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Query-Guided Event Detection from News and Blog Streams Aixin Sun and Meishan Hu
 

Summary: Query-Guided Event Detection from News and Blog Streams
Aixin Sun and Meishan Hu
Nanyang Technological University, Nanyang Avenue, Singapore 639798
axsun@ntu.edu.sg
Abstract
With the advent of Web 2.0, searching and publishing be-
come two major forms of online activities for web users.
When an event happens, web users would search for the
latest information about the event as well as publish blog
posts to discuss the event. Both the queries from users and
the blog posts published give strong indications of the real-
world events of users' concern. In this paper, we propose to
study query-guided event detection from two parallel doc-
ument streams (i.e., news and blog). Our goal is to group
user queries, news articles, and blog posts into events to
which they are related. The evolution of an event is reflected
by the changes in both the query keywords and news/blogs
content during the event happening period. We propose a
two-stage real-time event detection framework consisting of
event fragment detection and event detection. The proposed

  

Source: Aixin, Sun - School of Computer Engineering, Nanyang Technological University

 

Collections: Computer Technologies and Information Sciences