Purpose. Data mining is the forthcoming research area to solve different problems and classification is one of main problem in the field of data mining. In this paper, we use two classification algorithms J48 and Sequential Minimal Optimization alias SMO of the Weka interface.

Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. Resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents. This proposed work CBRS (Cluster Based Ranking with Significance) summarizes the multi document with semantic meaning of the terms in the documents. Such that it produces a good results while clustering and ranking with retrieving document. As a clustering result to improve or refine the sentence ranking results. The effectiveness of the proposed approach is demonstrated by both the cluster quality analysis and the summarization evaluation conducted on our simulated datasets.

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