A predominant statistical approach to identify semantic similarity of textual documents

P. Vigneshvaran, E. Jayabalan, K. Vijaya
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引用次数: 2

Abstract

Semantic similarity is the processes of identifying similar words. It relates to computing the similarity between documents which are not lexicographically similar. This paper proposed an empirical method to estimate the semantic similarity using HBase. Specifically this paper defines various word co-occurrence in the document measured and its synonyms are also identified using WordNet. By using the statistical approaches such as MSE and MSD, similarity has been measured. This research focuses on evaluating the similarity between the key document and source documents in the document corpus. In this paper, the developed predominant tool using statistical approach has been tested by checking the similarity of the assignments submitted by the students to check the integrity of a student. This tool may also be used to identify Plagiarism of documents and to eliminate duplicates in a text repository.
识别文本文档语义相似度的主要统计方法
语义相似是识别相似词的过程。它涉及计算字典上不相似的文档之间的相似性。本文提出了一种基于HBase的语义相似度的经验估计方法。具体来说,本文定义了被测文档中的各种词共现现象,并利用WordNet对其同义词进行了识别。通过统计方法,如MSE和MSD,测量了相似性。本研究的重点是评估文档语料库中关键文档和源文档之间的相似度。在本文中,利用统计方法开发的主要工具通过检查学生提交的作业的相似性来检查学生的完整性来进行测试。此工具还可用于识别文档的抄袭,并消除文本存储库中的重复项。
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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