A relevance-based topic model for news event tracking

Authors:
Viet Ha-Thuc;Yelena Mejova;Christopher Harris;Padmini Srinivasan
Affiliations:
The University of Iowa, Iowa City, IA, USA;The University of Iowa, Iowa City, IA, USA;The University of Iowa, Iowa City, IA, USA;The University of Iowa, Iowa City, IA, USA
Venue:
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Year:
2009

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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.