Topical keyphrase extraction with hierarchical semantic networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sung, Yoo Yeon | - |
dc.contributor.author | Kim, Seoung Bum | - |
dc.date.accessioned | 2021-08-31T14:49:20Z | - |
dc.date.available | 2021-08-31T14:49:20Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2020-01 | - |
dc.identifier.issn | 0167-9236 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/58397 | - |
dc.description.abstract | Topical keyphrase extraction is used to summarize large collections of text documents. However, traditional methods cannot properly reflect the intrinsic semantics and relationships of keyphrases because they rely on a simple term-frequency-based process. Consequently, these methods are not effective in obtaining significant contextual knowledge. To resolve this, we propose a topical keyphrase extraction method based on a hierarchical semantic network and multiple centrality network measures that together reflect the hierarchical semantics of keyphrases. We conduct experiments on real data to examine the practicality of the proposed method and to compare its performance with that of existing topical keyphrase extraction methods. The results confirm that the proposed method outperforms state-of-the-art topical keyphrase extraction methods in terms of the representativeness of the selected keyphrases for each topic. The proposed method can effectively reflect intrinsic keyphrase semantics and interrelationships. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | CENTRALITY | - |
dc.title | Topical keyphrase extraction with hierarchical semantic networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Seoung Bum | - |
dc.identifier.doi | 10.1016/j.dss.2019.113163 | - |
dc.identifier.scopusid | 2-s2.0-85074529522 | - |
dc.identifier.wosid | 000501403000007 | - |
dc.identifier.bibliographicCitation | DECISION SUPPORT SYSTEMS, v.128 | - |
dc.relation.isPartOf | DECISION SUPPORT SYSTEMS | - |
dc.citation.title | DECISION SUPPORT SYSTEMS | - |
dc.citation.volume | 128 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordPlus | CENTRALITY | - |
dc.subject.keywordAuthor | Topical keyphrase extraction | - |
dc.subject.keywordAuthor | Semantic relationships | - |
dc.subject.keywordAuthor | Hierarchical networks | - |
dc.subject.keywordAuthor | Phrase rankings | - |
dc.subject.keywordAuthor | Text mining | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.