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A relevance-based topic model for news event tracking
Conference proceeding

A relevance-based topic model for news event tracking

Viet Ha-Thuc, Yelena Mejova, Christopher Harris and Padmini Srinivasan
Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval, pp.764-765
SIGIR '09
07/19/2009
DOI: 10.1145/1571941.1572117

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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.
relevance models LDA topic models event tracking

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