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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/98226


    Title: Unsupervised clustering of morphologically related Chinese words
    Authors: Lee, Chia-Ling;Chang, Ya-Ning;Liu, Chao-Lin;Lee, Chia-Ying;Hsu, Jane Yung-jen
    劉昭麟
    Contributors: 資科系
    Keywords: morphological awareness;human cognition;computational linguistics;Chinese character meaning
    Date: 2014-07
    Issue Date: 2016-06-22 16:21:48 (UTC+8)
    Abstract: Many linguists consider morphological awareness a major factor that affects children’s reading development. A Chinese character embedded in different compound words may carry related but different meanings. For example, “商店(store)”, “商品(commodity)”, “商代(Shang Dynasty)”, and “商朝(Shang Dynasty)” can form two clusters: {“商店”, “商品”} and {“商代”, “商朝”}. In this paper, we aim at unsupervised clustering of a given family of morphologically related Chinese words. Successfully differentiating these words can contribute to both computer assisted Chinese learning and natural language understanding. In Experiment 1, we employed linguistic factors at the word, syntactic, semantic, and contextual levels in aggregated computational linguistics methods to handle the clustering task. In Experiment 2, we recruited adults and children to perform the clustering task. Experimental results indicate that our computational model achieved the same level of performance as children.
    Relation: Proceedings of the Thirty-Sixth Annual Meeting of the Cognitive Science Society (COGSCI`14), 2543‒2548. Québec City, Québec, Canada, 23-26 July 2014
    Data Type: conference
    Appears in Collections:[Department of Computer Science ] Proceedings

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