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Pregled bibliografske jedinice broj: 915717

Keyword Extraction Based on Selectivity and Generalized Selectivity


Beliga, Slobodan; Meštrović, Ana; Martinčić-Ipšić, Sanda
Keyword Extraction Based on Selectivity and Generalized Selectivity // Innovations, Developments, and Applications of Semantic Web and Information Systems / Lytras, Miltiadis D. ; Aljohani, Naif ; Damiani, Ernesto ; Chui, Kwok Tai (ur.).
Hershey, PA, USA: IGI Global, 2018. str. 170-204 doi:10.4018/978-1-5225-5042-6.ch007


Naslov
Keyword Extraction Based on Selectivity and Generalized Selectivity

Autori
Beliga, Slobodan ; Meštrović, Ana ; Martinčić-Ipšić, Sanda

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Innovations, Developments, and Applications of Semantic Web and Information Systems

Urednik/ci
Lytras, Miltiadis D. ; Aljohani, Naif ; Damiani, Ernesto ; Chui, Kwok Tai

Izdavač
IGI Global

Grad
Hershey, PA, USA

Godina
2018

Raspon stranica
170-204

ISBN
9781522550426

Ključne riječi
Keyword Extraction ; Keyword Expansion ; Keyword Ranking ; Complex Network ; Graph-Based Keyword Extraction ; Centrality Measures ; Selectivity ; Generalized Selectivity ; SBKE Method

Sažetak
This chapter presents 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 selectivity slightly outperforms an extraction based on the standard centrality measures. Therefore, the selectivity and its modification – generalized selectivity as the node centrality measures are included 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 and it can be easily ported to new languages and used in a multilingual scenario. The true potential of the proposed SBKE method is in its generality, portability and low computation costs, which positions it as a strong candidate for preparing collections which lack human annotations for keyword extraction.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



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