Plagiarism Detection in Medical Research Using Medical Ontology


Abstract in English

This paper presents a reference study of available algorithms for plagiarism detection and it develops semantic plagiarism detection algorithm for plagiarism detection in medical research papers by employing the Medical Ontologies available on the World Wide Web. The issue of plagiarism detection in medical research written in natural languages is a complex issue and related exact domain of medical research. There are many used algorithms for plagiarism detection in natural language, which are generally divided into two main categories, the first one is comparison algorithms between files by using fingerprints of files, and files content comparison algorithms, which include strings matching algorithms and text and tree matching algorithms. Recently a lot of research in the field of semantic plagiarism detection algorithms and semantic plagiarism detection algorithms were developed basing of citation analysis models in scientific research. In this research a system for plagiarism detection was developed using “Bing” search engine, where tow type of ontologies used in this system, public ontology as wordNet and many standard international ontologies in medical domain as Diseases ontology which contains a descriptions about diseases and definitions of it and the derivation between diseases.

References used

Vinod K.R.،Sandhya.S،Sathish Kumar D،Harani A،David Banji and،Otilia JF Banji 2011 ، Plagiarism history ،detection and prevention, Hygeia, Vol.3-Issue.1-Page 1- 4
Maxim mozgovoy, enhancing computer-aided plagiarism , university of joensuu computer science and statistics dissertations 18
Schleimer, S., Wilkerson, D. S., & Aiken, A. (2003). Winnowing: Local Algorithms for Document Fingerprinting. Proceedings of the 2003 ACM SIGMOD International Conference on on Management of Data - SIGMOD ’03, 76–85

Download