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- W2758439088 abstract "As the novel web social media emerges on the web, large scale unordered sentences are springing up in the forms: news headlines, microblogs, comments and so on. Domain keywords extraction is very important for information extraction, information retrieval, classification, clustering, topic detection and tracking, and so on. Although these massive sentences contain rich information, their loose semantic association and highly unordered semantic organization make web users extremely difficult to capture the rich information due to the lack of semantic coherence. Sentence ordering is a significant research area focusing on obtaining coherent sentence orders which could assist web user to easily understand these unordered sentences. TextRank is a common graph-based algorithm for keywords extraction. For TextRank, only edge weights are taken into account. We proposed a new text ranking formula that takes into account both edge and node weights of words, named F2N-Rank. The results show our model can obtain coherent sentence orders with higher accuracy in less iterations. The proposed sentence ordering model can be applied in automatic text organization and summarization." @default.
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- W2758439088 date "2017-09-27" @default.
- W2758439088 modified "2023-09-27" @default.
- W2758439088 title "Building Domain Keywords Using Cognitive Based Sentences Framework" @default.
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- W2758439088 doi "https://doi.org/10.1007/978-981-10-3187-8_2" @default.
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