摘要
提出一种基于句子相似度的论文抄袭检测模型。利用局部词频指纹算法对大规模文档进行快速检测,找出疑似抄袭文档。根据最长有序公共子序列算法计算句子间的相似度,并标注抄袭细节,给出抄袭依据。在标准中文数据集SOGOU-T上进行的实验表明,该模型具有较强的局部信息挖掘能力,在一定程度上克服了现有的论文抄袭检测算法精度不高的缺点。
A new model for plagiarism-identification of scientific papers based on sentence similarity is presented.Large-scale texts are quickly detected with Local Word-Frequency Fingerprin（tLWFF） to find suspected plagiarism ones.Sentence similari-ty is computed according to the Longest Sorted Common Subsequence（LSCS） between source texts and destination texts.The algorithm can mark plagiarism details,and show evidence.The identification experiments on the SOGOU-T database are done with this model.The results show it has higher information mining capacity,and partly overcomes the shortage of low-er precision on existing plagiarism-identification of scientific papers.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第24期199-201,共3页
Computer Engineering and Applications
基金
国家自然科学基金(No.60603023)
辽宁省教育厅重点实验室项目(No.LS2010180)~~
关键词
句子相似度
抄袭检测
局部词频
最长有序公共子序列
sentence similarity
plagiarism-detection
local word-frequency
Longest Sorted Common Subsequence（LSCS）
