Summary evaluation and text categorization

Authors:
Khurshid Ahmad;Bogdan Vrusias;Paulo C F de Oliveira
Affiliations:
University of Surrey, Guildford - Surrey, UK;University of Surrey, Guildford - Surrey, UK;University of Surrey, Guildford - Surrey, UK
Venue:
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Year:
2003

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Abstract

In general terms the evaluation of a summary depends on how close it is to the chief points in the source text. This begets the question as to what are the chief points in the source text and how is this information used in itself in identifying the source text. This is crucially important when we discuss automatic evaluation of summaries. So the question of main points is the source text. Typically, this would be around a nucleus of keywords. However, the salience, the frequency, and the relationship of the text with other texts in the collection (of these keywords is perhaps) are important. Text categorisation using neural networks explicates these points well and also has a practical impact.