Translated or cross-lingual plagiarism is defined as the translation of someone else’s work or words without marking it as such or without giving credit to the original author. The existence of cross-lingual plagiarism is not new, but only in recent years, due to the rapid development of the natural language processing, appeared the first algorithms which tackled the difficult task of detecting it. Most of these algorithms utilize machine translation to compare texts written in different languages. We propose a different method, which can effectively detect translations between language-pairs where machine translations still produce low quality results. Our new algorithm presented in this paper is based on information retrieval (IR) and a dictionary based similarity metric. The preprocessing of the candidate documents for the IR is computationally intensive, but easily parallelizable. We propose a desktop Grid solution for this task. As the application is time sensitive and the desktop Grid peers are unreliable, a resubmission mechanism is used which assures that all jobs of a batch finish within a reasonable time period without dramatically increasing the load on the whole system.
