Micro-video personalized recommendation algorithm based on social network credibility

A social network and recommendation algorithm technology, applied in computing, special data processing applications, instruments, etc., to reduce the impact and achieve the effect of high-quality recommended content

Pending Publication Date: 2018-11-30
HARBIN ENG UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, little research has been done so far on the recommendation of bit-sized videos
Secondly, in social media, there are also challenges in the personalized recommendation of high-quality UGC. Although some candidate items are easily recognized (s

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  • Micro-video personalized recommendation algorithm based on social network credibility
  • Micro-video personalized recommendation algorithm based on social network credibility
  • Micro-video personalized recommendation algorithm based on social network credibility

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Embodiment Construction

[0025] Below in conjunction with accompanying drawing, a kind of micro-video personalized recommendation algorithm based on social network trust degree provided by the present invention is further explained:

[0026] The present invention is realized through the following steps:

[0027] Step 1: Use the difference between global trust and local trust to calculate user deviation. On this basis, transfer and aggregate deviation-based trust and distrust relationships, and connect hidden relationships between users;

[0028] Step 2: Improve the traditional similarity calculation method and add confidence factors;

[0029] Step 3: Because the user's interests are constantly updated over time, the trust network evolves dynamically by taking advantage of the dependence of trust on time;

[0030] Step 4: Create a dual network time-domain evolution model composed of user similarity network and trust network to reduce the sparsity of trust network. In the proposed model, the predicte...

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Abstract

The invention provides a micro-video personalized recommendation algorithm based on social network credibility and belongs to the field of computer algorithms. The micro-video personalized recommendation algorithm includes the steps of firstly, calculating user deviation degree according to the difference of global credibility and local trust; secondly, adding a confidence degree factor into a traditional similarity calculation method; thirdly, using the dependence of trust on time to allow a trust network to dynamically evolve; fourthly, creating a dual network time domain evolution model (DNTDEM) comprising a user similarity network and a user trust network; fifthly, acquiring a brand new user trust network according to the DNTDEM; sixthly, using an LDA model to supplement recommendationcontent; seventhly, allowing predicted users to be similar to the emotion neighbors of the users, and using a minimum error square value to optimize the similarity. The micro-video personalized recommendation algorithm has the advantages that high-quality new-form user-generated content (UGC) can be effectively identified and recommended to appropriate users; influence of the subjective prejudices of other users on the recommendation content can be relieved, and high-quality recommendation content can be objectively provided for target users.

Description

technical field [0001] The invention relates to a personalized recommendation method for micro-videos under a double-network time-domain evolution model of user deviation degrees, and belongs to the field of computer algorithms. Background technique [0002] Recommendations have been widely used, whether in academia or in other domains such as business. For example, product recommendation in Amazon, movie recommendation in MovieLens, and web page recommendation in Google. With the rapid development of the Internet, social networks such as Weibo, blog, QQ, and e-commerce have emerged and flourished, making information sharing and knowledge exchange more convenient for users. However, with the increase in the amount of information, users cannot filter out the information that is beneficial to their needs in a short time in the face of huge data. At present, the research on recommendation algorithms of social networks has involved many platforms, including online social websi...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 王红滨褚慈谢晓东王勇军原明旗王念滨周连科秦帅张海彬冯梦园
Owner HARBIN ENG UNIV
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