Retrieval of source documents in a text reuse system

Nathaniel Clarence Haryanto, Lucia D. Krisnawati, Antonius Rachmat Chrismanto
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引用次数: 0

Abstract

The architecture of the text-reuse detection system consists of three main modules, i.e., source retrieval, text analysis, and knowledge-based postprocessing. Each module plays an important role in the accuracy rate of the detection outputs. Therefore, this research focuses on developing the source retrieval system in cases where the source documents have been obfuscated in different levels. Two steps of term weighting were applied to get such documents. The first was the local-word weighting, which has been applied to the test or reused documents to select query per text segments. The tf-idf term weighting was applied for indexing all documents in the corpus and as the basis for computing cosine similarity between the queries per segment and the documents in the corpus. A two-step filtering technique was applied to get the source document candidates. Using artificial cases of text reuse testing, the system achieves the same rates of precision and recall that are 0.967, while the recall rate for the simulated cases of reused text is 0.66.
文本再利用系统中的源文件检索
文本重复使用检测系统的架构由三个主要模块组成,即来源检索、文本分析和基于知识的后处理。每个模块都对检测结果的准确率起着重要作用。因此,本研究主要针对源文件被不同程度混淆的情况开发源检索系统。为了获取这类文档,我们采用了两个术语加权步骤。首先是本地词加权,它被应用于测试或重用文档,以选择每个文本片段的查询。tf-idf术语加权用于为语料库中的所有文档编制索引,并作为计算每段查询与语料库中文档之间余弦相似度的基础。采用两步过滤技术获得候选源文档。使用人工文本重用测试案例,该系统的精确率和召回率均为 0.967,而模拟文本重用案例的召回率为 0.66。
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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