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Identifying Temporal Corpus for Enhanced User Comments Analysis

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dc.contributor.authorJeong, Jongwook-
dc.contributor.authorLee, Youn Kyu-
dc.date.accessioned2023-12-11T07:07:16Z-
dc.date.available2023-12-11T07:07:16Z-
dc.date.issued2022-03-01-
dc.identifier.issn0218-1940-
dc.identifier.issn1793-6403-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/32065-
dc.description.abstractUser comments provide valuable information for requirements analysis. To effectively extract requirements from user comments, it is important to determine informative user comments. However, existing studies have mainly focused on NLP-based methods for analyzing user comments, rather than defining a set of user comments to be analyzed. If target user comments are not clearly determined, duplicate requirements can be discovered or new requirements cannot be discovered. To tackle this problem, we present a new method which defines a set of target corpora from user comments. Our method automatically defines a set of target corpora to be analyzed by identifying underlying temporal changes in user comments. We applied our method to real-world user comments collected from a mobile application store. We confirmed that our method successfully defined a set of corpora which aids the effective requirements elicitation, and facilitated discovering new requirements while avoiding the derivation of redundant requirements.-
dc.format.extent18-
dc.language영어-
dc.language.isoENG-
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD-
dc.titleIdentifying Temporal Corpus for Enhanced User Comments Analysis-
dc.typeArticle-
dc.publisher.location싱가폴-
dc.identifier.doi10.1142/S021819402250022X-
dc.identifier.scopusid2-s2.0-85129786915-
dc.identifier.wosid000793205300005-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, v.32, no.03, pp 439 - 456-
dc.citation.titleINTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING-
dc.citation.volume32-
dc.citation.number03-
dc.citation.startPage439-
dc.citation.endPage456-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordAuthorUser feedback-
dc.subject.keywordAuthoruser requirements-
dc.subject.keywordAuthorrequirements engineering-
dc.subject.keywordAuthornatural language processing-
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