Experiments on Document Chunking and Query Formation for Plagiarism Source Retrieval
نویسندگان
چکیده
This paper presents the details of the system we prepare as a participant of the PAN 2014 task on 'Source Retrieval: Uncovering Plagiarism, Authorship, and Social Software Misuse'. Our work is focused on intelligent chunking of suspicious documents and a hybrid approach of query formation. A method based on term frequency and word co-occurrence is proposed to extract query terms from a non-overlapping chunk of topically related sentences. The queries are then submitted to the ChatNoir search API to retrieve documents that are likely to be the sources of plagiarism. Finally a snippet matching and duplicate download restriction based filtering technique reduces the number of downloads. The evaluation results of the PAN14 Source Retrieval task show that the performance of our system is highly promising. The f-measure accuracy of the system is .3871 with a recall of .5083 which is the highest among all the participants.
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