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A New Similarity Measure for Automatic Construction of the Unknown Word Lexical Dictionary

机译:自动构建未知词词汇词典的新相似性度量

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This article deals with research that automatically constructs a lexical dictionary of unknown words. The lexical dictionary has been usefully applied to various fields for semantic information processing. It has limitations in which it only processes terms defined in the dictionary. Under this circumstance, the concept of 揢nknown Word (UW)?is defined. UW, in this research, is considered a word not defined in WordNet. Here is where a new method to construct UW lexical dictionary through inputting various document collections scattered on the web is proposed. We grasp related terms of UW and measure semantic relatedness (similarity) between an UW and a related term(s). The relatedness is obtained by calculating both probabilistic relationship and semantic relationship. This research can extend UW lexical dictionary with an abundant number of UW. It is also possible to prepare a foundation for semantic retrieval by simultaneously using the UW lexical dictionary and WordNet.
机译:本文涉及自动构建未知单词的词汇词典的研究。词汇词典已经有用地应用于语义信息处理的各个领域。它有局限性,只能处理字典中定义的术语。在这种情况下,定义了“已知单词(UW)”的概念。在这项研究中,UW被认为是WordNet中未定义的单词。这里提出了一种通过输入分散在网络上的各种文档集合来构造UW词典的新方法。我们掌握UW的相关术语,并测量UW与相关术语之间的语义相关性(相似性)。通过计算概率关系和语义关系来获得相关性。该研究可以用大量的UW扩展UW词汇词典。通过同时使用UW词汇词典和WordNet,也可以为语义检索奠定基础。

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