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Recommendation method considering overlapping community effect

A recommendation method and overlapping community technology, applied in the recommendation field considering the effect of overlapping communities, can solve problems such as cold start data sparseness

Active Publication Date: 2018-03-27
HEFEI UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the shortcomings of the existing technology, the present invention provides a recommendation method that considers overlapping community effects, in order to effectively solve the problems of "cold start" and data sparseness existing in the existing recommendation system, thereby improving the quality of recommendation and providing Provide users with better personalized services

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  • Recommendation method considering overlapping community effect
  • Recommendation method considering overlapping community effect
  • Recommendation method considering overlapping community effect

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Embodiment Construction

[0039] In this embodiment, a recommendation method that takes into account the effect of overlapping communities is to jointly apply user browsing behavior data and overlapping community data joined by users in a probability generation model. The probability graph model is such as figure 1 Shown. The recommendation method proposed by the present invention is based on the following assumption: each user has a polynomial distribution on a topic, this polynomial distribution will control the generation of two types of topics, one type of topic affects the user's choice of goods, and the other type of topic determines the user to join the community . Based on this assumption, the present invention compares the user as a document, the user's theme preference as the document theme, and the commodity selected by the user and the community joined as two types of words.

[0040] In this embodiment, such as figure 2 As shown, a recommendation method considering overlapping community effe...

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Abstract

The invention discloses a recommendation method considering an overlapping community effect, and the recommendation method is characterized by including the following steps of 1, obtaining a user-theme probability distribution matrix and a theme-commodity probability distribution matrix; 2, calculating the utility of the commodity for the user; and 3, according to the ranking of the utility scorefrom high to low, using the top N items to generate a recommendation list for the user and recommending the recommendation list to the user. The method can effectively solve the problem of 'cold start' and data sparsity in the existing recommendation system so as to improve the recommendation quality and provide better personalized service for the user.

Description

Technical field [0001] The present invention relates to the technical field of personalized recommendation, and specifically is a recommendation method considering overlapping community effects. Background technique [0002] With the rapid development of the Internet, people can establish social relationships, join communities, share, forward or comment on social media such as Twitter and Facebook. At the same time, the rapid growth of user-generated content has exacerbated "information overload", and it is difficult and time-consuming for users to obtain interesting information from massive amounts of data. In order to effectively solve this problem, social media operators establish a recommendation system based on user behavior data to provide users with personalized recommendations. [0003] However, the existing recommendation system takes user browsing behavior data as the only information source, which has the problems of "cold start" and data sparseness. For example, when ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 姜元春姬翠翠刘业政王锦坤孙见山孙春华吕曼丽
Owner HEFEI UNIV OF TECH
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