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ITI əməkdaslarının elmi isləri Elektron kitabxana Konfranslar İnformasiya Sistemi Qəzetlər UOT 004
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ITI əməkdaşlarının elmi işləri - məqalə


 Biblioqrafik təsvir
 Alguliyev , R.M. A new similarity measure and mathematical model for text summarization / R.M. Alguliyev , R.M. Aliguliyev , N. Isazade // İnformasiya Texnologiyaları Problemləri. - 2015. - N: 1.- P. 42-53.
 Annotasiya
 This paper proposes a new text similarity measure and mathematical model for automatic text summarization. Model consists of two stages. At the first stage, for detection of topics the sentences in document collection are clustered. At the second stage, the model generates a summary by extracting relevant sentences from each cluster. For clustering of sentences the kmeans algorithm is utilized. Sentence selection process is formalized as an optimization problem. To select relevant sentences from each cluster and avoid redundancy in the summary this model uses both the sentence-to-cluster relation and the sentence-to-sentence relation. To solve the optimization problem a differential evolution algorithm with adaptive mutation strategy is developed.
 Elektron variant
Elektron variant

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