Hyponymy verification of ontology concepts based on feature vectors

Xiaodan Tian; Qinglin Wang; Yuan Li

Hyponymy verification of ontology concepts based on feature vectors

Xiaodan Tian
, Qinglin Wang
, Yuan Li^*

^*此作品的通讯作者

自动化学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

2 引用（Scopus）

摘要

A new method based on feature vectors of semantic and context features to verify whether a pair of concepts has the hyponymy relation was represented. Based on word formation, the co-occurrence of concepts, the number of feature words and the location of concepts, feature vectors of hyponymy were built. Support vector machines (SVM) were used to train and predict data, and the relation extraction of ontology concepts was finally achieved.

源语言	英语
页（从-至）	351-354
页数	4
期刊	Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)
卷	44
期	SUPPL.2
出版状态	已出版 - 2013

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引用此

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title = "Hyponymy verification of ontology concepts based on feature vectors",

abstract = "A new method based on feature vectors of semantic and context features to verify whether a pair of concepts has the hyponymy relation was represented. Based on word formation, the co-occurrence of concepts, the number of feature words and the location of concepts, feature vectors of hyponymy were built. Support vector machines (SVM) were used to train and predict data, and the relation extraction of ontology concepts was finally achieved.",

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T1 - Hyponymy verification of ontology concepts based on feature vectors

AU - Tian, Xiaodan

AU - Wang, Qinglin

AU - Li, Yuan

PY - 2013

Y1 - 2013

N2 - A new method based on feature vectors of semantic and context features to verify whether a pair of concepts has the hyponymy relation was represented. Based on word formation, the co-occurrence of concepts, the number of feature words and the location of concepts, feature vectors of hyponymy were built. Support vector machines (SVM) were used to train and predict data, and the relation extraction of ontology concepts was finally achieved.

AB - A new method based on feature vectors of semantic and context features to verify whether a pair of concepts has the hyponymy relation was represented. Based on word formation, the co-occurrence of concepts, the number of feature words and the location of concepts, feature vectors of hyponymy were built. Support vector machines (SVM) were used to train and predict data, and the relation extraction of ontology concepts was finally achieved.

KW - Feature vector

KW - Hyponymy

KW - Ontology learning

KW - SVM

UR - https://www.scopus.com/pages/publications/84886298840

M3 - Article

AN - SCOPUS:84886298840

SN - 1672-7207

VL - 44

SP - 351

EP - 354

JO - Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)

JF - Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)

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Hyponymy verification of ontology concepts based on feature vectors

摘要

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