Extractive Summarization Technique Based on Fuzzy Membership Calculation Using Rough Sets

摘要

Selection of important sentences from a document is an important task in Automatic text summarization systems. When these sentences are presented without any modification in their syntax and semantics, they form extractive summary of the given text document. Extractive summarization techniques based on statistical methods like word frequency, indicator phrases and word co-occurrence are language independent. Recent studies have shown that word co-occurrence information can improve the quality of extractive summaries. This paper presents a statistical technique to identify important sentences of a text document using word co-occurrence information. The proposed technique adopts the rough set approach of Reduct and Core calculation for a given data. Fuzzy core concept is used, when the Core is empty or whenever the Core has to be enhanced. The proposed technique is tested with DUC 2002 data Sets and has given good results.