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

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...

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Bibliographic Details
Main Authors: Guiping Zhang, Xiaoying Zhang, Peiyan Wang, Dongfeng Cai
Format: Conference Proceeding
Language:English
Subjects:
active learning algorithm
concept acquisition
CRF model
domain ontology
Educational institutions
Feature extraction
Hafnium
Manuals
Ontologies
Online Access:Request full text
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Summary: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.
DOI:10.1109/NLPKE.2011.6138190