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    <titleInfo>
        <title>Chinese Hypernym-Hyponym Extraction from User Generated Categories</title>
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    <name type="personal">
        <namePart type="given">Chengyu</namePart>
        <namePart type="family">Wang</namePart>
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        <namePart type="given">Xiaofeng</namePart>
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        <dateIssued>2016-12</dateIssued>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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    <abstract>Hypernym-hyponym (“is-a”) relations are key components in taxonomies, object hierarchies and knowledge graphs. While there is abundant research on is-a relation extraction in English, it still remains a challenge to identify such relations from Chinese knowledge sources accurately due to the flexibility of language expression. In this paper, we introduce a weakly supervised framework to extract Chinese is-a relations from user generated categories. It employs piecewise linear projection models trained on a Chinese taxonomy and an iterative learning algorithm to update models incrementally. A pattern-based relation selection method is proposed to prevent “semantic drift” in the learning process using bi-criteria optimization. Experimental results illustrate that the proposed approach outperforms state-of-the-art methods.</abstract>
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        <url>https://aclanthology.org/C16-1128</url>
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        <date>2016-12</date>
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%0 Conference Proceedings
%T Chinese Hypernym-Hyponym Extraction from User Generated Categories
%A Wang, Chengyu
%A He, Xiaofeng
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F wang-he-2016-chinese
%X Hypernym-hyponym (“is-a”) relations are key components in taxonomies, object hierarchies and knowledge graphs. While there is abundant research on is-a relation extraction in English, it still remains a challenge to identify such relations from Chinese knowledge sources accurately due to the flexibility of language expression. In this paper, we introduce a weakly supervised framework to extract Chinese is-a relations from user generated categories. It employs piecewise linear projection models trained on a Chinese taxonomy and an iterative learning algorithm to update models incrementally. A pattern-based relation selection method is proposed to prevent “semantic drift” in the learning process using bi-criteria optimization. Experimental results illustrate that the proposed approach outperforms state-of-the-art methods.
%U https://aclanthology.org/C16-1128
%P 1350-1361

Markdown (Informal)

[Chinese Hypernym-Hyponym Extraction from User Generated Categories](https://aclanthology.org/C16-1128) (Wang & He, COLING 2016)

• Chinese Hypernym-Hyponym Extraction from User Generated Categories (Wang & He, COLING 2016)

ACL

• Chengyu Wang and Xiaofeng He. 2016. Chinese Hypernym-Hyponym Extraction from User Generated Categories. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1350–1361, Osaka, Japan. The COLING 2016 Organizing Committee.