relation: https://khub.utp.edu.my/scholars/15152/
title: KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data
creator: Aman, M.
creator: Abdulkadir, S.J.
creator: Aziz, I.A.
creator: Alhussian, H.
creator: Ullah, I.
description: Automatic key concept identification from text is the main challenging task in information extraction, information retrieval, digital libraries, ontology learning, and text analysis. The main difficulty lies in the issues with the text data itself, such as noise in text, diversity, scale of data, context dependency and word sense ambiguity. To cope with this challenge, numerous supervised and unsupervised approaches have been devised. The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. In this paper, a semantic based unsupervised approach (KP-Rank) is proposed for keyphrase extraction. In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. To evaluate the performance of the proposed method, three benchmark datasets (i.e. Inspec, 500N-KPCrowed and SemEval-2010) from different domains are used. The experimental results show that overall, the KP-Rank achieved significant improvements over the existing approaches on the selected performance measures. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
publisher: Springer
date: 2021
type: Article
type: PeerReviewed
identifier:   Aman, M. and Abdulkadir, S.J. and Aziz, I.A. and Alhussian, H. and Ullah, I.  (2021) KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data.  Multimedia Tools and Applications, 80 (8).  pp. 12469-12506.  ISSN 13807501     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099375213&doi=10.1007%2fs11042-020-10215-x&partnerID=40&md5=9d0ccf1ff2f914e59a57acc66aadf9d6
relation: 10.1007/s11042-020-10215-x
identifier: 10.1007/s11042-020-10215-x