User recommendation method and system based on meta-path similarity, server and storage medium

A recommendation method and recommendation system technology, applied in the field of big data, can solve problems that cannot be solved, and the time complexity of the algorithm is high

Active Publication Date: 2019-07-05
武汉斗鱼鱼乐网络科技有限公司
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AI Technical Summary

Problems solved by technology

[0002] On the live broadcast platform, in order to recommend live broadcast rooms that users are interested in, a collaborative filtering method based on users or live broadcast rooms is usually used, and the similarity between users or live broadcast rooms needs to be calculated. Watch as a vector, calculate the similarity by calculating the cosine distance between the vectors, and use SimRank to calculate the similarity based on the random walk method of the relationship between the user and the live broadcast. There are some problems in the conventional method, and the direct use of the viewing vector only considers whether The relationship between viewing, there is no impact of viewing time on similarity, SimRank uses a graph structure, but the time complexity of the algorithm is very high under the condition of big data, the above method cannot solve the problem of recommending popular live broadcasts to most users

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  • User recommendation method and system based on meta-path similarity, server and storage medium
  • User recommendation method and system based on meta-path similarity, server and storage medium
  • User recommendation method and system based on meta-path similarity, server and storage medium

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Embodiment Construction

[0040] The present invention provides a user recommendation method, system, server and storage medium based on meta-path similarity. The method constructs a heterogeneous network between users and live broadcast rooms, and counts the viewing time of users, and calculates the similarity contribution coefficient between live broadcast rooms to obtain The similarity between users, according to the similarity between users, obtains similar users of the user to be recommended, and recommends the live broadcast rooms watched by similar users to the user to be recommended.

[0041] In order to make the purpose, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the following The described embodiments are only some, not all, embodiments of th...

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Abstract

The invention relates to a user recommendation method and system based on meta-path similarity, a server and a storage medium. The method comprises the following steps: constructing a heterogeneous network between a user and a live broadcast room; according to the live broadcasting room similarity recommendation method, the watching duration is considered, similar users of the to-be-recommended user are obtained, the live broadcasting room watched by the similar users is recommended to the to-be-recommended user, and hot live broadcasting can be quickly recommended to the to-be-recommended user in the live broadcasting room.

Description

technical field [0001] The invention relates to the field of big data, in particular to a user recommendation method, system, server and storage medium based on meta-path similarity. Background technique [0002] On the live broadcast platform, in order to recommend live broadcast rooms that users are interested in, a collaborative filtering method based on users or live broadcast rooms is usually used, and the similarity between users or live broadcast rooms needs to be calculated. Watch as a vector, calculate the similarity by calculating the cosine distance between the vectors, and use SimRank to calculate the similarity based on the random walk method of the relationship between the user and the live broadcast. There are some problems in the conventional method, and the direct use of the viewing vector only considers whether The relationship between viewing and watching time does not affect the similarity. SimRank uses a graph structure, but the time complexity of the al...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/732
Inventor 王璐
Owner 武汉斗鱼鱼乐网络科技有限公司
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