Approaches for Candidate Document Retrieval and Detailed Comparison of Plagiarism Detection.

Abstract

In this paper we report on our plagiarism detection system which is used to process the PAN plagiarism corpus for the tasks of Candidate Document Retrieval and Detailed Comparison. To retrieve the plagiarism candidate document by using ChatNoir API, a method based on tf*idf to extract the keywords of suspicious documents as queries is proposed. An Lucene ranking method is used for plagiarism candidate document reduction. And a detailed comparison algorithm to get the web pages that are actually sources for plagiarized passages is applied. To extract all plagiarism passages from the suspicious document and their corresponding source passages from the source document, a plagiarism detection method combined with semantic similarity and structure similarity is proposed. Semantic similarity is calculated by Vector Space Model while structure similarity is calculated by our own method. We use information retrieval to get candidate pairs of sentences from suspicious document and potential source document. A method which is called Bilateral Alternating Sorting is applied to merge pairs of sentences. Those plagiarism candidate result pairs are screened in post-processing.

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