LexTrim: a lexical cohesion based approach to parse-and-trim style headline generation

Authors:
Ruichao Wang;Nicola Stokes;William Doran;Eamonn Newman;John Dunnion;Joe Carthy
Affiliations:
Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland;Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland;Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland;Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland;Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland;Intelligent Information Retrieval Group, Department of Computer Science, University College Dublin, Ireland
Venue:
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Year:
2005

Citing 2
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Abstract

In this paper we compare two parse-and-trim style headline generation systems. The Topiary system uses a statistical learning approach to finding topic labels for headlines, while our approach, the LexTrim system, identifies key summary words by analysing the lexical cohesion structure of a text. The performance of these systems is evaluated using the ROUGE evaluation suite on the DUC 2004 news stories collection.