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2006
Springer

Analyzing Entities and Topics in News Articles Using Statistical Topic Models

8 years 4 months ago
Analyzing Entities and Topics in News Articles Using Statistical Topic Models
Statistical language models can learn relationships between topics discussed in a document collection and persons, organizations and places mentioned in each document. We present a novel combination of statistical topic models and named-entity recognizers to jointly analyze entities mentioned (persons, organizations and places) and topics discussed in a collection of 330,000 New York Times news articles. We demonstrate an analytic framework which automatically extracts from a large collection: topics; topic trends; and topics that relate entities.
David Newman, Chaitanya Chemudugunta, Padhraic Smy
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where ISI
Authors David Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
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