Latent semantic analysis for multiple-type interrelated data objects

Xuanhui Wang, Jian Tao Sun, Zheng Chen, Cheng Xiang Zhai

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

Abstract

Co-occurrence data is quite common in many real applications. Latent Semantic Analysis (LSA) has been successfully used to identify semantic relations in such data. However, LSA can only handle a single co-occurrence relationship between two types of objects. In practical applications, there are many cases where multiple types of objects exist and any pair of these objects could have a pairwise co-occurrence relation. All these co-occurrence relations can be exploited to alleviate data sparseness or to represent objects more meaningfully. In this paper, we propose a novel algorithm, M-LSA, which conducts latent semantic analysis by incorporating all pairwise co-occurrences among multiple types of objects. Based on the mutual reinforcement principle, M-LSA identifies the most salient concepts among the co-occurrence data and represents all the objects in a unified semantic space. M-LSA is general and we show that several variants of LSA are special cases of our algorithm. Experiment results show that M-LSA outperforms LSA on multiple applications, including collaborative filtering, text clustering, and text categorization.

Original languageEnglish (US)
Title of host publicationProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery
Pages236-243
Number of pages8
ISBN (Print)1595933697, 9781595933690
DOIs
StatePublished - 2006
Event29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - Seatttle, WA, United States
Duration: Aug 6 2006Aug 11 2006

Publication series

NameProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Volume2006

Other

Other29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Country/TerritoryUnited States
CitySeatttle, WA
Period8/6/068/11/06

Keywords

  • LSA
  • M-LSA
  • Multiple-type
  • Mutual reinforcement principle

ASJC Scopus subject areas

  • General Engineering
  • Information Systems
  • Software
  • Applied Mathematics

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