抽象的な

Multi-document Summarization Based on Cluster

Khanapure V.M, Prof. Chirchi V.R

A summary can be loosely defined as a text which is produced from one or more texts, that contain a significant portion of the information in the original text(s), and that is no longer than half of the original text(s).The main goal of a summary is to present the main ideas in a document in less space. Multi-document summarization is the process of producing a single summary of a set of related source documents, is relatively new. For handling multiple input document following are the problems1.Recognizing and coping with redundancy 2.Identifying important differences among document and 3.Covering the informative content as much as possible. In this paper, to address these problems, we propose multidoument summarization based on cluster using sentence-level semantic analysis (SLSS), mixture model and symmetric non-negative matrix factorization (SNMF).