Selectivity-Based Keyword Extraction Method
Slobodan Beliga,
Ana Meštrović and
Sanda Martinčić-Ipšić
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Slobodan Beliga: Department of Informatics, University of Rijeka, Rijeka, Croatia
Ana Meštrović: Department of Informatics, University of Rijeka, Rijeka, Croatia
Sanda Martinčić-Ipšić: Department of Informatics, University of Rijeka, Rijeka, Croatia
International Journal on Semantic Web and Information Systems (IJSWIS), 2016, vol. 12, issue 3, 1-26
Abstract:
In this work the authors propose a novel Selectivity-Based Keyword Extraction (SBKE) method, which extracts keywords from the source text represented as a network. The node selectivity value is calculated from a weighted network as the average weight distributed on the links of a single node and is used in the procedure of keyword candidate ranking and extraction. The authors show that selectivity-based keyword extraction slightly outperforms an extraction based on the standard centrality measures: in/out-degree, betweenness and closeness. Therefore, they include selectivity and its modification – generalized selectivity as node centrality measures in the SBKE method. Selectivity-based extraction does not require linguistic knowledge as it is derived purely from statistical and structural information of the network. The experimental results point out that selectivity-based keyword extraction has a great potential for the collection-oriented keyword extraction task.
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:12:y:2016:i:3:p:1-26
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