The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection
Abstract
In the last decade, the plagiarism phenomenon has widely spread and become a topical problem in the modern scientific world, caused by the wide availability of electronic documents online and offline. This work will be devoted to describe a new plagiarism detection system named AOGK « Agents Oriented Genetic-K-means » based on a multi-agents architecture composed of three modules: text parsing to transform documents into vectors; Learning module using genetic algorithms to build a prediction model; Test module using k-means for the final classification of suspicious document; To evaluate their system the authors have used a range of reference metrics (precision, recall, f-measure and entropy) and the benchmark PAN 09. They have compared the results obtained with the performance of other systems found in literature; the authors' aim is the preservation of copyright.
Related Content
Tutita M. Casa, Fabiana Cardetti, Madelyn W. Colonnese.
© 2024.
14 pages.
|
R. Alex Smith, Madeline Day Price, Tessa L. Arsenault, Sarah R. Powell, Erin Smith, Michael Hebert.
© 2024.
19 pages.
|
Marta T. Magiera, Mohammad Al-younes.
© 2024.
27 pages.
|
Christopher Dennis Nazelli, S. Asli Özgün-Koca, Deborah Zopf.
© 2024.
31 pages.
|
Ethan P. Smith.
© 2024.
22 pages.
|
James P. Bywater, Sarah Lilly, Jennifer L. Chiu.
© 2024.
20 pages.
|
Ian Jones, Jodie Hunter.
© 2024.
20 pages.
|
|
|