Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

10-2008

Abstract

In this paper, we aim at detecting events of common user interests from huge volume of user-generated content. The degree of interest from common users in an event is evidenced by a significant surge of event-related queries issued to search for documents (e.g., news articles, blog posts) relevant to the event. Taking the stream of queries from users and the stream of documents as input, our proposed framework seamlessly integrates the two streams into a single stream of query profiles. A query profile is a set of documents matching a query at a given time. With the single stream of query profiles, the well-studied techniques in event detection (e.g., incremental clustering) could be easily applied. In our experiments using real data collected from Blog and News search engines respectively, the proposed technique achieved very high event detection accuracy.

Keywords

blog, event detection, popular queries, query profile

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

WIDM '08: Proceedings of the 10th ACM workshop on Web information and data management

First Page

1

Last Page

8

ISBN

9781605582603

Identifier

10.1145/1458502.1458504

Publisher

ACM

Additional URL

http://doi.org/10.1145/1458502.1458504

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