Automatic Extending HowNet's Attribute Lexicon on the Web

Jinglei Zhao, Hui Liu, R. Lu
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引用次数: 0

Abstract

It is well known that lexical knowledge sources as WordNet, HowNet are very important to natural language processing applications in artificial intelligence. This paper proposes a new Web-mining algorithm to automatically extend HowNetpsilas attribute set. Seeded by the original attribute set in HowNet, the algorithm uses a conjunctive lexical pattern plus a validation mechanism called PES (position exchanging search) to extend the lexicon iteratively on the Web. Also, a Web-based attribute classifier is constructed which behaves as a filter to control the level of false positives during each iteration. The algorithm is evaluated using both standard human judgements and HowNet based evaluation. Some experimental results about the performance of the method are provided.
在Web上自动扩展HowNet的属性词典
众所周知,WordNet、HowNet等词汇知识库对于自然语言处理在人工智能中的应用非常重要。本文提出了一种新的web挖掘算法来自动扩展HowNetpsilas属性集。该算法以HowNet中的原始属性集为种子,使用连词模式和称为PES(位置交换搜索)的验证机制在Web上迭代地扩展词典。此外,还构造了一个基于web的属性分类器,它的行为像过滤器一样,在每次迭代期间控制误报的级别。该算法使用标准的人类判断和基于HowNet的评估进行评估。给出了该方法性能的一些实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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