Extraction Based Multi Document Summarization using Single Document Summary Cluster

Multi document summarization has very great impact amongresearch community, ever since the growth of online informationand availability. Selecting most important sentences from suchhuge repository of data is quiet tricky and challenging task. Whilemulti document poses some additional overhead in sentenceselection, generating summaries for each individual documentsand merging the sentences in a coherent order would greaterstrength. The proposed approach was competitively better ascompared to state of MEAD summarizer at focused compressionratios. This paper focus on three different studies namely i. Tofind the performance of multi document summarizer from singledocument cluster (using MEAD) ii. Comparison of our approachwith MEAD performance for the dataset considered iii. To extractsentences for multi document summarization at 30% compressionrate to obtain 100% efficiency using 7-point summary sheet. Investigation carried out from an average of 22 documents showsthat our system is promising