Document summarization is the process of reducing size of text document and that retains the most important content of the original document into the reduced document(Summary).In recent year there are huge work has been done in document summarization. There are various techniques available for document summarization but most of the techniques used similarity of sentences to extract sentence, in the document summarization a context of the document are important, so our current method used term indexing model to gives index to document as well as sentences in that document. In this proposed system we used context based document indexing based on vector space model. This document indexing model works with document frequency (DF) and term frequency (TF).DF and TF model gives document indexing weight which is used for document summarization. We compare our system with traditional term based indexing model and will prove that our system gives better result than this system.

Vector space model, Document frequency, Term Frequency, Document context

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