A relevance-based topic model for news event tracking

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. Categories and Subject Descriptors

• Type: Conference
• Year: 2009
• Where: SIGIR
• Authors: Viet Ha-Thuc, Yelena Mejova, Christopher Harris, Padmini Srinivasan
• Keywords: Event Tracking, Information Retrieval, SIGIR 2009, Temporal Patterns, Text Streams