Training a Selection Function for Extraction

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Training a Selection Function for Extraction
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence affects the performance of each heuristic. We study how different query types can affect the performance of each heuristic and discuss the possibility of using machine learning algorithms to automatically learn good combination functions to combine several heuristics. We also briefly describe the design, implementation, and performance of a multilingual text summarization system SUMMARIST. Keywords Automated text summarization, topic extraction, summary evaluation.
Chin-Yew Lin
Added 03 Aug 2010
Updated 03 Aug 2010
Type Conference
Year 1999
Where CIKM
Authors Chin-Yew Lin
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