Higashiyama, Shohei and Mathieu, Blondel and Seki, Kazuhiro and Uehara, Kuniaki (2015) Cost-sensitive structured perceptron incorporating category hierarchy for named entity recognition. Journal of Information and Communication Technology, 14. pp. 1-20. ISSN 2180-3862

Full text not available from this repository. (Request a copy)

Abstract

Named Entity Recognition (NER) is a fundamental natural language processing task for the identification and classification of expressions into predefined categories, such as person and organization.Existing NER systems usually target about 10 categories and do not incorporate analysis of category relations.However, categories often belong naturally to some predefined hierarchy.In such cases, the distance between categories in the hierarchy becomes a rich source of information that can be exploited.This is intuitively useful particularly when the categories are numerous.On that account, this paper proposes an NER approach that can leverage category hierarchy information by introducing, in the structured perceptron framework, a cost function more strongly penalizing category predictions that are more distant from the correct category in the hierarchy.Experimental results on the GENIA biomedical text corpus indicate the effectiveness of the proposed approach as compared with the case where no cost function is utilized. In addition, the proposed approach demonstrates the superior performance over a representative work using multi-class support vector machines on the same corpus.A possible direction to further improve the proposed approach is to investigate more elaborate cost functions than a simple additive cost adopted in this work.

Item Type:	Article
Uncontrolled Keywords:	Named entity recognition, category hierarchy, cost-sensitive learning, biomedical text mining.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	29 Apr 2018 01:43
Last Modified:	29 Apr 2018 01:43
URI:	https://repo.uum.edu.my/id/eprint/24079

Actions (login required)

View Item