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Published Paper Details:
Paper Title
A Hybrid, Multi-Stage Approach for Advanced Plagiarism Detection
Authors
Suhani Goyal, Saksham, Saurabh
Keywords
Plagiarism detection, hybrid model, multi-stage architecture, document fingerprinting, Winnowing algorithm, k-gram hashing, hash-based screening, suffix automaton, exact string matching, syntactic similarity, structural reorganization detection, semantic similarity, deep learning, Attention-based Bi-LSTM, neural attention mechanism, text embeddings, paraphrasing detection, contextual analysis, source code similarity, natural language processing, precision, recall, F1-score, semantic plagiarism d
Abstract
Plagiarism detection is a critical task in academic and professional settings. Traditional methods often struggle to identify sophisticated forms of plagiarism, such as paraphrasing and structural reorganization. This paper proposes a novel, multi-stage architecture for an improved and advanced plagiarism checker. Our hybrid model integrates three distinct techniques: (1) an efficient, hash-based document fingerprinting algorithm for initial large-scale screening, (2. a precise string-matching algorithm for detailed syntactic analysis, and (3) a deep learning model with an attention mechanism for capturing semantic similarities. By combining these methods, the proposed system aims to achieve high accuracy and efficiency, effectively identifying a wide spectrum of plagiarism, from literal copying to semantic paraphrasing.
IJCRT's Publication Details
Unique Identification Number - IJCRT2511962
Paper ID - 297650
Page Number(s) - i144-i151
Pubished in - Volume 13 | Issue 11 | November 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Suhani Goyal, Saksham, Saurabh, "A Hybrid, Multi-Stage Approach for Advanced Plagiarism Detection", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 11, pp.i144-i151, November 2025, Available at :http://www.ijcrt.org/papers/IJCRT2511962.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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