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ECIR
2016
Springer

Semi-Supervised Events Clustering in News Retrieval

4 years 3 months ago
Semi-Supervised Events Clustering in News Retrieval
The presentation of news articles to meet research needs has traditionally been a document-centric process. Yet users often want to monitor developing news stories based on an event, rather than by examining an exhaustive list of retrieved documents. In this work, we illustrate a news retrieval system, eventNews, and an underlying algorithm which is event-centric. Through this system, news articles are clustered around a single news event or an event and its sub-events. The algorithm presented can leverage the creation of new Reuters stories and their compact labels as seed documents for the clustering process. The system is configured to generate top-level clusters for news events based on an editorially supplied topical label, known as a ‘slugline,’ and to generate sub-topic-focused clusters based on the algorithm. The system uses an agglomerative clustering algorithm to gather and structure documents into distinct result sets. Decisions on whether to merge related documents or...
Jack G. Conrad, Michael Bender
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where ECIR
Authors Jack G. Conrad, Michael Bender
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