Application of association rules mining to Named Entity Recognition and co-reference resolution for the Indonesian language

Indra Budi, Stéphane Bressan

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)426-446
Number of pages21
JournalInternational Journal of Business Intelligence and Data Mining
Volume2
Issue number4
DOIs
Publication statusPublished - Dec 2007

Keywords

  • Association rules
  • Co-reference resolution
  • Entity equivalence
  • NER
  • Named Entity Recognition

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