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

Kyle Williams; Hung Hsuan Chen; C. Lee Giles

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

Kyle Williams, Hung Hsuan Chen, C. Lee Giles

Research output: Contribution to journal › Conference article › peer-review

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 language	English (US)
Pages (from-to)	1021-1026
Number of pages	6
Journal	CEUR Workshop Proceedings
Volume	1180
State	Published - 2014
Event	2014 Cross Language Evaluation Forum Conference, CLEF 2014 - Sheffield, United Kingdom Duration: Sep 15 2014 → Sep 18 2014

All Science Journal Classification (ASJC) codes

General Computer Science

Cite this

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title = "Supervised ranking for plagiarism Source retrieval: Notebook for PAN at CLEF 2013",

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.",

author = "Kyle Williams and Chen, {Hung Hsuan} and Giles, {C. Lee}",

year = "2014",

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AU - Chen, Hung Hsuan

AU - Giles, C. Lee

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Y1 - 2014

N2 - 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.

AB - 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.

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AN - SCOPUS:84981268159

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Y2 - 15 September 2014 through 18 September 2014

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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