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ECAI
2010
Springer
10 years 2 months ago
From bursty patterns to bursty facts: The effectiveness of temporal text mining for news
Many document collections are by nature dynamic, evolving as the topics or events they describe change. The goal of temporal text mining is to discover bursty patterns and to ident...
Ilija Subasic, Bettina Berendt
KDD
2007
ACM
176views Data Mining» more  KDD 2007»
11 years 4 months ago
Mining correlated bursty topic patterns from coordinated text streams
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
SDM
2007
SIAM
177views Data Mining» more  SDM 2007»
10 years 5 months ago
Bursty Feature Representation for Clustering Text Streams
Text representation plays a crucial role in classical text mining, where the primary focus was on static text. Nevertheless, well-studied static text representations including TFI...
Qi He, Kuiyu Chang, Ee-Peng Lim, Jun Zhang
IAT
2009
IEEE
10 years 11 months ago
STORIES in Time: A Graph-Based Interface for News Tracking and Discovery
—We present the STORIES methods and tool for (a) an abstracted story representation from a collection of time-indexed documents; (b) visualising it in a way that encourages users...
Bettina Berendt, Ilija Subasic
ACL
2012
8 years 6 months ago
Finding Bursty Topics from Microblogs
Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Al...
Qiming Diao, Jing Jiang, Feida Zhu, Ee-Peng Lim
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