Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations

Cheng Luo, Wei Pang, Zhe Wang, Chenghua Lin

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

120 Citations (Scopus)
12 Downloads (Pure)


In this paper, we investigate the social-based recommendation algorithms on heterogeneous social networks and proposed Hete-CF, a social collaborative filtering algorithm using heterogeneous relations. Distinct from the exiting methods, Hete-CF can effectively utilise multiple types of relations in a heterogeneous social network. More importantly, Hete-CF is a general approach and can be used in arbitrary social networks, including event based social networks, location based social networks, and any other types of heterogeneous information networks associated with social information. The experimental results on a real-world dataset DBLP (a typical heterogeneous information network)demonstrate the effectiveness of our algorithm.
Original languageEnglish
Title of host publication2014 IEEE International Conference on Data Mining
EditorsRavi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
PublisherIEEE Explore
Number of pages6
ISBN (Electronic)9781479943029
ISBN (Print)9781479943012, 9781479943036
Publication statusPublished - 24 Dec 2014
Event14th IEEE International Conference on Data Mining - Shenzhen, China
Duration: 14 Dec 201417 Dec 2014

Publication series

NameIEEE proceedings
PublisherIEEE Xplore
ISSN (Print)1550-4786
ISSN (Electronic)2374-8486


Conference14th IEEE International Conference on Data Mining
Abbreviated titleICDM 2014

Bibliographical note

The work described here was funded by the National Natural Science
Foundation of China (NSFC) under Grant No. 61373051; the National Science
and Technology Pillar Program (Grant No.2013BAH07F05), the Key Laboratory
for Symbolic Computation and Knowledge Engineering, Ministry of
Education, China, and the UK Economic & Social Research Council (ESRC);
award reference: ES/M001628/1.


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