EnBlogue: emergent topic detection in web 2.0 streams

Authors:
Foteini Alvanaki;Michel Sebastian;Krithi Ramamritham;Gerhard Weikum
Affiliations:
Saarland University, Saarbruecken, Germany;Saarland University, Saarbruecken, Germany;IIT Bombay, Mumbai, India;Max-Planck Institute Informatics, Saarbruecken, Germany
Venue:
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Year:
2011

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Abstract

Emergent topics are newly arising themes in news, blogs, or tweets, often implied by interesting and unexpected correlations of tags or entities. We present the enBlogue system for emergent topic detection. The name enBlogue reflects the analogy with emerging trends in fashion often referred to as en Vogue. EnBlogue continuously monitors Web 2.0 streams and keeps track of sudden changes in tag correlations which can be adjusted using personalization to reflect particular user interests. We demonstrate enBlogue with several real-time monitoring scenarios as well as with time lapse on archived data.