NeoPlag: An Ecosystem to Support the Development and Evaluation of New Algorithms to Detect Plagiarism

Abstract

Nowadays the plagiarism constitutes a complex problem, due several factors as the incorrect use of new technologies to access and share the information, the different forms and areas where can be present plagiarism (texts, code, images, self-plagiarism, etc.) or the lack of respect to ideas and contributions of other persons. On those grounds, in this paper we present a novel ecosystem to provide support during the development process of new algorithms to detect plagiarism, test the existing algorithms or perform benchmarking analysis. This platform named "NeoPlag" provides a complete set of services that allow developers focusing in design of detection technique, without worrying by deployment issues as development of search services in internet, text extraction, semantic analysis of texts, configuration the citation styles, among several others. In order to analyze the usefulness of the proposed ecosystem, we have developed and uploaded into system a basic detection algorithm based on vector space model. With the developed algorithm we have carried out a benchmarking between our ecosystem and commercial tool (Viper). The achieved results by our proposal are encouraging and shown highest rates of plagiarism detection.