Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJBIDM.2007.016382
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dc.titleApplication of association rules mining to Named Entity Recognition and co-reference resolution for the Indonesian language
dc.contributor.authorBudi, I.
dc.contributor.authorBressan, S.
dc.date.accessioned2013-07-04T07:40:43Z
dc.date.available2013-07-04T07:40:43Z
dc.date.issued2007
dc.identifier.citationBudi, I.,Bressan, S. (2007). Application of association rules mining to Named Entity Recognition and co-reference resolution for the Indonesian language. International Journal of Business Intelligence and Data Mining 2 (4) : 426-446. ScholarBank@NUS Repository. <a href="https://doi.org/10.1504/IJBIDM.2007.016382" target="_blank">https://doi.org/10.1504/IJBIDM.2007.016382</a>
dc.identifier.issn17438187
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39397
dc.description.abstractIn this paper, we propose a new method, association rules mining for Named Entity Recognition (NER) and co-reference resolution. The method uses several morphological and lexical features such as Pronoun Class (PC) and Name Class (NC), String Similarity (SP) and Position (P) in the text, into a vector of attributes. Applied to a corpus of newspaper in the Indonesian language, the method outperforms state-of-the-art maximum entropy method in name entity recognition and is comparable with state-of-the-art machine learning methods, decision tree, for co-reference resolution. © 2007, Inderscience Publishers.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1504/IJBIDM.2007.016382
dc.sourceScopus
dc.subjectAssociation rules
dc.subjectCo-reference resolution
dc.subjectEntity equivalence
dc.subjectNamed Entity Recognition
dc.subjectNER
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1504/IJBIDM.2007.016382
dc.description.sourcetitleInternational Journal of Business Intelligence and Data Mining
dc.description.volume2
dc.description.issue4
dc.description.page426-446
dc.identifier.isiutNOT_IN_WOS
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