SENTENCE ORDERING USING CLUSTER CORRELATION AND PROBABILITY IN MULTI-DOCUMENTS SUMMARIZATION

Abstrak

Most of the document summary are arranged extractive by taking important sentences from the document. Extractive based summarization often not consider the connection sentence.  A good sentence ordering should aware about rhetorical relations such as cause-effect relation, topical relevancy and chronological sequence which exist between the sentences.  Based on this problem, we propose a new method for sentence ordering in multi document summarization using cluster correlation and probability for English documents. Sentences of multi-documents are grouped based on similarity into clusters. Sentence extracted from each cluster to be a summary that will be listed based on cluster correlation and probability. User evaluation showed that the summary result of proposed method easier to understanding than the previous method. The result of ROUGE method also shows increase on sentence arrangement compared to previous method.