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COLING
2008

Detecting Multiple Facets of an Event using Graph-Based Unsupervised Methods

11 years 2 months ago
Detecting Multiple Facets of an Event using Graph-Based Unsupervised Methods
We propose a new unsupervised method for topic detection that automatically identifies the different facets of an event. We use pointwise Kullback-Leibler divergence along with the Jaccard coefficient to build a topic graph which represents the community structure of the different facets. The problem is formulated as a weighted set cover problem with dynamically varying weights. The algorithm is domainindependent and generates a representative set of informative and discriminative phrases that cover the entire event. We evaluate this algorithm on a large collection of blog postings about different news events and report promising results.
Pradeep Muthukrishnan, Joshua Gerrish, Dragomir R.
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where COLING
Authors Pradeep Muthukrishnan, Joshua Gerrish, Dragomir R. Radev
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