期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：9
DOI：10.14569/IJACSA.2018.090960
出版社：Science and Information Society (SAI)
摘要：Named Entity Recognition (NER) is one of the tasks in the information extraction. NER is used for extracting and classifying words or entities that belong to the proper noun category in text data such as person's name, location, organization, date and others. As seen in today's generation, social media such as web pages, blogs, Facebook, Twitter, Instagram and online newspapers are among the major contributors to the generation of information. This paper presents an enhanced Malay Named Entity Recognition model using combination fuzzy c-means and K-Nearest Neighbours Algorithm method for crime analysis. The results showed that this combination method could improve the accuracy performance on entity recognition of crime data in Malay. The model is expected to provide a better method in the process of recognizing named entities for text analysis particularly in Malay.
关键词：Named entity recognition; information extraction; fuzzy c-means; k-nearest neighbors; malay language; crime data
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