Semantic Similarity Search Model for Obfuscated Plagiarism Detection in Marathi Language using Fuzzy and Naïve Bayes Approaches
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 3
Abstract
Abstract: Plagiarism detection (PD) in natural language texts is an example of NLP applications that is linked with information retrieval (IR) and soft computing (SC) approaches. Obfuscated plagiarism cases contain invisible texts, which is difficult to find in existing plagiarism detection methods. In this paper fuzzy semanticbased similarity search model and Naïve Bayes model for uncovering obfuscated plagiarism for English and Marathi language are presented and compared with different state-of-the-art baselines (B1-W1G, B2- W3G, B3- W5G, B4-S2S). The fuzzy model identification is based on ‘If-then’ fuzzy rules. Semantic relatedness between words is studied based on the part-of-speech (POS) tags and WordNet-based similarity measures. Naïve Bayes classifier is used to achieve better detection performance. Results are assessed using precision, recall, Fmeasure and granularity for Fuzzy and Naïve approaches and it is observed that Naïve Bayes model gives more appropriate result than fuzzy semantic based model.
Authors and Affiliations
Ms. Nilam Shenoy , Mrs. M. A. Potey
Keywords
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