The two-stage unsupervised approach to multidocument summarization

This paper suggests an approach for creating a summary for a set of documents with revealing the topics and extracting informative sentences. The topics are determined through clustering of sentences, and the informative sentences are extracted using the ranking algorithm. The result of the summarization has been shown depends on the clustering method, the ranking algorithm, and the similarity measure. The experiments on an open benchmark datasets DUC2001 and DUC2002 have showed that the suggested clustering methods and the ranking algorithm show better results than the known k-means method and the ranking algorithms PageRank and HITS.