A relevance-based topic model for news event tracking

Viet Ha-Thuc, Yelena Mejova, Christopher Harris, Padmini Srinivasan

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

13 Citations (Scopus)

Abstract

Event tracking is the task of discovering temporal patterns of popular events from text streams. Existing approaches for event tracking have two limitations: scalability and inability to rule out non-relevant portions in text streams. In this study, we propose a novel approach to tackle these limitations. To demonstrate the approach, we track news events across a collection of weblogs spanning a two-month time period.

Original languageEnglish
Title of host publicationProceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
Pages764-765
Number of pages2
DOIs
Publication statusPublished - 28 Dec 2009
Externally publishedYes
Event32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009 - Boston, MA, United States
Duration: 19 Jul 200923 Jul 2009

Other

Other32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
CountryUnited States
CityBoston, MA
Period19/7/0923/7/09

Fingerprint

Scalability
Topic model
News

Keywords

  • Event tracking
  • LDA
  • Relevance models
  • Topic models

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

Cite this

Ha-Thuc, V., Mejova, Y., Harris, C., & Srinivasan, P. (2009). A relevance-based topic model for news event tracking. In Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009 (pp. 764-765) https://doi.org/10.1145/1571941.1572117

A relevance-based topic model for news event tracking. / Ha-Thuc, Viet; Mejova, Yelena; Harris, Christopher; Srinivasan, Padmini.

Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009. 2009. p. 764-765.

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

Ha-Thuc, V, Mejova, Y, Harris, C & Srinivasan, P 2009, A relevance-based topic model for news event tracking. in Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009. pp. 764-765, 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009, Boston, MA, United States, 19/7/09. https://doi.org/10.1145/1571941.1572117
Ha-Thuc V, Mejova Y, Harris C, Srinivasan P. A relevance-based topic model for news event tracking. In Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009. 2009. p. 764-765 https://doi.org/10.1145/1571941.1572117
Ha-Thuc, Viet ; Mejova, Yelena ; Harris, Christopher ; Srinivasan, Padmini. / A relevance-based topic model for news event tracking. Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009. 2009. pp. 764-765
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