异构信息网络中基于元结构的协同过滤算法

Translated title of the contribution: Meta Struct-CF:A Meta Structure Based Collaborative Filtering Algorithm in Heterogeneous Information Networks

Xu Wang, Wei Pang, Zhe Wang

Research output: Contribution to journalArticle

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Abstract

In recent years,heterogeneous information networks (HINs) have received a lot of attention as they contain rich semantic information.Previous works have demonstrated that the rich relationship information in HINs can effectively improve the recommendation performance.As an important tool for mining relationship information in HINs,meta-path has been widely used in many algorithms.However,because of its simple linear structure,meta-path may not be able to express complex relationship information.To address this issue,this paper proposed a new recommendation algorithm,Metastruct-CF,which applies Meta structure to capture the accurate relationship information among data objects.Different from existing methods,the proposed combines algorithm multiple relationships to effectively utilize the information in HINs.Extensive experiments on two real world datasets show that this algorithm achieves better recommendation performance than several popular or state-of-the-art methods.
Translated title of the contributionMeta Struct-CF:A Meta Structure Based Collaborative Filtering Algorithm in Heterogeneous Information Networks
Original languageChinese
Pages (from-to)397-401
Number of pages5
JournalComputer Science
Volume46
Issue number6A
Publication statusPublished - Jun 2019

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