Abstract
The automatic keyphrases extraction is a useful task for many computational applications in the natural language processing and text mining fields. Several solutions to this problem have been reported, but the obtained results still show low rates of accuracy and performance. In this paper, a new unsupervised method for keyphrase extraction from text documents is proposed. The use of lexical-syntactic patterns is combined with a graph-based topic modeling in this approach. The topic modeling is supported by a semantic analysis process carried out from the fuzzy logic perspective. The method was evaluated with the SemEval-2010 and Inspec datasets and compared with other state-of-the-art proposals.
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