Classifying and Ranking Search Engine Results as Potential Sources of Plagiarism

Source retrieval for plagiarism detection involves using a search engine to retrieve candidate sources of plagiarism for a given suspicious document so that more accurate com-parisons can be made. An important consideration is that only documents that are likely to be sources of plagiarism should be retrieved so as to minimize the number of unneces-sary comparisons made. A supervised strategy for source re-trieval is described whereby search results are classified and ranked as potential sources of plagiarism without retrieving the search result documents and using only the information available at search time. The performance of the supervised method is compared to a baseline method and shown to im-prove precision by up to 3.28%, recall by up to 2.6 % and the F1 score by up to 3.37%. Furthermore, features are an-alyzed to determine which of them are most important for search result classification with features based on document and search result similarity appearing to be the most impor-tant