DC FieldValueLanguage
dc.contributor.authorKapellas, Nikos-
dc.contributor.authorKapidakis, Sarantos-
dc.date.accessioned2024-10-09T12:57:26Z-
dc.date.available2024-10-09T12:57:26Z-
dc.date.issued2023-
dc.identifier.isbn978-989-758-671-2-
dc.identifier.isbn2184-3228-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2801-
dc.description.abstractThis research presents a comprehensive analysis of news articles with the primary objectives of exploring the underlying structure of the data and detecting events contained within news articles. The study collects articles from Greek online newspapers and focuses on analyzing a subset of this data, related to a predefined news topic. To achieve this, a hybrid approach that combines topic modeling, feature extraction, clustering, and named entity recognition, is employed. The obtained results prove to be satisfactory, as they demonstrate the effectiveness of the proposed methodology in news event detection and extracting relevant contextual information. This research provides valuable insights for multiple parties, including news organizations, researchers, news readers, and decision-making systems, as it contributes to the fields of event detection and clustering. Moreover, it deepens the understanding of applying solutions that do not require explicit human intervention, to real-world language challenges.en_US
dc.language.isoenen_US
dc.publisherScitepressen_US
dc.relation.ispartofProceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023)en_US
dc.subjectEvent Detectionen_US
dc.subjectNews Articlesen_US
dc.subjectTopic Modelingen_US
dc.subjectNatural Language Processingen_US
dc.subjectUnsupervised Clusteringen_US
dc.subjectNamed Entity Recognitionen_US
dc.titleEvent Detection in News Articles: A Hybrid Approach Combining Topic Modeling, Clustering, and Named Entity Recognitionen_US
dc.typeConference Paperen_US
dc.relation.conference15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management,13-15 November 2023, Rome, Italyen_US
dc.identifier.doi10.5220/0012234300003598en_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume2en_US
dc.relation.issueKEODen_US
dc.identifier.spage272en_US
dc.identifier.epage279en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldEngineering and Technologyen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.openairetypeConference Paper-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-8723-0276-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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