Study on assistant concept acquisition in domain ontology construction for Chinese texts

Author

Zhang, Guiping ; Zhang, Xiaoying ; Wang, Peiyan ; Cai, Dongfeng

Author_Institution

Knowledge Eng. Res. Center, Shenyang Aerosp. Univ., Shenyang, China

fYear

2011

fDate

27-29 Nov. 2011

Firstpage

177

Lastpage

182

Abstract

Concept acquisition is an important part of domain ontology construction, and how to accomplish assistant concept acquisition becomes a research focus. In this paper, a character-based CRF model is adopted to obtain the set of candidate terms, and we propose an active learning algorithm to select a concept from the set of candidate terms for the user and use the stochastic gradient descent algorithm for training the weight of concepts. The experiment results show that this algorithm can effectively assist user acquire domain concepts, when the set of correct terms identified by the CRF model is used as candidate concepts, the value of MAP reaches 0.9335.

Keywords

gradient methods; learning (artificial intelligence); natural languages; ontologies (artificial intelligence); stochastic processes; text analysis; Chinese texts; active learning algorithm; assistant concept acquisition; candidate terms; character-based CRF model; concept weight training; domain ontology construction; stochastic gradient descent algorithm; Educational institutions; Feature extraction; Hafnium; Manuals; Ontologies; CRF model; active learning algorithm; concept acquisition; domain ontology;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on

Conference_Location

Tokushima

Print_ISBN

978-1-61284-729-0

Type

conf

DOI

10.1109/NLPKE.2011.6138190

Filename

6138190