一种基于相关度排序模型的抄袭来源检索与文本对齐方法

Lei-lei Kong, Zicheng Zhao, Zhimao Lu, Haoliang Qi, Feng Zhao
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引用次数: 3

摘要

由于万维网上可获得的数字资源,文本剽窃问题日益严重。来源检索和文本比对是抄袭检测的两个核心任务。介绍了一种基于相关度排序模型的抄袭源检索与文本对齐系统。无论是源检索任务还是文本对齐任务都将其视为一个信息检索过程,并通过相关度排序来搜索抄袭源,获得候选抄袭种子。源检索采用BM25模型,文本对齐采用向量空间模型。在此基础上,开发了一个名为HawkEyes的抄袭检测系统,并给出了一些演示。
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A Method of Plagiarism Source Retrieval and Text Alignment Based on Relevance Ranking Model
The problem of text plagiarism has increased because of the digital resources available on the World Wide Web. Source Retrieval and Text Alignment are two core tasks of plagiarism detection. A plagiarism source retrieval and text alignment system based on relevance ranking model is described in this paper. Not only the source retrieval task but also the text alignment task is all regarded as a process of information retrieval, and the relevance ranking is used to search the plagiarism sources and obtain the candidate plagiarism seeds. For source retrieval, BM25 model is used, while for text alignment, Vector Space Model is exploited. Furthermore, a plagiarism detection system named HawkEyes is developed based on the proposed methods and some demonstrations of HawkEyes are given.
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