Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Generic text summarization using relevance measure and latent semantic analysis
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Advances in Automatic Text Summarization
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MCMR: Maximum coverage and minimum redundant text summarization model
Expert Systems with Applications: An International Journal
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In this paper is proposed the generic summarization method that extracts the most relevance sentences from the source document to form a summary. This method based on clustering of sentences. The specificity of this approach is that the generated summary can contain the main contents of different topics as many as possible and reduce its redundancy at the same time. The clustering method satisfies as much homogeneity within each cluster as well as much separability between the clusters as possible.