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Video clustering recommendation method and apparatus

A recommendation method and video technology, applied in the field of video clustering, can solve the problems of low quality of clustering results, easy to be affected by outliers, low computational efficiency, etc.

Active Publication Date: 2016-03-09
TCL CORPORATION
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a video clustering recommendation method to solve the problem that the existing segmentation clustering algorithm requires multiple iterative operations, the calculation efficiency is relatively low, and it is easily affected by outliers, resulting in poor quality of clustering results. high problem

Method used

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  • Video clustering recommendation method and apparatus
  • Video clustering recommendation method and apparatus

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] figure 1 The implementation flow of the video clustering recommendation method provided by the first embodiment of the present invention is shown, and the details are as follows:

[0052] In step S101, according to the number of ratings of all users on the video, the videos are sorted to obtain the video set n is the number of videos.

[0053] Specifically, all the users mentioned in the embodiments of the present invention may be the video ratings of all users of the platform obtained through a data collection platform such as Internet TV, or may be comprehensive data obtained by multiple data collection platforms.

[0054] The number of ratings of the video refers to the number of ratings for a certain video, and the more the number of ratings, the higher the popularity of the video. As an optional implementation, the number of ratings may be the number of users who have rated the video, that is, for the same user, when the same video has been rated multiple times,...

Embodiment 2

[0080] figure 2 The implementation flow of the video clustering recommendation method provided by the second embodiment of the present invention is shown, and the details are as follows:

[0081] In step S201, according to the method described in the first embodiment, the videos are clustered to generate video collection classes.

[0082] In step S202, the target video input by the user is received, and the video collection class to which the target video belongs is searched.

[0083] Specifically, the target video input by the user in the embodiment of the present invention may be the video that the user is searching for, or the video that the user is currently watching. In addition, in order to improve the accuracy of video recommendation, it is also possible to set the The duration exceeds a certain length of time, such as watching a video for more than five minutes.

[0084] The video collection class to which the target video belongs can be calculated by calculating th...

Embodiment 3

[0098] image 3 A schematic structural diagram of a video clustering recommendation device provided by the third embodiment of the present invention is shown, and the details are as follows:

[0099] The video clustering and recommending device described in the embodiment of the present invention includes:

[0100] The sorting unit 301 is used to sort the videos according to the number of ratings of the videos by all users to obtain the video set n is the number of videos;

[0101] The degree of difference calculation unit 302 is used to calculate the scores of each video in turn from high to low according to the number of ratings of the videos Compared with the number of ratings Higher videos, or by the number of ratings Higher videos form a video set class, and the set difference degree is calculated;

[0102] The video collection class generation unit 303 is used to obtain the calculated minimum value of the collection difference degree, and if the minimum value of...

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Abstract

The invention provides a video clustering recommendation method. The method comprises: according to scoring numbers on videos by all users, sorting is carried out the video to obtain a video set N (C1<0>, C2<0>,C3<0>, ... Cn<0>), wherein the n expresses the number of videos; on the basis of the scoring numbers of the videos, set difference calculation is carried out on each video Ci<0> and one video Ci<0> with the high scoring number successively in a descending order; and a calculated minimum set different value is obtained; if the minimum set different value is less than a preset threshold value, the video Ci<0> with the high scoring number corresponding to the minimum set different value and the video Ci<0> are combined into a video set class. According to the invention, multi-times iterative operation during clustering can be avoided; the influence by an abnormal value cab be avoided; and the classification efficiency and the clustering quality are substantially improved.

Description

technical field [0001] The invention belongs to the field of video clustering, and in particular relates to a video clustering recommendation method and device. Background technique [0002] With the continuous enrichment of Internet resources, when people view multimedia resources, such as watching videos or playing music files, they need to search for files in a large number of multimedia resources, and it takes a lot of time to obtain the multimedia data that users like. [0003] In order to improve users’ access to favorite multimedia files, such as video data, the existing video recommendation methods are generally based on clustering technology and collaborative filtering recommendation algorithm. Through clustering technology, the scope of searching the nearest neighbors of the target object is narrowed to the target object. Several clusters with the highest degree of similarity can effectively reduce the amount of calculation and improve real-time response capability...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/30
CPCG06F16/783G06F18/23213
Inventor 冯研
Owner TCL CORPORATION
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