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CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring
Taxonomy is not only a fundamental form of knowledge representation, but...
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Is China Entering WTO or shijie maoyi zuzhi--a Corpus Study of English Acronyms in Chinese Newspapers
This is one of the first studies that quantitatively examine the usage o...
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Morpho-syntactic Lexicon Generation Using Graph-based Semi-supervised Learning
Morpho-syntactic lexicons provide information about the morphological an...
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Does the Web of Science Accurately Represent Chinese Scientific Performance?
The purpose of this study is to compare Web of Science (WoS) with a Chin...
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Towards Accurate Word Segmentation for Chinese Patents
A patent is a property right for an invention granted by the government ...
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Error Detection in a Large-Scale Lexical Taxonomy
Knowledge base (KB) is an important aspect in artificial intelligence. O...
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Learning to Mine Chinese Coordinate Terms Using the Web
Coordinate relation refers to the relation between instances of a concept and the relation between the directly hyponyms of a concept. In this paper, we focus on the task of extracting terms which are coordinate with a user given seed term in Chinese, and grouping the terms which belong to different concepts if the seed term has several meanings. We propose a semi-supervised method that integrates manually defined linguistic patterns and automatically learned semi-structural patterns to extract coordinate terms in Chinese from web search results. In addition, terms are grouped into different concepts based on their co-occurring terms and contexts. We further calculate the saliency scores of extracted terms and rank them accordingly. Experimental results demonstrate that our proposed method generates results with high quality and wide coverage.
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