WO2014153843A1 - 一种数字电视用户的分类方法、装置及系统 - Google Patents

一种数字电视用户的分类方法、装置及系统 Download PDF

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Publication number
WO2014153843A1
WO2014153843A1 PCT/CN2013/076931 CN2013076931W WO2014153843A1 WO 2014153843 A1 WO2014153843 A1 WO 2014153843A1 CN 2013076931 W CN2013076931 W CN 2013076931W WO 2014153843 A1 WO2014153843 A1 WO 2014153843A1
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Prior art keywords
application
execution time
data packet
application program
classification
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PCT/CN2013/076931
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English (en)
French (fr)
Inventor
李昌盛
景麟
施驰
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深圳创维数字技术股份有限公司
深圳市创维软件有限公司
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Publication of WO2014153843A1 publication Critical patent/WO2014153843A1/zh

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/80Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
    • H04N21/81Monomedia components thereof
    • H04N21/8166Monomedia components thereof involving executable data, e.g. software
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/442Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44204Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched

Definitions

  • the present invention relates to the field of digital television, and in particular, to a method, device and system for classifying digital television users. Background technique
  • Embodiments of the present invention provide a method, an apparatus, and a system for classifying digital television users.
  • the application can be monitored at the system level of the set-top box.
  • the statistical analysis is based on the application usage. It is not necessary to cooperate with the application developer, and only needs to set the factory-set set-top box.
  • the embodiment of the invention provides a classification method for a digital television user, including:
  • the execution time of the listening application gets the execution time information
  • Generating an application execution data packet corresponding to the application where the application execution data package includes: the execution time information; And sending the generated application execution data packet to the front-end server, so that the front-end server performs cluster analysis on the received application execution data packet to obtain a classification of the digital television user.
  • a method for classifying digital television users including:
  • the front-end server performs cluster analysis on the received application execution data packet
  • the classification of the digital television user is obtained.
  • the embodiment of the present invention further provides a classification device for a digital television user, including: a monitoring module, configured to monitor an execution time of an application to obtain execution time information;
  • a generating module configured to generate an application execution data packet corresponding to the application, where the application execution data packet includes: the execution time information;
  • a sending module configured to send the generated application execution data packet to the front-end server, so that the front-end server performs cluster analysis on the received application execution data packet to obtain a classification of the digital television user.
  • a classification device for a digital television user comprising:
  • a receiving module configured to send an application execution data packet by the top box, where the application execution data packet includes at least: execution time information;
  • a clustering analysis module configured to perform cluster analysis on the received application execution data packet; and a user classification obtaining module, configured to obtain a classification of the digital television user according to the cluster analysis result.
  • an embodiment of the present invention further provides a classification system for a digital television user, including: a set top box and a front end server, where:
  • the set top box is configured to listen to an execution time of an application to obtain execution time information, and generate an application execution data packet corresponding to the application, where the application execution data package includes: the execution time information; The generated application execution data packet is sent to the front-end server;
  • the front-end server such as the above device, is configured to execute an application packet sent by the receiver set-top box; perform cluster analysis on the received application execution data packet; and obtain a classification of the digital television user according to the cluster analysis result.
  • the usage of the application program can be monitored in the set top box, and the user will be monitored.
  • the application execution data packet is sent to the front-end server, so that the front-end server can perform cluster analysis on the received application execution data packet to obtain the classification of the digital television user.
  • the invention monitors at the system level of the set-top box, and statistically analyzes the application to use the application. For the unit, there is no need to cooperate with the application developer, and it is only necessary to set the factory-set set-top box accordingly, and the implementation is effective and convenient.
  • FIG. 1 is a schematic structural diagram of a digital television user classification apparatus according to an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of another digital television user classification apparatus according to an embodiment of the present invention
  • FIG. 4 is a flowchart of a method for classifying a digital television user according to an embodiment of the present invention
  • FIG. 5 is an execution time of a method for classifying a digital television user according to an embodiment of the present invention
  • FIG. 6 is a flow chart of another method for classifying digital television users in an embodiment of the present invention. detailed description
  • FIG. 1 is a schematic structural diagram of a classification apparatus for a digital television user according to an embodiment of the present invention.
  • the present invention can be implemented in digital television terminals such as digital television set top boxes, integrated digital television receivers and the like.
  • the classification device of the digital television user in the embodiment of the present invention includes at least: a monitoring module 101, a generating module 102, and a sending module 103, where:
  • the monitoring module 101 is configured to monitor the execution time of the application to obtain execution time information.
  • the monitoring record service program is added in the set top box system program, and when the set top box is turned on, the monitoring record service program is started, for example, on the bottom layer of the Android system set top box, Activity Manager Service Department adds force port Monitor month ⁇ Service, because each Activity (application execution activity) call in the Android system set-top box executes the monitoring record service program, the Monitor service can be added in the Activity Manager Service, record the life cycle of each Activity, you can know each Activity Execution time in the statistical period (such as one day, one week, etc.) (including: foreground execution time, total execution time, etc.), and provides an interface for external calls.
  • the execution time information includes: the total execution time of the application and the foreground execution time of the application.
  • the application A can run in the background and the foreground, and when the background is run, the user can be notified when the push information appears.
  • the user can open the application, application A starts executing in the foreground, and the total execution time can be a superposition of the foreground execution time and the background execution time. If application A is always running in the background, and when running in the foreground, the background runs are never aborted, and the total execution time is equal to the background execution time.
  • the execution time of the listening application gets the execution time information, and the application's foreground execution time can predict the user's actual use of the active number for the application.
  • the monitoring module 101 may include: a total execution time start recording unit, a foreground execution time start recording unit, a foreground execution time stop recording unit, and a total execution time stop recording unit, where:
  • the total execution time start recording unit is configured to start recording the total execution time of the application when the application is detected to be started.
  • the foreground execution time start recording unit is configured to start recording the foreground execution time of the application when detecting that the application is executed in the foreground.
  • the foreground execution time stop recording unit is configured to stop recording the foreground execution time of the application when the application is detected to be executed in the background, and save the foreground execution time of the application obtained by the recording.
  • the total execution time stop recording unit is configured to stop recording the total execution time of the application when the application is detected ends, and save the total execution time of the application obtained by the recording.
  • the generating module 102 is configured to generate an application execution data packet corresponding to the application, where the application execution data packet includes: the execution time information.
  • the application execution data package corresponding to the application is generated, and each application corresponds to one application execution data package, and at least one application execution data package is generated, where the application execution data package may include: execution time information, an application Package name, user ID, execution time information includes: total execution time of the application and the application before Taiwan execution time.
  • the sending module 103 is configured to send the generated application execution data packet to the front-end server, so that the front-end server performs cluster analysis on the received application execution data packet to obtain a classification of the digital television user.
  • the at least one application execution data packet generated by the generation module 102 is sent to the front end server, and the front end server performs cluster analysis on the received at least one application execution data packet to obtain a classification of the digital television user.
  • FIG. 2 is a schematic structural diagram of another type of digital television user classification apparatus according to an embodiment of the present invention.
  • the classification device of the digital television user in the embodiment of the present invention at least includes: a receiving module 201, a cluster analysis module 202, and a user classification obtaining module 203, where:
  • the receiving module 201 is configured to send an application execution data packet, where the application execution data packet includes at least: execution time information.
  • the application execution data packet sent by the front-end server receiver set-top box, where the application execution data package may include: execution time information, an application package name, a user identifier, and execution time information, including: an application execution time and an application.
  • the foreground execution time is an execution time information obtained by monitoring the execution time of the application when the set top box runs the monitoring record service program after adding the monitoring record service program in the set top box system program.
  • the cluster analysis module 202 is configured to perform cluster analysis on the received application execution data packet.
  • the clustering analysis is performed on the received application execution data packet.
  • the clustering analysis module 202 may include: a searching unit and an adding unit, where:
  • a searching unit configured to search, from the preset application category, an application classification that matches the received application execution data packet.
  • an adding unit configured to add, according to the matched application classification, a user corresponding to the application execution data packet to a preset user classification.
  • Cluster analysis refers to statistical analysis techniques that divide subjects into relatively homogeneous groups.
  • the searching unit searches for the application classification that matches the received application execution data packet from the preset application classification, wherein the preset application classification can be divided into multiple levels of directories, for example, the application classification A level, and the application classification level A sub-category Set B, application classification A: Game, education, business, tools, subset of application classification B: Shooting, puzzle, racing, financial in business, Real estate, hotel services, advertising, etc.
  • the application M of the user M executes the data packet N (the application package name is financial, the total execution time is 4h), and the corresponding application classification class A is found as the business class, and the application classification A level subset B is the financial class. .
  • the adding unit adds the user corresponding to the application execution data packet to the preset user classification according to the matched application classification.
  • the clustering result can be calculated by using the Euclidean distance tool to obtain the user classification.
  • the Euclid Distance refers to the true distance between two points in the m-dimensional space
  • the Euclidean distance in the two-dimensional space is the straight line distance between two points, in the digital TV user classification.
  • the application execution data packet corresponds to The user is classified into a class, that is, added to the corresponding preset user category, wherein the preset user category may be the same as the preset application category, or may be customized.
  • the user corresponding to the application execution data packet is added to the preset user classification according to the matched application classification. For example, the application execution packet N of the user M (the application package name is financial, the total execution time is 4h), and the matching pre-finish is found.
  • the application is classified into business class-finance type, and user P's application execution data package Q (application package name is securities, the total execution time is 4h), and the matching preset application is classified as business class-finance type, User M and User P are added to the preset user category: Financial category.
  • the user classification obtaining module 203 is configured to obtain a classification of the digital television user according to the cluster analysis result.
  • the classification of the digital television user is obtained, and the operator can send the service such as the root. Further, after obtaining the cluster analysis result, the operator can take out the data of the typical user and conduct a targeted questionnaire survey, thereby obtaining more accurate user classification information.
  • User classification information allows operators to provide more accurate advertising services, application recommendations, etc., while using The user classification service feeds back to the user for a better user experience.
  • FIG. 3 is a schematic structural diagram of a classification system of a digital television user according to an embodiment of the present invention.
  • the classification system of the digital television user in the embodiment of the present invention includes: a set top box 1 and a front end server. 2, where:
  • the set top box 1 is configured to listen to an execution time of an application to obtain execution time information; generate an application execution data packet corresponding to the application, where the application execution data package includes: the execution time information; The generated application execution data packet is sent to the front-end server;
  • the front-end server 2 is configured to execute a data packet for an application sent by the receiver to the top box; perform cluster analysis on the received application execution data packet; and obtain a classification of the digital television user according to the cluster analysis result.
  • the specific implementation of the classification method of the digital television user provided by the embodiment of the present invention is described below.
  • the classification method includes at least:
  • Step S401 Listening to the execution time of the application to obtain execution time information.
  • the monitoring record service program is added to the set top box system program, and when the set top box is turned on, the monitoring and recording service program shown in the running is started, for example, on the bottom layer of the Android system set top box.
  • Activity Manager Service adds the role of Monitor Month, because each Activity (application execution activity) call in the Android system set-top box executes the monitoring record service program, so the Monitor service can be added in the Activity Manager Service, record each Activity Life cycle, you can know that each activity is in the statistical cycle (for example, one day, Execution time in a week, etc. (including: foreground execution time, total execution time, etc.), and provides an interface for external calls.
  • the execution time information includes: the total execution time of the application and the foreground execution time of the application.
  • the application A can run in the background and the foreground, and when the background is run, the user can be notified when the push information appears.
  • the user can open the application, application A starts executing in the foreground, and the total execution time can be a superposition of the foreground execution time and the background execution time. If application A is always running in the background, and when running in the foreground, the background runs are never aborted, and the total execution time is equal to the background execution time.
  • the execution time of the listening application gets the execution time information, and the application's foreground execution time can predict the user's actual use of the active number for the application.
  • FIG. 5 is a flowchart of execution time monitoring of a digital television user classification method according to an embodiment of the present invention. As shown in FIG. 5, the execution time monitoring process of the digital television user classification method at least includes:
  • step S501 the application is started.
  • Step S502 starting to record the total execution time of the application.
  • Step S503 detecting that the application is executed in the foreground.
  • Step S504 starting to record the foreground execution time of the application.
  • Step S505 detecting that the application is executed in the background.
  • Step S506 stopping recording the foreground execution time of the application.
  • Step S507 saving the foreground execution time of the application obtained by the recording.
  • Step S508 detecting that the application ends.
  • Step S509 stopping recording the total execution time of the application.
  • Step S510 The total execution time of the application obtained by the recording is saved.
  • the execution time information is obtained based on the recorded foreground execution time and total execution time.
  • Step S402 generating an application execution data packet corresponding to the application, where the application execution data packet includes: the execution time information.
  • the application execution data package corresponding to the application is generated, and each application corresponds to one application execution data package, and at least one application execution data package is generated, where the application execution data package may include: execution time information, an application The package name, user ID, and execution time information include: the total execution time of the application and the foreground execution time of the application.
  • Step S403 Send the generated application execution data packet to the front-end server, so that the front-end server performs cluster analysis on the received application execution data packet to obtain a classification of the digital television user.
  • the generated at least one application execution data packet is sent to the front-end server, and the front-end server performs cluster analysis on the received at least one application execution data packet to obtain a classification of the digital television user.
  • the usage of the application program can be monitored in the set top box, and the generated application execution data packet is sent to the front end server, so that the front end server can receive the received
  • the application execution data packet is clustered and analyzed to obtain the classification of the digital television user.
  • the invention is monitored at the system level of the set top box, and the statistical analysis is performed by using the application program. It is not necessary to cooperate with the application developer, and only needs to set the factory set top box correspondingly. Adding a monitoring record service program to the set-top box system program is effective and convenient.
  • 6 is a flow chart of another method for classifying digital television users in an embodiment of the present invention.
  • the present invention can be implemented in, for example, a digital television front-end server. As shown in FIG. 6, the method for classifying a digital television user in the embodiment of the present invention includes at least:
  • Step S601 The application execution data packet sent by the receiver top box, where the application execution data packet includes at least: execution time information.
  • the application execution data packet sent by the front-end server receiver set-top box, where the application execution data package may include: execution time information, an application package name, a user identifier, and execution time information, including: an application execution time and an application.
  • the foreground execution time is an execution time letter obtained by monitoring the execution time of the application when the set top box runs the monitoring record service program after the monitoring record service program is added in the set top box system program, and the execution execution time packet is sent to the received application. Cluster analysis.
  • performing cluster analysis on the received application execution data packet may include: searching and receiving from the preset application classification The applied application performs data packet matching application classification; and the user corresponding to the application execution data packet is added to the preset user classification according to the matched application classification.
  • Cluster analysis refers to statistical analysis techniques that divide subjects into relatively homogeneous groups. Searching for the application classification matching the received application execution data packet from the preset application classification, where the preset application With classification, it can be divided into multi-level catalogs, such as application classification A, application classification A-level subset B, application classification A: game, education, business, tools, application classification subset B : Shooting, puzzle, racing, business, financial, real estate, hotel services, advertising, etc. in the game category.
  • the application M of the user M executes the data packet N (the application package name is financial, the total execution time is 4h), and the corresponding application classification class A is found as the business class, and the application classification A level subset B is the financial class. .
  • the user corresponding to the application execution data packet is added to the preset user classification.
  • the clustering result can be calculated by using the Euclidean distance tool as a tool to obtain the user classification.
  • the Euclidean distance refers to the true distance between two points in the m-dimensional space
  • the Euclidean distance in the two-dimensional space is the straight line segment distance between two points.
  • the digital TV user classification ie different users The distance between the execution time of the application.
  • the user corresponding to the application execution packet is classified into one. The class is added to the corresponding preset user category.
  • the preset user category can be the same as the preset application category, or can be customized.
  • the user corresponding to the application execution data packet is added to the preset user classification according to the matched application classification. For example, the application execution packet N of the user M (the application package name is financial, the total execution time is 4h), and the matching pre-finish is found.
  • the application is classified into business class-financial class, user P's application execution data package Q (application package name is securities, total execution time is 4h), and the matching preset application is classified as business class-finance class, User M and User P are added to the preset user category: Financial category.
  • Step S603 obtaining a classification of the digital television user according to the cluster analysis result.
  • the classification of the digital television user is obtained, and the operator can provide more accurate advertisement service, application recommendation, service push and other services to the specific user according to the user classification.
  • the operator can take out the data of the typical user and conduct a targeted questionnaire survey, thereby obtaining more accurate user classification information.
  • User classification information enables operators to provide more accurate advertising services, application recommendations, etc., while giving back to users in the user classification service for a better user experience.
  • an application executed by a front-end server receiver top box executes a data packet, and performs cluster analysis on the application execution data packet to obtain a classification of the digital television user, and statistical analysis is performed by the application program.
  • the cooperation execution data includes the execution time information obtained by the set top box monitoring application in the application execution data package, and the front end server clusters the application execution data package to obtain the classification of the digital television user, and the implementation manner is effective and convenient.

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Abstract

本发明公开了一种数字电视用户的分类方法、装置及终端,该数字电视用户的分类方法包括:监听应用程序的执行时间得到执行时间信息;生成与所述应用程序对应的应用执行数据包,所述应用执行数据包包括:所述执行时间信息;将所述生成的应用执行数据包发送给前端服务器,以使前端服务器对接收到的应用执行数据包进行聚类分析,得到数字电视用户的分类。采用本发明,可在机顶盒中对应用程序的使用情况进行监听,从而前端服务器可对机顶盒生成的应用执行数据包进行聚类分析得到数字电视用户的分类,该发明在机顶盒系统级进行监听,无需与应用程序开发者合作,只需对应设置出厂的机顶盒,实现方式有效便捷。

Description

一种数字电视用户的分类方法、 装置及系统 本申请要求于 2013 年 03 月 27 日提交中国专利局、 申请号为 201310101197.3 , 发明名称为 "一种数字电视用户的分类方法、 装置及终端" 的中国专利申请的优先权, 其全部内容通过引用结合在本申请中。 技术领域
本发明涉及数字电视领域, 尤其涉及一种数字电视用户的分类方法、装置 及系统。 背景技术
随着电信网络、有线电视网络和计算机网络的融合以及高清数字电视业务 的推广, 数字电视用户不断增加, 不同的用户对数字电视业务的要求不同, 其 中,用户分类使得运营商得以向用户提供更为精确的广告服务、应用程序推荐、 业务推送等服务。
现有技术中,通过对用户进行问卷调查,或在应用程序中记录用户的情况, 对问卷调查结果或记录结果进行统计分析,从而得到用户分类的信息。但是对 用户进行问卷调查的参与度较低且降低了用户的体验,而在应用软件中记录用 户的情况, 需与应用程序的开发者合作, 实现模式较为复杂。 发明内容 本发明实施例在于提供一种数字电视用户的分类方法、 装置及系统。 可 在机顶盒系统级对应用程序的使用情况进行监听,统计分析以应用程序的使用 为单位, 无需与应用程序开发者合作, 只需对应设置出厂的机顶盒。
本发明实施例提供了一种数字电视用户的分类方法, 包括:
监听应用程序的执行时间得到执行时间信息;
生成与所述应用程序对应的应用执行数据包, 所述应用执行数据包包括: 所述执行时间信息; 将所述生成的应用执行数据包发送给前端服务器,以使前端服务器对接收 到的应用执行数据包进行聚类分析, 得到数字电视用户的分类。
一种数字电视用户的分类方法, 包括:
前端服务器接收机顶盒发送的应用执行数据包,所述应用执行数据包至少 包括: 执行时间信息;
前端服务器对所述接收到应用执行数据包进行聚类分析;
根据所述聚类分析结果得到数字电视用户的分类。
相应地, 本发明实施例还提供了一种数字电视用户的分类装置, 包括: 监听模块, 用于监听应用程序的执行时间得到执行时间信息;
生成模块, 用于生成与所述应用程序对应的应用执行数据包, 所述应用执 行数据包包括: 所述执行时间信息;
发送模块, 用于将所述生成的应用执行数据包发送给前端服务器, 以使前 端服务器对接收到的应用执行数据包进行聚类分析, 得到数字电视用户的分 类。
一种数字电视用户的分类装置, 包括:
接收模块, 用于接收机顶盒发送的应用执行数据包, 所述应用执行数据包 至少包括: 执行时间信息;
聚类分析模块, 用于对所述接收到应用执行数据包进行聚类分析; 用户分类获得模块, 用于根据所述聚类分析结果得到数字电视用户的分 类。
相应地, 本发明实施例还提供了一种数字电视用户的分类系统, 包括: 机 顶盒和前端服务器, 其中:
所述机顶盒,如上述的装置, 用于监听应用程序的执行时间得到执行时间 信息; 生成所述应用程序对应的应用执行数据包, 所述应用执行数据包包括: 所述执行时间信息; 将所述生成的应用执行数据包发送给前端服务器;
所述前端服务器,如上述的装置,用于接收机顶盒发送的应用执行数据包; 对所述接收到应用执行数据包进行聚类分析;根据所述聚类分析结果得到数字 电视用户的分类。
实施本发明实施例, 可在机顶盒中对应用程序的使用情况进行监听,将生 成的应用执行数据包发给前端服务器 ,从而前端服务器可对接收到的应用执行 数据包进行聚类分析得到数字电视用户的分类,该发明在机顶盒系统级进行监 听, 统计分析以应用程序的使用为单位, 无需与应用程序开发者合作, 只需对 应设置出厂的机顶盒, 实现方式有效便捷。 附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施 例或现有技术描述中所需要使用的附图作筒单地介绍,显而易见地, 下面描述 中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付 出创造性劳动性的前提下, 还可以根据这些附图获得其他的附图。
图 1是本发明实施例中一种数字电视用户的分类装置的结构示意图; 图 2是本发明实施例中另一种数字电视用户的分类装置的结构示意图; 图 3是本发明实施例中一种数字电视用户的分类系统的结构示意图; 图 4是本发明实施例中一种数字电视用户的分类方法的流程图; 图 5 是本发明实施例中一种数字电视用户的分类方法的执行时间监听流 程图;
图 6是本发明实施例中另一种数字电视用户的分类方法的流程图。 具体实施方式
为了使本发明所要解决的技术问题、 技术方案及有益效果更加清楚明白, 以下结合附图及实施例, 对本发明进行进一步详细说明。
请参阅图 1 , 图 1是本发明实施例中一种数字电视用户的分类装置的结构 示意图。本发明可以实现在如数字电视机顶盒、一体化数字电视接收机等数字 电视终端中。如图 1所示, 本发明实施例中的数字电视用户的分类装置至少包 括: 监听模块 101、 生成模块 102和发送模块 103 , 其中:
监听模块 101 , 用于监听应用程序的执行时间得到执行时间信息。 具体实 现中,监听应用程序的执行时间得到执行时间信息之前,在机顶盒系统程序中 添加监控记录服务程序, 当开启机顶盒时, 启动运行该监控记录服务程序, 例 如, 在 Android系统机顶盒底层, Activity Manager Service处添力口 Monitor月^ 务, 由于 Android系统机顶盒中每个 Activity (应用程序执行活动)调用都执 行该监控记录服务程序,因此 Monitor服务可以添加在 Activity Manager Service 处, 记录每个 Activity的生命周期, 可以得知每个 Activity在统计周期(例如 一天、 一周等)里的执行时间 (包括: 前台执行时间、 总执行时间等), 且提 供接口供外部调用。
其中,执行时间信息包括: 应用程序的总执行时间和应用程序的前台执行 时间, 例如, 应用程序 A可在后台与前台运行, 当在后台运行时, 出现推送 的信息时可通知用户, 此时用户可打开应用程序, 应用程序 A开始在前台执 行, 总执行时间可以为前台执行时间与后台执行时间的叠加。如果应用程序 A 一直在后台运行, 且当在前台执行时, 后台运行从未中止, 则总执行时间与后 台执行时间相等。监听应用程序的执行时间得到执行时间信息,通过应用程序 的前台执行时间可以预知用户对应用程序真正使用活跃数。
进一步可选的, 监听模块 101可以包括: 总执行时间开始记录单元、 前台 执行时间开始记录单元、前台执行时间停止记录单元和总执行时间停止记录单 元, 其中:
总执行时间开始记录单元, 用于当检测到所述应用程序启动时, 开始记录 所述应用程序的总执行时间。
前台执行时间开始记录单元, 用于当检测到所述应用程序在前台执行时, 开始记录所述应用程序的前台执行时间。
前台执行时间停止记录单元, 用于当检测到所述应用程序在后台执行时, 停止记录所述应用程序的前台执行时间,并保存所述记录得到的应用程序的前 台执行时间。
总执行时间停止记录单元, 用于当检测到所述应用程序结束时,停止记录 所述应用程序的总执行时间, 并保存所述记录得到的应用程序的总执行时间。
生成模块 102, 用于生成与所述应用程序对应的应用执行数据包, 所述应 用执行数据包包括: 所述执行时间信息。 具体实现中, 生成与应用程序对应的 应用执行数据包,每个应用程序对应一个应用执行数据包, 则生成至少一个应 用执行数据包, 其中, 应用执行数据包可以包括: 执行时间信息、 应用程序包 名称、 用户标识, 执行时间信息包括: 应用程序的总执行时间和应用程序的前 台执行时间。
发送模块 103 , 用于将所述生成的应用执行数据包发送给前端服务器, 以 使前端服务器对接收到的应用执行数据包进行聚类分析,得到数字电视用户的 分类。具体实现中,将生成模块 102生成的至少一个应用执行数据包发送给前 端服务器, 前端服务器对接收到的至少一个应用执行数据包进行聚类分析,得 到数字电视用户的分类。
通过实施本发明实施例提供的一种数字电视用户的分类装置,可在机顶盒 中对应用程序的使用情况进行监听, 将生成的应用执行数据包发给前端服务 器,从而前端服务器可对接收到的应用执行数据包进行聚类分析得到数字电视 用户的分类, 该发明在机顶盒系统级进行监听, 统计分析以应用程序的使用为 单位, 无需与应用程序开发者合作, 只需对应设置出厂的机顶盒, 在机顶盒系 统程序中添加监控记录服务程序, 实现方式有效便捷。 图 2是本发明实施例中另一种数字电视用户的分类装置的结构示意图。本 发明可以实现在如数字电视机前端服务器中。如图 2所示, 本发明实施例中的 数字电视用户的分类装置至少包括: 接收模块 201、 聚类分析模块 202和用户 分类获得模块 203 , 其中:
接收模块 201 , 用于接收机顶盒发送的应用执行数据包, 所述应用执行数 据包至少包括: 执行时间信息。 具体实现中, 前端服务器接收机顶盒发送的应 用执行数据包, 其中, 应用执行数据包可以包括: 执行时间信息、 应用程序包 名称、 用户标识, 执行时间信息包括: 应用程序的总执行时间和应用程序的前 台执行时间。 执行时间信息为在机顶盒系统程序中添加监控记录服务程序后, 开启机顶盒运行该监控记录服务程序时,监听应用程序的执行时间得到的执行 时间信息。
聚类分析模块 202, 用于对所述接收到应用执行数据包进行聚类分析。 具 体实现中, 对接收到的应用执行数据包进行聚类分析, 进一步可选的, 聚类分 析模块 202可以包括: 查找单元和添加单元, 其中:
查找单元,用于从预设的应用分类中查找与所述接收到的应用执行数据包 匹配的应用分类。 添加单元,用于根据所述匹配的应用分类将所述应用执行数据包对应的用 户添加到预设的用户分类中。
聚类分析是指将研究对象分为相对同质的群组的统计分析技术。查找单元 从预设的应用分类中查找与接收到的应用执行数据包匹配的应用分类, 其中, 预设的应用分类, 可以分为多级目录, 例如应用分类 A级, 应用分类 A级的 子集 B级, 应用分类 A级: 游戏类、 教育类、 商务类、 工具类, 应用分类的 子集 B 级: 游戏类中的射击类、 益智类、 赛车类, 商务类中的金融类、 房地 产类、 酒店服务类、 广告类等。 例如, 用户 M的应用执行数据包 N (应用包 名为财经, 总执行时间为 4h ), 查找到对应预设的应用分类 A级为商务类, 应 用分类 A级的子集 B级为金融类。
添加单元根据匹配的应用分类将应用执行数据包对应的用户添加到预设 的用户分类中, 具体的, 可以以欧氏距离为工具计算出聚类的结果, 得到用户 的分类。 其中, 欧氏距离 (Euclid Distance )是指在 m维空间中两个点之间的 真实距离,在二维空间中的欧氏距离就是两点之间的直线段距离,在数字电视 用户分类中, 即不同用户的应用程序的执行时间之间的距离, 当对于在同一类 应用分类中的应用执行数据包,其前台执行时间或者总执行时间相近或者相同 时,将该应用执行数据包对应的用户归为一类, 即添加到对应的预设的用户分 类中, 其中, 预设的用户分类可与预设的应用分类相同, 也可以自定义。 根据 匹配的应用分类将应用执行数据包对应的用户添加到预设的用户分类中, 例 如, 用户 M的应用执行数据包 N (应用包名为财经, 总执行时间为 4h ), 查找 到匹配预设的应用分类为商务类-金融类, 用户 P的应用执行数据包 Q (应用 包名为证券,总执行时间为 4h ),查找匹配的预设的应用分类为商务类-金融类, 则将用户 M与用户 P添加到预设的用户分类: 金融类。
用户分类获得模块 203 , 用于根据所述聚类分析结果得到数字电视用户的 分类。 具体实现中, 根据聚类分析结果得到数字电视用户的分类, 运营商可根 送等服务。 进一步可选的, 运营商在拿到聚类分析结果后, 可以拿出典型用户 的数据, 进行针对性的问卷调查, 进而可以得到更精确的用户分类信息。 用户 分类信息可以使得运营商提供更精确的广告服务,应用程序推荐等, 同时在用 户分类服务中反馈给用户, 以得到更好的用户体验。
通过实施本发明实施例提供的一种数字电视用户的分类装置,前端服务器 接收机顶盒发送的应用执行数据包,并对应用执行数据包进行聚类分析得到数 字电视用户的分类, 统计分析以应用程序的使用为单位, 无需与应用程序开发 者合作,应用执行数据包中包括机顶盒监听应用程序得到的执行时间信息, 前 端服务器对应用执行数据包进行聚类分析则可得到数字电视用户的分类,实现 方式有效便捷。 请参阅图 3 , 图 3为是本发明实施例中一种数字电视用户的分类系统的结 构示意图, 如图所示, 本发明实施例中的数字电视用户的分类系统包括: 机顶 盒 1和前端服务器 2, 其中:
机顶盒 1 , 如上述的装置, 用于监听应用程序的执行时间得到执行时间信 息; 生成所述应用程序对应的应用执行数据包, 所述应用执行数据包包括: 所 述执行时间信息; 将所述生成的应用执行数据包发送给前端服务器;
前端服务器 2, 如上述的装置, 用于接收机顶盒发送的应用执行数据包; 对所述接收到应用执行数据包进行聚类分析;根据所述聚类分析结果得到数字 电视用户的分类。 下面阐述本发明实施例提供的数字电视用户的分类方法的具体实现。
图 4是本发明实施例中一种数字电视用户的分类方法的流程图,本发明可 以实现在如数字电视机顶盒、一体化数字电视接收机等数字电视终端中,如图 所示数字电视用户的分类方法至少包括:
步骤 S401 , 监听应用程序的执行时间得到执行时间信息。 具体实现中, 在监听应用程序的执行时间得到执行时间信息之前,在机顶盒系统程序中添加 监控记录服务程序, 当开启机顶盒时,启动运行所示监控记录服务程序,例如, 在 Android系统机顶盒底层, Activity Manager Service处添力口 Monitor月良务, 由于 Android系统机顶盒中每个 Activity (应用程序执行活动)调用都执行该 监控记录服务程序,因此 Monitor服务可以添加在 Activity Manager Service处, 记录每个 Activity的生命周期,可以得知每个 Activity在统计周期(例如一天、 一周等)里的执行时间 (包括: 前台执行时间、 总执行时间等), 且提供接口 供外部调用。
其中,执行时间信息包括: 应用程序的总执行时间和应用程序的前台执行 时间, 例如, 应用程序 A可在后台与前台运行, 当在后台运行时, 出现推送 的信息时可通知用户, 此时用户可打开应用程序, 应用程序 A开始在前台执 行, 总执行时间可以为前台执行时间与后台执行时间的叠加。如果应用程序 A 一直在后台运行, 且当在前台执行时, 后台运行从未中止, 则总执行时间与后 台执行时间相等。监听应用程序的执行时间得到执行时间信息,通过应用程序 的前台执行时间可以预知用户对应用程序真正使用活跃数。
进一步可选的,图 5是本发明实施例中一种数字电视用户的分类方法的执 行时间监听流程图,如图 5所示,数字电视用户的分类方法的执行时间监听流 程至少包括:
步骤 S501 , 启动应用程序。
步骤 S502, 开始记录所述应用程序的总执行时间。
步骤 S503 , 检测到所述应用程序在前台执行。
步骤 S504, 开始记录所述应用程序的前台执行时间。
步骤 S505 , 检测到所述应用程序在后台执行。
步骤 S506, 停止记录所述应用程序的前台执行时间。
步骤 S507, 保存所述记录得到的应用程序的前台执行时间。
步骤 S508, 检测到所述应用程序结束。
步骤 S509, 停止记录所述应用程序的总执行时间。
步骤 S510, 保存所述记录得到的应用程序的总执行时间。
根据记录的前台执行时间和总执行时间得到执行时间信息。
步骤 S402, 生成与所述应用程序对应的应用执行数据包, 所述应用执行 数据包包括: 所述执行时间信息。 具体实现中, 生成与应用程序对应的应用执 行数据包,每个应用程序对应一个应用执行数据包, 则生成至少一个应用执行 数据包, 其中, 应用执行数据包可以包括: 执行时间信息、 应用程序包名称、 用户标识,执行时间信息包括: 应用程序的总执行时间和应用程序的前台执行 时间。 步骤 S403 , 将所述生成的应用执行数据包发送给前端服务器, 以使前端 服务器对接收到的应用执行数据包进行聚类分析, 得到数字电视用户的分类。 具体实现中,将生成的至少一个应用执行数据包发送给前端服务器, 前端服务 器对接收到的至少一个应用执行数据包进行聚类分析,得到数字电视用户的分 类。
通过实施本发明实施例提供的一种数字电视用户的分类方法,可在机顶盒 中对应用程序的使用情况进行监听, 将生成的应用执行数据包发给前端服务 器,从而前端服务器可对接收到的应用执行数据包进行聚类分析得到数字电视 用户的分类, 该发明在机顶盒系统级进行监听, 统计分析以应用程序的使用为 单位, 无需与应用程序开发者合作, 只需对应设置出厂的机顶盒, 在机顶盒系 统程序中添加监控记录服务程序, 实现方式有效便捷。 图 6是本发明实施例中另一种数字电视用户的分类方法的流程图。本发明 可以实现在如数字电视机前端服务器中。如图 6所示, 本发明实施例中的数字 电视用户的分类方法至少包括:
步骤 S601 , 接收机顶盒发送的应用执行数据包, 所述应用执行数据包至 少包括: 执行时间信息。 具体实现中, 前端服务器接收机顶盒发送的应用执行 数据包, 其中, 应用执行数据包可以包括: 执行时间信息、 应用程序包名称、 用户标识,执行时间信息包括: 应用程序的总执行时间和应用程序的前台执行 时间。执行时间信息为在机顶盒系统程序中添加监控记录服务程序后, 开启机 顶盒运行该监控记录服务程序时,监听应用程序的执行时间得到的执行时间信 步骤 S602, 对所述接收到应用执行数据包进行聚类分析。 具体实现中, 对接收到的应用执行数据包进行聚类分析, 进一步可选的,对所述接收到应用 执行数据包进行聚类分析可以包括:从预设的应用分类中查找与所述接收到的 应用执行数据包匹配的应用分类;根据所述匹配的应用分类将所述应用执行数 据包对应的用户添加到预设的用户分类中。
聚类分析是指将研究对象分为相对同质的群组的统计分析技术。从预设的 应用分类中查找与接收到的应用执行数据包匹配的应用分类, 其中,预设的应 用分类, 可以分为多级目录, 例如应用分类 A级, 应用分类 A级的子集 B级, 应用分类 A级: 游戏类、 教育类、 商务类、 工具类, 应用分类的子集 B级: 游戏类中的射击类、 益智类、 赛车类, 商务类中的金融类、 房地产类、 酒店服 务类、 广告类等。 例如, 用户 M的应用执行数据包 N (应用包名为财经, 总 执行时间为 4h ), 查找到对应预设的应用分类 A级为商务类, 应用分类 A级 的子集 B级为金融类。
根据匹配的应用分类将应用执行数据包对应的用户添加到预设的用户分 类中, 具体的, 可以以欧氏距离为工具计算出聚类的结果, 得到用户的分类。 其中, 欧氏距离是指在 m维空间中两个点之间的真实距离, 在二维空间中的 欧氏距离就是两点之间的直线段距离,在数字电视用户分类中, 即不同用户的 应用程序的执行时间之间的距离,当对于在同一类应用分类中的应用执行数据 包, 其前台执行时间或者总执行时间相近或者相同时,将该应用执行数据包对 应的用户归为一类, 即添加到对应的预设的用户分类中, 其中, 预设的用户分 类可与预设的应用分类相同,也可以自定义。根据匹配的应用分类将应用执行 数据包对应的用户添加到预设的用户分类中, 例如, 用户 M的应用执行数据 包 N (应用包名为财经, 总执行时间为 4h ), 查找到匹配预设的应用分类为商 务类-金融类, 用户 P的应用执行数据包 Q (应用包名为证券, 总执行时间为 4h ), 查找匹配的预设的应用分类为商务类-金融类, 则将用户 M与用户 P添 加到预设的用户分类: 金融类。
步骤 S603, 根据所述聚类分析结果得到数字电视用户的分类。 具体实现 中,根据聚类分析结果得到数字电视用户的分类,运营商可根据该用户分类向 具体的用户提供更为精确的广告服务、 应用程序推荐、 业务推送等服务。 进一 步可选的, 运营商在拿到聚类分析结果后, 可以拿出典型用户的数据, 进行针 对性的问卷调查, 进而可以得到更精确的用户分类信息。用户分类信息可以使 得运营商提供更精确的广告服务,应用程序推荐等, 同时在用户分类服务中反 馈给用户, 以得到更好的用户体验。
通过实施本发明实施例提供的一种数字电视用户的分类方法,前端服务器 接收机顶盒发送的应用执行数据包,并对应用执行数据包进行聚类分析得到数 字电视用户的分类, 统计分析以应用程序的使用为单位, 无需与应用程序开发 者合作,应用执行数据包中包括机顶盒监听应用程序得到的执行时间信息, 前 端服务器对应用执行数据包进行聚类分析则可得到数字电视用户的分类,实现 方式有效便捷。
需要说明的是,通过以上的实施方式的描述, 本领域的技术人员可以清楚 地了解到本发明可借助软件加必需的硬件平台的方式来实现,当然也可以全部 通过硬件来实施。基于这样的理解, 本发明的技术方案对背景技术做出贡献的 全部或者部分可以以软件产品的形式体现出来,该计算机软件产品可以存储在 存储介质中, 如 ROM/RAM、 磁碟、 光盘等, 包括若干指令用以使得一台计算 机设备(可以是个人计算机, 服务器, 或者网络设备等)执行本发明各个实施 例或者实施例的某些部分所述的方法。
以上所揭露的仅为本发明实施例中的较佳实施例而已,当然不能以此来限 定本发明之权利范围, 因此依本发明权利要求所作的等同变化,仍属本发明所 涵盖的范围。

Claims

权 利 要 求
1、 一种数字电视用户的分类方法, 其特征在于, 所述方法包括: 监听应用程序的执行时间得到执行时间信息;
生成与所述应用程序对应的应用执行数据包, 所述应用执行数据包包括: 所述执行时间信息;
将所述生成的应用执行数据包发送给前端服务器,以使前端服务器对接收 到的应用执行数据包进行聚类分析, 得到数字电视用户的分类。
2、 根据权利要求 1所述的方法, 其特征在于, 所述执行时间信息包括: 应用程序的总执行时间;
所述监听应用程序的执行时间得到执行时间信息包括:
当检测到所述应用程序启动时, 开始记录所述应用程序的总执行时间; 当检测到所述应用程序结束时,停止记录所述应用程序的总执行时间, 并 保存所述记录得到的应用程序的总执行时间。
3、 根据权利要求 2所述的方法, 其特征在于, 所述执行时间信息还包括: 应用程序的前台执行时间;
所述开始记录所述应用程序的总执行时间之后包括:
当检测到所述应用程序在前台执行时,开始记录所述应用程序的前台执行 时间;
当检测到所述应用程序在后台执行时,停止记录所述应用程序的前台执行 时间, 并保存所述记录得到的应用程序的前台执行时间。
4、 一种数字电视用户的分类方法, 其特征在于, 所述方法包括: 前端服务器接收机顶盒发送的应用执行数据包,所述应用执行数据包至少 包括: 执行时间信息;
前端服务器对所述接收到应用执行数据包进行聚类分析;
根据所述聚类分析结果得到数字电视用户的分类。
5、 根据权利要求 4所述的方法, 其特征在于, 所述前端服务器对所述接 收到应用执行数据包进行聚类分析包括:
从预设的应用分类中查找与所述接收到的应用执行数据包匹配的应用分 类;
根据所述匹配的应用分类将所述应用执行数据包对应的用户添加到预设 的用户分类中。
6、 一种数字电视用户的分类装置, 其特征在于, 所述装置包括: 监听模块, 用于监听应用程序的执行时间得到执行时间信息;
生成模块, 用于生成与所述应用程序对应的应用执行数据包, 所述应用执 行数据包包括: 所述执行时间信息;
发送模块, 用于将所述生成的应用执行数据包发送给前端服务器, 以使前 端服务器对接收到的应用执行数据包进行聚类分析, 得到数字电视用户的分 类。
7、 根据权利要求 6所述的装置, 其特征在于, 所述执行时间信息包括: 应用程序的总执行时间;
所述监听模块包括:
总执行时间开始记录单元, 用于当检测到所述应用程序启动时, 开始记录 所述应用程序的总执行时间;
总执行时间停止记录单元, 用于当检测到所述应用程序结束时,停止记录 所述应用程序的总执行时间, 并保存所述记录得到的应用程序的总执行时间。
8、 根据权利要求 7所述的装置, 其特征在于, 所述执行时间信息还包括: 应用程序的前台执行时间;
所述监听模块还包括:
前台执行时间开始记录单元, 用于当检测到所述应用程序在前台执行时, 开始记录所述应用程序的前台执行时间; 前台执行时间停止记录单元, 用于当检测到所述应用程序在后台执行时, 停止记录所述应用程序的前台执行时间,并保存所述记录得到的应用程序的前 台执行时间。
9、 一种数字电视用户的分类装置, 其特征在于, 所述装置包括: 接收模块, 用于接收机顶盒发送的应用执行数据包, 所述应用执行数据包 至少包括: 执行时间信息;
聚类分析模块, 用于对所述接收到应用执行数据包进行聚类分析; 用户分类获得模块, 用于根据所述聚类分析结果得到数字电视用户的分 类。
10、 根据权利要求 9所述的装置, 其特征在于, 所述聚类分析模块包括: 查找单元,用于从预设的应用分类中查找与所述接收到的应用执行数据包 匹配的应用分类;
添加单元,用于根据所述匹配的应用分类将所述应用执行数据包对应的用 户添加到预设的用户分类中。
11、 一种数字电视用户的分类系统, 其特征在于, 包括: 机顶盒和前端服 务器, 其中:
所述机顶盒,如权利要求 6~8任一所述的装置,用于监听应用程序的执行 时间得到执行时间信息; 生成所述应用程序对应的应用执行数据包, 所述应用 执行数据包包括: 所述执行时间信息; 将所述生成的应用执行数据包发送给前 端服务器;
所述前端服务器, 如权利要求 9~10任一所述的装置, 用于接收机顶盒发 送的应用执行数据包; 对所述接收到应用执行数据包进行聚类分析;根据所述 聚类分析结果得到数字电视用户的分类。
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