Academic literature on the topic 'Text Reuse Detection'

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Journal articles on the topic "Text Reuse Detection"

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Haryanto, Nathaniel Clarence, Lucia Dwi Krisnawati, and Antonius Rachmat Chrismanto. "Retrieval of source documents in a text reuse system." Jurnal Teknologi dan Sistem Komputer 8, no. 2 (2020): 140–49. http://dx.doi.org/10.14710/jtsiskom.8.2.2020.140-149.

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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
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Miller, Hadar, Tsvi Kuflik, and Moshe Lavee. "Text Alignment in the Service of Text Reuse Detection." Applied Sciences 15, no. 6 (2025): 3395. https://doi.org/10.3390/app15063395.

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This study introduces a novel approach to text alignment tailored for ancient languages, with a focus on Hebrew and Aramaic, aimed at enhancing text reuse detection. Unlike previous methods, our approach integrates multiple NLP components into a specialized comparison pipeline, which is then incorporated into the Smith–Waterman algorithm. This integration enables improved alignment accuracy, particularly for historical texts characterized by fluctuations, orthographic changes, transcription variations, and word transpositions. Our key contributions include (1) a refined distance function that
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Chekhovich, Yu V., and O. S. Belenkaya. "Methodology for the implementation and use of text reuse detection systems in secondary education." Informatics and education, no. 10 (December 24, 2021): 5–14. http://dx.doi.org/10.32517/0234-0453-2021-36-10-5-14.

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The article analyses the situation with the lack of systematic control over the originality of texts of students’ written works in secondary schools, including individual projects, provided by the Russian Federal State Educational Standards. The authors point out that compliance with the academic program’s requirements to observe the norms and rules of citation and absence of plagiarism in the texts of individual projects is not ensured in practice in any way. In particular, schools have not developed evaluation criteria and procedures for monitoring. Also, there is no access to the necessary
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Jēkabsons, Gints. "Evaluation of Fingerprint Selection Algorithms for Local Text Reuse Detection." Applied Computer Systems 25, no. 1 (2020): 11–18. http://dx.doi.org/10.2478/acss-2020-0002.

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AbstractDetection of local text reuse is central to a variety of applications, including plagiarism detection, origin detection, and information flow analysis. This paper evaluates and compares effectiveness of fingerprint selection algorithms for the source retrieval stage of local text reuse detection. In total, six algorithms are compared – Every p-th, 0 mod p, Winnowing, Hailstorm, Frequency-biased Winnowing (FBW), as well as the proposed modified version of FBW (MFBW).Most of the previously published studies in local text reuse detection are based on datasets having either artificially ge
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Noreen, Ayesha, Iqra Muneer, and Rao Muhammad Adeel Nawab. "Mono-lingual text reuse detection for the Urdu language at lexical level." Engineering Applications of Artificial Intelligence 136 (October 2024): 109003. http://dx.doi.org/10.1016/j.engappai.2024.109003.

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Muneer, Iqra, and Rao Muhammad Adeel Nawab. "Cross-lingual Text Reuse Detection Using Translation Plus Monolingual Analysis for English-Urdu Language Pair." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 2 (2022): 1–18. http://dx.doi.org/10.1145/3473331.

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Cross-Lingual Text Reuse Detection (CLTRD) has recently attracted the attention of the research community due to a large amount of digital text readily available for reuse in multiple languages through online digital repositories. In addition, efficient machine translation systems are freely and readily available to translate text from one language into another, which makes it quite easy to reuse text across languages, and consequently difficult to detect it. In the literature, the most prominent and widely used approach for CLTRD is Translation plus Monolingual Analysis (T+MA). To detect CLTR
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Muneer, Iqra, and Rao Muhammad Adeel Nawab. "Cross-Lingual Text Reuse Detection at sentence level for English–Urdu language pair." Computer Speech & Language 75 (September 2022): 101381. http://dx.doi.org/10.1016/j.csl.2022.101381.

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Safin, Kamil Fanisovich, and Yury Victorovich Chehovich. "Combined method for plagiarism detection in text documents." Proceedings of the Institute for System Programming of the RAS 34, no. 1 (2022): 151–60. http://dx.doi.org/10.15514/ispras-2022-34(1)-11.

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There are two global approaches to the problem of searching plagiarism in the text: external and intrinsic search. The first approach implies search through an external collection of documents that could have been used for text reuse. The second approach, on the contrary, does not use any external data, but analyzes the text by itself. It is proposed to combine these two approaches to speed up the search for text plagiarism. With a large flow of documents that need to be checked, the outer corpus search system processes each document and finds plagiarised blocks in each document, if there are
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BABASAHEB, WAGHMODE. "WEB AUTHENTICATION PASSWORD DETECTION OF NETWORK SECURITY ATTACK USING S-PASS." IJIERT - International Journal of Innovations in Engineering Research and Technology 4, no. 2 (2017): 42–48. https://doi.org/10.5281/zenodo.1462261.

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<strong><strong>&nbsp;</strong>In Today�s digital world all information and data is kept safe by passwords. The simple and convenient format of password is in the form of text. But,text passwords are not always strong enough and under different vulnerabilities they are very easily stolen and changed. When a person creates a weak password or same password is reused in many sites it may be possible that others can acquire that password. If one password is stolen,then it is possible that it can be used for all the websites. This phenomenon is known as the Domino Effect. Other possible risky attac
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Dai, Liqin, and ChunHua Chen. "Intelligent Detection Method of English Text in Natural Scenes in Video." Scientific Programming 2021 (November 23, 2021): 1–10. http://dx.doi.org/10.1155/2021/6239112.

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With the rapid development of Internet technology, breakthroughs have been made in all branches of computer vision. Especially in image detection and target tracking, deep learning techniques such as convolutional neural networks have achieved excellent results. In order to explore the applicability of machine learning technology in the field of video text recognition and extraction, a YOLOv3 network based on multiscale feature transformation and migration fusion is proposed to improve the accuracy of english text detection in natural scenes in video. Firstly, aiming at the problem of multisca
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Dissertations / Theses on the topic "Text Reuse Detection"

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Nawab, Rao Muhammad Adeel. "Mono-lingual paraphrased text reuse and plagiarism detection." Thesis, University of Sheffield, 2012. http://etheses.whiterose.ac.uk/2785/.

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Book chapters on the topic "Text Reuse Detection"

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Hagen, Matthias, and Benno Stein. "Candidate Document Retrieval for Web-Scale Text Reuse Detection." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24583-1_35.

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Kothwal, Rambhoopal, and Vasudeva Varma. "Cross Lingual Text Reuse Detection Based on Keyphrase Extraction and Similarity Measures." In Multilingual Information Access in South Asian Languages. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40087-2_7.

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Colavizza, Giovanni, Mario Infelise, and Frédéric Kaplan. "Mapping the Early Modern News Flow: An Enquiry by Robust Text Reuse Detection." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15168-7_31.

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Sánchez-Vega, Fernando, Luis Villaseñor-Pineda, Manuel Montes-y-Gómez, and Paolo Rosso. "Towards Document Plagiarism Detection Based on the Relevance and Fragmentation of the Reused Text." In Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16761-4_3.

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Suchecka, Karolina, and Nathalie Gasiglia. "On Digital Comparative Editions and Textual Similarity Detection Tools: Towards a Hypertextual Cartography of a Rewritten Myth." In Tackling the Toolkit: Plotting Poetry through Computational Literary Studies. Institute of Czech Literature of the Czech Academy of Sciences, 2022. http://dx.doi.org/10.51305/icl.cz.9788076580336.11.

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Our project aims to expose the intertextual relationships observable within a heterogeneous literary corpus. For this purpose, we examine the output of two text reuse detection tools, Tracer and TextPAIR. We suggest some solutions to overcome the specific limitations observed in those tools and to enhance data quality. We believe that automatic analysis of the rewriting process can make it more comprehensible if the analysis is combined with empirical research methods adapted to the corpus in question.
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Gaspar, Sandra Ávila, Rayssa de Macedo Rebelo, Alexandre dos Santos Pyrrho, Simone da Silva, Marcia Cristina Braga Nunes Varricchio, and Paulo Sérgio Torres Brioso. "Potential plastic digestor of Euphorbia Tirucalli." In Engineering and its advancements. Seven Editora, 2024. http://dx.doi.org/10.56238/sevened2024.004-018.

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Natural products that cause oxidative stress and even local corrosion are of interest as degrading products of materials persistent in nature, such as plastic. This chapter evaluated the corrosive and shrinkage physicochemical action of total aqueous extracts of Euphorbia tirucalli, a species described as corrosive and shrinkage, from specimens with geographic variations (mangrove and mountains of Rio de Janeiro and the north coast of São Paulo) also subjected to temperature variations, on polypropylene (PP-5). This plastic is used on a daily basis and can be subjected to reuse processes. In t
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Conference papers on the topic "Text Reuse Detection"

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Boonchieng, Ekkarat, Wanchaloem Nadda, Wongthawat Liawrungrueang, and Waraporn Boonchieng. "Enhancing Disease Symptom Analysis in Thai Text: Methods for Text Oversampling in Imbalanced Data for Disease Detection." In 2024 IEEE International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2024. http://dx.doi.org/10.1109/iri62200.2024.00068.

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Seo, Jangwon, and W. Bruce Croft. "Local text reuse detection." In the 31st annual international ACM SIGIR conference. ACM Press, 2008. http://dx.doi.org/10.1145/1390334.1390432.

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"Significant Word-based Text Alignment for Text Reuse Detection." In Jan. 31-Feb. 1, 2017 Bali (Indonesia). EIRAI, 2017. http://dx.doi.org/10.17758/eirai.f0217102.

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Hagen, Matthias, Martin Potthast, Payam Adineh, Ehsan Fatehifar, and Benno Stein. "Source Retrieval for Web-Scale Text Reuse Detection." In CIKM '17: ACM Conference on Information and Knowledge Management. ACM, 2017. http://dx.doi.org/10.1145/3132847.3133097.

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Saki, Misam, Heshaam Faili, and Masoud Asadpour. "Text reuse detection by keyword extraction for telegram channels." In 2017 Iranian Conference on Electrical Engineering (ICEE). IEEE, 2017. http://dx.doi.org/10.1109/iraniancee.2017.7985277.

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Lulu, Leena, Boumediene Belkhouche, and Saad Harous. "Overview of fingerprinting methods for local text reuse detection." In 2016 12th International Conference on Innovations in Information Technology (IIT). IEEE, 2016. http://dx.doi.org/10.1109/innovations.2016.7880050.

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Manjavacas, Enrique, Brian Long, and Mike Kestemont. "On the Feasibility of Automated Detection of Allusive Text Reuse." In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-2514.

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Liu, Yang, Jun Liu, Siqi Sun, and Zhuang Du. "Medical Image Text Area Detection Based on Feature Reuse Convolutional Neural Network." In the 2019 International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3366715.3366738.

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Lulu, Leena, Boumediene Belkhouche, and Saad Harous. "Candidate document retrieval for Arabic-based text reuse detection on the web." In 2016 12th International Conference on Innovations in Information Technology (IIT). IEEE, 2016. http://dx.doi.org/10.1109/innovations.2016.7880048.

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Barrón-Cedeño, Alberto. "On the mono- and cross-language detection of text reuse and plagiarism." In Proceeding of the 33rd international ACM SIGIR conference. ACM Press, 2010. http://dx.doi.org/10.1145/1835449.1835687.

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