Connecting users with similar interests via tag network inference

Xufei Wang, Huan Liu, Wei Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations


The popularity of social networking greatly increases interaction among people. However, one major challenge remains - how to connect people who share similar interests. In a social network, the majority of people who share similar interests with given a user are in the long tail that accounts for 80% of total population. Searching for similar users by following links in social network has two limitations: it is inefficient and incomplete. Thus, it is desirable to design new methods to find like-minded people. In this paper, we propose to use collective wisdom from the crowd or tag networks to solve the problem. In a tag network, each node represents a tag as described by some words, and the weight of an undirected edge represents the co-occurrence of two tags. As such, the tag network describes the semantic relationships among tags. In order to connect to other users of similar interests via a tag network, we use diffusion kernels on the tag network to measure the similarity between pairs of tags. The similarity of people's interests are measured on the basis of similar tags they share. To recommend people who are alike, we retrieve top k people sharing the most similar tags. Compared to two baseline methods triadic closure and LSI, the proposed tag network approach achieves 108% and 27% relative improvements on the BlogCatalog dataset, respectively.

Original languageEnglish (US)
Title of host publicationCIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
Number of pages6
StatePublished - 2011
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: Oct 24 2011Oct 28 2011

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Other20th ACM Conference on Information and Knowledge Management, CIKM'11
Country/TerritoryUnited Kingdom


  • diffusion kernel
  • like-minded users
  • tag network

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)


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