Clustering and Feature Specific Sentence Extraction Based Summarization of Multiple Documents

This paper presents an approach to cluster multiple documents by using document clustering approach and to produce cluster wise summary based on feature profile oriented sentence extraction strategy. Related documents are grouped into same cluster using document clustering algorithm. Feature profile is generated by considering word weight, sentence position, sentence length, sentence centrality, proper nouns in the sentence and numerical data in the sentence. Based on the feature profile sentence score is calculated for each sentence. According to different compression rates sentences are extracted from each cluster and ranked in order of importance based on sentence score. Extracted sentences are arranged in chronological order as in original documents and from this, cluster wise summary can be generated. Experimental results show that the proposed clustering algorithm is efficient and feature profile is used to extract most important sentences from multiple documents.