Report
Plagiarism: Report
| Title: | Plagiarism: Report |
|---|---|
| Authors: | Lamar-Leon, Javier, Quaresma, Paulo, Nogueira, Vitor |
| Publication Year: | 2024 |
| Collection: | Repositório Científico da Universidade de Évora |
| Subject Terms: | Plagiarism detection |
| Description: | Plagiarism detection is essential for maintaining academic integrity, ensuring that scholarly works are original and properly cited. With the rise of online resources and AI writing tools, the risk of plagiarism has increased, making detection crucial in the academic process. Detection methods can be monolingual or cross-lingual and are classified as intrinsic or extrinsic, utilizing various techniques such as N-gram-based, vector-based, and semantic-based methods. The expansion of the internet and new detection tools like large language models have intensified the need for effective plagiarism detection. Academic institutions rely on these tools to ensure the originality of submissions, preserving the credibility of academic work. |
| Document Type: | report |
| Language: | Portuguese |
| Relation: | https://hdl.handle.net/10174/38636; jlamarleon@gmail.com; pq@uevora.pt; vbn@uevora.pt |
| Availability: | https://hdl.handle.net/10174/38636 |
| Rights: | openAccess |
| Accession Number: | edsbas.1174DD61 |
| Database: | BASE |
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