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A multi-user sharing-oriented multimedia network video recommendation method

A network video and recommendation method technology, which is applied in the field of big data multimedia network video applications, can solve problems such as user resentment and recommendation system accuracy reduction, so as to improve utilization, realize incremental update, and increase computing speed and computing resources. The effect of utilization

Pending Publication Date: 2021-10-01
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

However, random or excessive exploration may lead to a decrease in the accuracy of the recommendation system, and the randomly recommended content may also arouse user disgust

Method used

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  • A multi-user sharing-oriented multimedia network video recommendation method
  • A multi-user sharing-oriented multimedia network video recommendation method
  • A multi-user sharing-oriented multimedia network video recommendation method

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Embodiment Construction

[0089] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0090] In this embodiment, the data set comes from the data of a certain operator's IPTV set-top box. Among them, 1100 user data were selected from the IPTV video system for a period of three months to watch records, which involved a total of 498,309 log records and 2830 programs.

[0091] like figure 1 As shown, the present invention provides a kind of multimedia network video recommending method facing multi-user sharing, and the method comprises the following steps:

[0092] Step 1: Collect the multi-user mixed behavior log record data of multi-user watching online video, and process the multi-user mixed behavior log record data, including data cleaning, data integration and data resampling.

[0093] (1-1) IPTV set-top boxes are used to collect multi-user mixed behavior log record data of multi-user watching online video at an...

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Abstract

The invention discloses a multi-user sharing-oriented multimedia network video recommendation method, which comprises the following steps: firstly, constructing multi-user characteristics by utilizing collected program information in a multi-user sharing environment, and constructing a leading user label according to the similarity of the program characteristics and the continuity of user watching behaviors, so that separation of multi-user mixed logs is realized; performing periodic multi-user identification prediction of future sessions; secondly, building a user interest mining model based on a time-varying LinUCB algorithm to learn interest changes of a user for each program theme, and enhancing the personalized ability and efficiency of a recommendation system from three aspects of parallel calculation, adaptive control of an exploration coefficient and incremental updating based on LSTM; and finally, establishing an article quality model based on a non-time-varying LinUCB algorithm to further ensure the program quality, and integrating the two algorithms into a final recommendation system model by adopting a cross weighting strategy to form a final program recommendation list. The novelty and accuracy of the recommendation result are ensured.

Description

technical field [0001] The invention relates to the technical field of big data multimedia network video applications, in particular to a multi-user-oriented multimedia network video recommendation method. Background technique [0002] With the advent of the digital age, smart devices such as smartphones and tablet computers, and the vigorous development of Internet multimedia video technology, the number of online videos has achieved explosive growth. From the traditional cable TV to the leap-forward development of Internet Protocol Television (IPTV), the Internet TV industry has ushered in tremendous development and changes. On the one hand, the scale of IPTV users has achieved rapid growth. In 2014, the total number of users was only about 30 million, in 2017 it exceeded 121 million, and in 2018 it reached 151 million. On the other hand, the number of online videos is increasing rapidly, and the contents are flourishing. According to statistics from the online program ...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/735G06F16/783
CPCG06F16/9535G06F16/783G06F16/735Y02D10/00
Inventor 魏昕孙诗云胡正莹周亮
Owner NANJING UNIV OF POSTS & TELECOMM
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