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A Novel Approach for Searching Linguistic Synonyms through Parts of Speech Tagging

机译:一种通过词性标注搜索语言同义词的新方法

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Synonym-based searching is considered to be a complicated problem, as text mining from unstructured data of web is challenging. Finding useful information which matches user need from the bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. To realize this technique, pattern generation is taken into consideration with the help of Parts-of-Speech tagging and Web Scrapping. Two approaches were built i.e. Non-Context Based Searching and Context-Based Searching while the latter technique proved to be a more efficient in dealing with intent-based linguistic semantics than the former one. The paper concludes with recommendations and future work by giving a new direction to natural language.
机译:基于同义词的搜索被认为是一个复杂的问题,因为从Web的非结构化数据中挖掘文本具有挑战性。从大量网页中找到符合用户需求的有用信息是一项繁琐的任务。为了解决这个问题,本文提出了一种新颖实用的同义词检索技术。为了替换语义,要考虑用户意图来实现该技术。为了实现该技术,借助于词性标记和Web剪贴,考虑了模式生成。建立了两种方法,即基于非上下文的搜索和基于上下文的搜索,而后一种技术被证明在处理基于意图的语言语义上比前一种更为有效。本文通过给出自然语言的新方向,提出了建议和未来的工作。

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