基于热扩散影响力传播的社交网络个性化推荐算法

doi:10.16451/j.cnki.issn1003-6059.201908008

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Abstract

The primary objective of a personalized recommendation system is to provide pertinent recommendations for users and improve internet information utilization. A social network personalized recommendation algorithm based on heat diffusion influence propagation(HDIP) is proposed in this paper combining HDIP with the hidden follow-up relationship in the social network of users. Firstly, in the HDIP algorithm, the friendship in real life is transformed into follow-up relationship between customers in shopping network. Heterogeneous information network graphs are constructed and the composite similarities between users are calculated. Secondly, the influence propagation process in social networks based on the heat diffusion model is simulated. Probability scores of users in the social network are calculated and accurately sorted to select neighboring users similar to the target users. Finally, the products of potential interest are recommended to the target users according to the ranking. Thus, the personalized recommendation is implemented. The public dataset is utilized for the comparison between HDIP and conventional recommendation algorithms. The experimental results show that HDIP produces a relatively high accuracy and various recommendation effects.

Key words： Data Mining Social Network Heat Diffusion Collaborative Filtering Personalized Recommendation

Received: 17 September 2018

ZTFLH:

TP 301

Fund:

Supported by National Natural Science Foundation of China(No.61772252), Natural Science Foundation of Liaoning Province(No.20180550542), Dalian Science and Technology Innovation Fund(No.2018J12GX047), Dalian Key Laboratory Special Fund

Corresponding Authors: REN Yonggong(Corresponding author), Ph.D., professor. His research interests include database technology, data mining and intelligent information calculation.

About author:: YANG Liu, master student. Her research interests include data mining.LIU Yang, Ph.D., lecturer. His research interests include digital image processing and radar retrieval.

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Cite this article:

REN Yonggong,YANG Liu,LIU Yang. Heat Diffusion Influence Propagation Based Personalized Recommendation Algorithm for Social Network[J]. , 2019, 32(8): 746-757.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201908008 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I8/746

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