Ramiz M. Aliguliyev

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The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a large volume of documents, presenting the user with a summary of each document greatly facilitates the task of finding the desired documents.(More)
Multi-document summarization is a process of automatic creation of a compressed version of a given collection of documents that provides useful information to users. In this article we propose a generic multi-document summarization method based on sentence clustering. We introduce five clustering methods, which optimize various aspects of intra-cluster(More)
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(More)
With the rapid growth of information on the Internet and electronic government recently, automatic multi-document summarization has become an important task. Multi-document summarization is an optimization problem requiring simultaneous optimization of more than one objective function. In this study, when building summaries from multiple documents, we(More)
Text summarization is the process of automatically creating a compressed version of a given document preserving its information content. There are two types of summarization: extractive and abstrac-tive. Extractive summarization methods simplify the problem of summarization into the problem of selecting a representative subset of the sentences in the(More)