Recommendation method based on deep social relationship

A social relationship and recommendation method technology, applied in the field of personalized recommendation, can solve problems such as data sparsity, achieve the effect of improving accuracy and solving data sparsity problems

Active Publication Date: 2018-07-24
HEFEI UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of data sparsity in existing collaborative filtering algorithms, the present invention proposes a recommendation method based on deep social relationships, hoping to make full use of the social relationship

Method used

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  • Recommendation method based on deep social relationship
  • Recommendation method based on deep social relationship
  • Recommendation method based on deep social relationship

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Experimental program
Comparison scheme
Effect test

Embodiment

[0100] In order to verify the effectiveness of this method, this paper selects the Flixster and Douban data sets commonly used in recommendation systems. For these two data sets, users with at least 5 rating records and 5 social relations are retained, and then items with less than 5 rating records are filtered out to obtain the data set used in the final experiment.

[0101] This article uses Hit Ratio (HR) and Normalized Discounted Cumulative Gain (NDCG) as evaluation criteria.

[0102] This paper selects 7 methods to compare the effects with the methods proposed in this paper, namely PMF, SR, SocialMF, AutoRec, NeuMF, CNR and NSR. Specifically, according to the experimental results, the results can be drawn as Figure 2a , Figure 2b As shown, the experimental results show that the method proposed in this paper is better than the seven selected methods. Such as Figure 3a , Figure 3b As shown, the experimental results also show that the method proposed in this paper i...

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Abstract

The invention discloses a recommendation method based on deep social relationship, which comprises the steps of 1, constructing a rating matrix of users for an object and a social relationship matrixamong the users; 2, constructing an input layer in a one-hot coding mode; 3, obtaining a social embedded matrix by automatic coding according to the social relationship matrix among the users; 4, constructing an embedded layer through the input layer and the social embedded matrix; 5, constructing a collaboration layer through the embedded layer; and 6, inputting information of the collaboration layer into a hidden layer to obtain corresponding predicted score information, and thus performing object recommendation. According to the invention, the social relationship among the users can be fully utilized to solve a problem of data sparsity, excellent accuracy is ensured at the same time through establishing a complex deep neural network structure between users and objects, and thus accuraterecommendation is carried out for the users.

Description

technical field [0001] The invention relates to the field of personalized recommendation, in particular to a recommendation method based on deep social relationships. technical background [0002] With the advent of the era of information explosion, recommendation systems are used in various industries, including: movies, books, academic papers, etc. The recommendation system mainly recommends items for each user independently based on the user's past purchase records and search history, as well as the behavior of other users. [0003] Collaborative filtering algorithms are widely used in the field of recommendation systems. The collaborative filtering algorithm discovers the user's preferences by mining the user's historical behavior data, divides the users into groups based on different preferences, and recommends items with similar tastes. Although the collaborative filtering algorithm is widely used and has high precision, it has the problem of data sparsity. [0004]...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q30/06G06Q50/00G06F17/30
CPCG06Q30/0218G06Q30/0224G06Q30/0631G06Q50/01G06F16/2465
Inventor 吴乐孙培杰汪萌洪日昌刘学亮杨文娟
Owner HEFEI UNIV OF TECH
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