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User behavior analysis method, analysis and prediction method and TV program push system

A behavior analysis and prediction system technology, applied in electrical components, electrical digital data processing, selective content distribution, etc., can solve problems such as poor user behavior description accuracy, lost behavior timing and periodicity, and inaccurate user behavior analysis. To achieve the effect of convenient collaborative analysis

Inactive Publication Date: 2016-06-22
TCL CORPORATION
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Problems solved by technology

[0004] The purpose of the present invention is to provide a user behavior analysis method, analysis and prediction method and TV program push system to solve the inaccurate analysis of user behavior in the prior art, the loss of behavior timing and periodic characteristics, resulting in accurate description of user behavior poor sex problem

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  • User behavior analysis method, analysis and prediction method and TV program push system
  • User behavior analysis method, analysis and prediction method and TV program push system
  • User behavior analysis method, analysis and prediction method and TV program push system

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Embodiment Construction

[0061] In order to make the object, technical solution and effect of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0062] see figure 1 , which is a flowchart of an embodiment of the user behavior analysis method of the present invention, as shown in the figure, the method includes the following steps:

[0063] S1. According to the historical user behavior data, extract the user behavior pattern structure data and store it in the user behavior pattern database;

[0064] S2. Perform the first clustering of the user behavior pattern structural data stored in the user behavior pattern database according to the characteristics of the behavior type, and generate similar clustered user data sets according to the type;

[0065] S3. Perform a second clustering according to changing structural features on the user data clustered according to similar types, and ge...

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Abstract

The invention discloses a user behavior analysis method, a user behavior analytical prediction method and a television program push system. The user behavior analysis method comprises firstly analyzing data of historical user behavior, extracting structured data of user behavior patterns and storing the structured data in a database of user behavior patterns; secondly, leading the structured data of the user behavior patterns to be subjected to a first clustering according to behavior type features and generating a user data set of similar clustering by types; thirdly, leading the user data of similar clustering by types to be subjected to a second clustering according to change structure features and generating a cluster data set of users with similar behavior changes; finally, outputting cluster result data of the users. Due to the fact that time-order characters of the changes of user behavior are taken into consideration in the second clustering, so that the cluster data set of the users contains change information of the user behavior which pure statistical data does not contain, and description of users can be more complete; the cluster result set obtained finally can be conveniently applied to collaborative analysis among users and to promotion field of television programs for pushing potential interested programs for users.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a user behavior analysis method, an analysis and prediction method and a TV program push system. Background technique [0002] At present, most algorithms use statistical data for preliminary data processing. Such data processing of user behavior data will lose behavior timing and periodic characteristics. It is precisely because of the loss of these data characteristics that the accuracy of user descriptions will be unsatisfactory. . Moreover, the behavior of the same user is too unpredictable. It is difficult to completely predict the next behavior of the user if only the statistical data of the user is analyzed. , I went to watch B-type programs due to unknown reasons, but you can’t find the behavior change information hidden in the user’s viewing history according to the statistical description, so you won’t recommend B-type programs, so you can’t provide users with huma...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30H04N21/258H04N21/462
Inventor 董延平汪灏泓
Owner TCL CORPORATION
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