异构信息网络中基于元结构的协同过滤算法

摘要/Abstract

摘要： 近年来,异构信息网络由于包含丰富的语义信息引起了众多研究者的关注。已有的研究已经证实异构信息网络中丰富的关系信息能够提高推荐效果。作为一种挖掘异构信息网络中关系信息的重要工具,元路径已经被广泛地应用到许多算法中,然而元路径受到线性结构的限制,不能表示更加复杂的关系信息。为了解决这一问题,文中提出了一种新的推荐系统算法,即MetaStruct-CF。该算法利用元结构来挖掘异构信息网络中丰富的关系信息。不同于现有的一些算法,该算法结合了多种信息,以有效地利用异构信息网络中丰富的信息。两个真实世界数据集上的大量实验表明,MetaStruct-CF能够有效地提高推荐效果。

关键词: 推荐系统, 协同过滤, 异构信息网络, 元结构

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.

Key words: Collaborative filtering, Heterogeneous information network, Meta structure, Recommendation systems

中图分类号:

TP391

王旭, 庞巍, 王喆. 异构信息网络中基于元结构的协同过滤算法[J]. 计算机科学, 2019, 46(6A): 397-401. https://doi.org/

WANG Xu, PANG Wei, WANG Zhe. MetaStruct-CF:A Meta Structure Based Collaborative Filtering Algorithm in Heterogeneous Information Networks[J]. Computer Science, 2019, 46(6A): 397-401. https://doi.org/

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