Benchmarking Mi-NER: Malay Entity Recognition Engine

Benchmarking Mi-NER: Malay Entity Recognition Engine

150 150 MIMOS Berhad

Authors:

Thenmalar Ulanganathan, Ali Ebrahimi, Benjamin Chu Min Xian, Khalil Bouzekri, Rohana Mahmud and Ong Hong Hoe

 

Abstract:

Named entity recognition (NER) is a process of recognizing, identifying, and extracting useful entities, like person, location and organization for information mining from unstructured texts. This paper presents (Mi-NER), a Malay
language Named Entity Recognition engine that is developed using a probabilistic approach. The results of benchmarking Mi-NER against existing systems are presented in this paper. In addition, the details of the experimental work are highlighted and discussed. Precision, Recall and F-Measure have been used to measure the results for this evaluation.

 

Source:

The Ninth International Conference on Information, Process and Knowledge Management (eKNOW 2017), France, March 19 – 23, 2017

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