A Query-Based Summarizer based on the Context

Divya Vidyadharan, Anju CR

Abstract: Summarization condenses a document or multiple documents into a smaller version by preserving the information content and its meaning. It is very difficult to summarize large documents manually. Many summarizers have been developed to capture the content of the document. Existing models use similarity between the sentences to extract the most salient features. The techniques do not depend on the context of the document. A context sensitive model based on association of the terms is introduced. The resulting index weights are used to calculate sentence similarity.

Keywords: query summarizer, lexical association, term frequency, sentence similarity