Selectivity-Based Keyword Extraction Method

doi:10.4018/IJSWIS.2016070101

Selectivity-Based Keyword Extraction Method

2016-07-01

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Sanda Martinčić-Ipšić

DOI：10.4018/IJSWIS.2016070101

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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.

Keyword:

Centrality Measures

Complex Network

Generalized Selectivity

Graph-Based Keyword Extraction

Keyword Expansion

Keyword Extraction

Keyword Ranking

Selectivity

Selectivity-Based Keyword Extraction Method

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