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- W4254670069 abstract "In this article we present a new semantic and syntactic-based method for external plagiarism detection. In the proposed approach, latent dirichlet allocation (LDA) and parts of speech (POS) tags are used together to detect plagiarism between the sample and a number of source documents. The basic hypothesis is that considering semantic and syntactic information between two text documents may improve the performance of the plagiarism detection task. Our method is based on two steps, naming, which is a pre-processing where we detect the topics from the sentences in documents using the LDA and convert each sentence in POS tags array; then a post processing step where the suspicious cases are verified purely on the basis of semantic rules. For two types of external plagiarism (copy and random obfuscation), we empirically compare our approach to the state-of-the-art N-gram based and stop-word N-gram based methods and observe significant improvements." @default.
- W4254670069 created "2022-05-12" @default.
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- W4254670069 date "2019-01-01" @default.
- W4254670069 modified "2023-09-30" @default.
- W4254670069 title "Latent Dirichlet Allocation and POS Tags Based Method for External Plagiarism Detection" @default.
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- W4254670069 doi "https://doi.org/10.4018/978-1-5225-8057-7.ch015" @default.
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