Single Document Keyphrase Extraction Using Sentence Clustering and Latent Dirichlet Allocation

Abstract : This paper describes the design of a system for extracting keyphrases from a single document The principle of the algorithm is to cluster sentences of the documents in order to highlight parts of text that are semantically related. The clusters of sentences, that reflect the themes of the document, are then analyzed to find the main topics of the text. Finally, the most important words, or groups of words, from these topics are proposed as keyphrases.
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https://hal.archives-ouvertes.fr/hal-01151516
Contributor : Claude Pasquier <>
Submitted on : Wednesday, May 13, 2015 - 6:38:09 AM
Last modification on : Thursday, May 3, 2018 - 1:08:47 PM

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  • HAL Id : hal-01151516, version 1

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Claude Pasquier. Single Document Keyphrase Extraction Using Sentence Clustering and Latent Dirichlet Allocation. 5th International Workshop on Semantic Evaluation (SemEval '10), Jul 2010, Uppsala, Sweden. 〈hal-01151516〉

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