Abstract
Document summarization is an important step while clustering the large no. of digital documents data base. Documents are clustered in accordance with their contents using the document text summary. The document summarization involves the knowledge corpus scheme comprising of corpus coverage, sentence coverage and term coverage weight. Further, three new weights are introduced as super sentence coverage weight, super corpus coverage weight and super term coverage weight. Super coverage weight is based on synonyms of the key words. The quality of document summary improves and diversified when synonyms of key words are also given due weightage in the process of text processing. The evaluation for the document summary quality is based on inner content metrics precision, recall, F-measure method.
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