Collective topic modeling for heterogeneous networks

Hongbo Deng, Bo Zhao, Jiawei Han

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

Abstract

In this paper, we propose a joint probabilistic topic model for simultaneously modeling the contents of multi-typed objects of a heterogeneous information network. The intuition behind our model is that different objects of the heterogeneous network share a common set of latent topics so as to adjust the multinomial distributions over topics for different objects collectively. Experimental results demonstrate the effectiveness of our approach for the tasks of topic modeling and object clustering.

Original languageEnglish (US)
Title of host publicationSIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery
Pages1109-1110
Number of pages2
ISBN (Print)9781450309349
DOIs
StatePublished - Jan 1 2011
Event34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011 - Beijing, China
Duration: Jul 24 2011Jul 28 2011

Publication series

NameSIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011
CountryChina
CityBeijing
Period7/24/117/28/11

Keywords

  • Heterogeneous network
  • Topic modeling

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Deng, H., Zhao, B., & Han, J. (2011). Collective topic modeling for heterogeneous networks. In SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1109-1110). (SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval). Association for Computing Machinery. https://doi.org/10.1145/2009916.2010073