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|Title:||Application of association rules mining to Named Entity Recognition and co-reference resolution for the Indonesian language||Authors:||Budi, I.
Named Entity Recognition
|Issue Date:||2007||Citation:||Budi, 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. https://doi.org/10.1504/IJBIDM.2007.016382||Abstract:||In 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.||Source Title:||International Journal of Business Intelligence and Data Mining||URI:||http://scholarbank.nus.edu.sg/handle/10635/39397||ISSN:||17438187||DOI:||10.1504/IJBIDM.2007.016382|
|Appears in Collections:||Staff Publications|
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