combination of components 320, 322, and 324 can be implemented on any combination of ad source 224, ad server 226, and geo-time refinement server 228. In yet another embodiment, any combination of components 320, 322, and 324 can be implemented in conjunction with, or integrated with, an embodiment of MPTE317. These are only some of the exemplary embodiments, and many other embodiments that can be used to provide the functionality of the invention described herein also fall within the scope of the invention. To do.
[0070] The advertisement distribution component 320 facilitates the presentation of advertisements to users of the mobile device 310. In one embodiment, the advertisement distribution component 320 provides the advertisement to the mobile device 310. The advertisement may include actual advertisement content, information about the advertisement content, hyperlinks to the advertisement, references to the advertisement, coupons, and the like. In addition, according to embodiments of the present invention, the advertisement can include scripts, software modules, and APIs that can be called to render the advertisement content on the display of the mobile device 310. Advertisements can be in any number of different formats, such as audio, video, text, graphics, etc. In some embodiments, the ad may be interactive, and in other embodiments, the ad may be accompanied by a click-through feature so that user interaction with the ad can be monitored and recorded. There is also. In some embodiments, the ad distribution component 320 unravels the reference, maps the connection through a hyperlink, pulls out the ad content, streams the content to the mobile device 310, monitors click-through, and so on. .. In other embodiments, any one or more of these functions may be performed by other components of system embodiment 300.
[0071] According to one embodiment of the invention, the ad selection component 322 receives from the prediction component 346 information indicating location, time, and / or other information regarding ad filtering to the user. Based on the received information, the ad selection component 322 searches the ad store 324, for example by querying the relevant index, and is suitable for presenting to the user at a specified and / or predicted time point, location, etc. You can elicit ads. In another embodiment, the ad selection component 322 can also receive information from the sampling component 326 that can be used when selecting an ad. For example, the predictive component 346 can provide a predictive position of the mobile device 310 corresponding to a specified time period, and the sampling component 326 can be a storage space available in cache 315 on the mobile device 310. Can provide information about. Using all of this information, the ad selection component 322 is an ad for presenting to the user of the mobile device 310 in a way that maximizes the probability of user exposure to the ad while minimizing the processing load, network communication, etc. Can be selected.
[0072] The advertising store 324 can be used to store advertisements and information related to advertisements. The advertising store 324 may include one or more advertising databases, such as the advertising database 227 described above with reference to FIG. The ad store can include indexes associated with the ad database, as well as information relevant to the ad, mappings between hyperlinks and content, and other types of content. Depending on the embodiment, the advertisement store 324 may be used to store the script, API, and the like.
[0073] Moving to FIG. 4, a schematic diagram showing an example 400 of the geo-time advertisement narrowing process according to the embodiment of the present invention is shown. FIG. 4 shows a first position 410, a second position 412, a third position 414, and a fourth position 416. FIG. 4 also shows the mobile device 420, as well as the two servers 422 and 424. Process Example 400 is merely an example of a suitable process embodiment and is not intended to suggest any limitation on the scope of use or functionality of the present invention. Also, Process Example 400 shall not be construed as having any dependency or requirement with respect to any one component or combination of components exemplified herein.
[0074] Positions 410, 412, 414, and 416 are possible in any type of position and any suitable embodiment for modeling geo-temporal behavior associated with the mobile device 420. But it can be specified and specified. For example, in one embodiment, positions 410, 421, 414, and 416 can be geographical locations, such as by a set of coordinates including latitude and latitude, towns, cities, counties, states, cities, and so on. It can be specified in many ways. According to one embodiment of the invention, an entity associated with an advertisement can provide data indicating where a particular advertisement should be presented. Since different entities may use different specification schemes to specify their location, the data provided is normalized to allow for more efficient processing through various methods as described herein. A standard input method can be obtained.
[0075] In one embodiment, for example, positions 410, 412, 414, and 416 can be cells in a cellular network. In other embodiments, locations 410, 412, 414, and 416 can be specified by addressing information (eg, IP address) associated with the host computing device or mobile device 420. In other embodiments, positions 410, 412, 414, and 416 can be regions specified by mathematical functions and thus can include other attributes that may be useful in narrowing down the advertisement.
[0076] As shown in FIG. 4, the mobile device 420 is shown at the first position 410. While in the first position, the user can interact with the mobile device 420. In response to detecting user interaction with the mobile device 420, device location information can be collected, for example by server 422. In other embodiments, device location information can be independently monitored by network components and then provided to server 422 or 424. In yet another embodiment, the client on the mobile device 420 can be configured to push location information to servers 422 and 242.
As shown in 428, the mobile device 420 moves from the first position 410 to the second position 412. According to the sample design, the time stamped device position data can be collected again when the mobile device 420 is in the second position 412. As shown in 429, the mobile device 420 moves to a third position. Needless to say, a certain amount of time may pass between the time when the mobile device 420 enters a certain position and the time when the mobile device 420 exits the position. Data related to the length of time a mobile device stays in a certain position can be collected. Similarly, data regarding the duration of user interaction with the mobile device 420 can be collected.
As shown in 430, during a specified time period, while the mobile device 420 is in the third position, the server 422 communicates with the mobile device 420 on the cache associated with the mobile device 420. Determine the amount of memory available. In embodiments, the server 422 can also obtain other types of information, such as whether the user is interacting with the mobile device 420, for example. Based on the information collected, server 422 can select advertisement 426 and propagate that selection to server 424 as shown in 432. Further, as shown in 434, the selected advertisement is provided to the mobile device 420 by the server 424. According to one embodiment, the advertisement 426 can be cached on the mobile device 420, for example, along with instructions, scripts, modules, APIs, etc. that facilitate the presentation of the advertisement 426 at a specified time and position. In addition, the advertisement 426 can be configured to be presented when the specified conditions are met.
[0079] As further shown in FIG. 436, the mobile device 420 moves from the third position 414 to the fourth position 416. Advertisement 426 can be presented to the user while the mobile device 420 is in the fourth position. In some embodiments, components of either or both of the servers 422 and 424 can collect time-stamped location data and use that data to generate a geo-time model of this geo-time model. It can be used to predict the subsequent location and instance of user interaction associated with the mobile device 420.
[0080] To reiterate the point, it is addressed to the user of the mobile device based on the predicted device location by generating a geo-time model using the data collected according to a dynamically updatable sample design. Described the system and method for narrowing down advertising content. Moving to FIG. 5, a flow chart showing an exemplary method of narrowing down the advertising content addressed to the user of the mobile device based on the predicted device position is shown. In the first exemplary step, step 510, reference is made to a dynamically updatable sample design associated with the mobile device. This sample design can be used to identify the sampling time period for collecting device location information associated with the mobile device. In embodiments, referencing a dynamically updatable sample design includes deriving the sample design, receiving input values obtained from the sample design, calculating input values using the sample design, and the like. be able to.
[0081] In the second step 512, an instance of user interaction with a mobile device is detected during the sampling period specified using the sample design. User interaction with the device can include, for example, the user powering the device, the user making a call using the device, the user having the device communicate with the content provider, and the like. In step 514, the location of the device is determined in each instance of the user interaction process with the device. As described above, the location of the device can include designation of geographical area, city, county, state, country, etc. In addition, the location of the device can be specified and specified with respect to the IP address of the computing device to which the mobile device is connected.
[0082] In step 516, time stamped data indicating the device location for each instance of user interaction processing is recorded. This time stamped position data can be stored in a searchable database. In addition, the recorded data can be maintained for a specific amount of time. The system can be configured to assess the usefulness of old data, determine the appropriate time to discard the collected data, and thereby make room for the newly collected data. Can be done. As shown in step 518 of FIG. 5, the time stamped device location data collected is used to update the geo-time model representing the device location and the user interaction process for the time period.
[0083] Continuing with reference to FIG. 5, a first time period is specified, as shown in step 520. In step 522, the device position is predicted for the first time period, and in step 524, the user dialogue processing in the first time period is predicted. These predictions are made by referring to the geo-time model corresponding to the device. In embodiments, the geo-time model can include a model generated by regression analysis or other similar time-continuous prediction techniques. In such cases, the location and user dialogue processing can be predicted by calculating the expected value using the specified first time period as input to the model. In other embodiments, other types of statistical and predictive distributions and models can be used to create geo-time models. In some embodiments, the geo-time model may actually consist of a number of different mathematical and statistical models that can be referenced. In various embodiments, predicting device location and user interaction processing from a geo-time model can include reliability level analysis, as shown in FIG.
[0084] As shown in step 526 of FIG. 5, the exemplary method further predictively delivers the advertisement so that the selected advertisement can be presented to the user in the specified first hour period. Includes selection. In step 528, the selected advertisement is provided to the mobile device. In step 530, it is determined that the sample design should be updated, and in the final exemplary step 532, the sample design is updated. In embodiments of the invention, the sample design can be updated based on various assessments of the efficiency and usefulness of the sample design. According to an embodiment of the present invention, updating the sample design results in changes such as higher frequency of data collection, lower frequency of data collection, data collection at different time points, and the like. Can include.
Moving on to FIG. 6, we show a flow chart of an exemplary method of predicting device location and user interaction processing information using a geo-time model to narrow down advertising content addressed to users of mobile devices. .. An exemplary first step, step 610, specifies a first time period. In step 612, the reliability level of the first set associated with the prediction of the device position in the designated first time period is determined. In step 614, it is determined whether or not any of the reliability levels of the first set exceeds the first predetermined threshold value.
[0086] As shown in FIG. 6, the reliability level of the second set according to the prediction of the user dialogue processing with the device in the specified first time period is determined. This is as shown in step 616. In step 618, it is determined whether or not any of the reliability levels of the second set exceeds the second predetermined threshold value. In the final exemplary step 620, the selected advertising content is provided for presentation to the user during the designated first hour period. In embodiments, advertising content is selected based on which reliability level exceeds each threshold. For example, in one embodiment, some advertisement is based on at least 80% reliability level associated with individual predictions of device location and at least 80% reliability level associated with corresponding predictions of user interaction with the device. You can choose. In another embodiment, some advertising content can be selected based on location prediction and vice versa, regardless of the outcome of the user dialogue processing prediction. These judgments can be made in order to deal with individual business plans, bandwidth management directives, and the like.
[0087] Moving to FIG. 7, a flow chart showing another exemplary method of narrowing down the advertising content addressed to the user of the mobile device based on the predicted device position is shown. In step 710, a set of advertising content is selected based on the predicted device location and user interaction processing in the specified first time period. In step 712, the availability of the mobile device during the second designated time period is detected. Generally, the second designated time period appears before the first designated time period. In step 714, the availability of storage space in the cache on the mobile device is determined. In one embodiment, the mobile device can report this information, and in other embodiments, this information can be extracted or provided by other entities.
[0088] In step 716, a subset of selected advertising content is selected based on the availability of storage space in the cache on the mobile device. In step 718, an executable script is generated. This executable script is configured to facilitate the presentation of a subset of advertising content during the first designated time period. Thus, as shown in step 720, a subset of the advertising content can be supplied to the device along with the script before the first designated time period appears. The executable script can be configured to display advertising content when one or more conditions occur, such as the appearance of a first designated time period and user interaction with the device. In some embodiments, the script may include an API along with a subset of the advertising content. In other embodiments, a tag or other simple instruction or marker that the mobile device can recognize can be included so that the mobile device can determine when to present the advertising content to the user.
[0089] The various components illustrated, and the components not shown, can have many different configurations without departing from the gist and scope of the invention. The embodiments of the present invention have been described with the intention of being exemplary rather than limiting. Alternative embodiments that do not deviate from the scope of the present invention will also be apparent to those skilled in the art. One of ordinary skill in the art will be able to develop alternatives to achieve the above improvements without departing from the scope of the present invention.
[0090] It goes without saying that certain features and sub-combinations are useful and can be used without quoting other features and sub-combinations, which are considered to fall within the scope of the claims. It is not necessary to perform all the steps shown in the various figures in the specific order described.
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Priority claims8
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| TW201015473A | Taiwan Province of China | A | |
| WO2010036525A3 | World Intellectual Property Organization (WIPO) | A3 | |
| EP2329442A2 | European Patent Office (EPO) | A2 | |
| KR20110061580A | Republic of Korea | A | |
| CN102165477A | China | A | |
| US8060406B2 | United States of America | B2 | |
| JP2012503824A | Japan | A | |
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| ZA201100532B | South Africa | B | |
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| RU2011111521A | Russian Federation | A | |
| EP2329442A4 | European Patent Office (EPO) | A4 | |
| AU2009296912B2 | Australia | B2 | |
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| CA2732659C | Canada | C | |
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Numbers
- Publication, DOCDB
- 5543471
- Publication, EPODOC
- JP5543471B
- Application
- 2011529100
- Application, DOCDB
- 2011529100
- Application, EPODOC
- JP20110529100
Titles
- English
- Prediction advertising narrowing down based on geography * time
Classification
- CPC, 4
- G06Q30/02
- G06Q30/0261
- G06Q30/0267
- H04W4/02
- IPC, 1
- G06Q30 02
