Supervised ranking for plagiarism Source retrieval: Notebook for PAN at CLEF 2013

Kyle Williams, Hung Hsuan Chen, C. Lee Giles

Research output: Contribution to journalConference article

5 Scopus citations

Abstract

Source retrieval involves making use of a search engine to retrieve candidate sources of plagiarism for a given suspicious document so that more accurate comparisons can be made. We describe a strategy for source retrieval that uses a supervised method to classify and rank search engine results as potential sources of plagiarism without retrieving the documents themselves. Evaluation shows the performance of our approach, which achieved the highest precision (0.57) and F1 score (0.47) in the 2014 PAN Source Retrieval task.

Original languageEnglish (US)
Pages (from-to)1021-1026
Number of pages6
JournalCEUR Workshop Proceedings
Volume1180
StatePublished - Jan 1 2014
Event2014 Cross Language Evaluation Forum Conference, CLEF 2014 - Sheffield, United Kingdom
Duration: Sep 15 2014Sep 18 2014

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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