Abstract

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 publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages1019-1024
Number of pages6
DOIs
StatePublished - 2011
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: Oct 24 2011Oct 28 2011

Other

Other20th ACM Conference on Information and Knowledge Management, CIKM'11
CountryUnited Kingdom
CityGlasgow
Period10/24/1110/28/11

Fingerprint

Tag
Inference
Social networks
Kernel
Wisdom
Long tail
Interaction
Node
Top-k
Social networking
Closure

Keywords

  • diffusion kernel
  • like-minded users
  • tag network

ASJC Scopus subject areas

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

Cite this

Wang, X., Liu, H., & Fan, W. (2011). Connecting users with similar interests via tag network inference. In International Conference on Information and Knowledge Management, Proceedings (pp. 1019-1024) https://doi.org/10.1145/2063576.2063723

Connecting users with similar interests via tag network inference. / Wang, Xufei; Liu, Huan; Fan, Wei.

International Conference on Information and Knowledge Management, Proceedings. 2011. p. 1019-1024.

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

Wang, X, Liu, H & Fan, W 2011, Connecting users with similar interests via tag network inference. in International Conference on Information and Knowledge Management, Proceedings. pp. 1019-1024, 20th ACM Conference on Information and Knowledge Management, CIKM'11, Glasgow, United Kingdom, 10/24/11. https://doi.org/10.1145/2063576.2063723
Wang X, Liu H, Fan W. Connecting users with similar interests via tag network inference. In International Conference on Information and Knowledge Management, Proceedings. 2011. p. 1019-1024 https://doi.org/10.1145/2063576.2063723
Wang, Xufei ; Liu, Huan ; Fan, Wei. / Connecting users with similar interests via tag network inference. International Conference on Information and Knowledge Management, Proceedings. 2011. pp. 1019-1024
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