Article

EPCI: extracting potentially copyright infringement texts from the web

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Hayato YamanaAuthors Info & Claims

WWW '07: Proceedings of the 16th international conference on World Wide Web

Pages 1151 - 1152

https://doi.org/10.1145/1242572.1242740

Published: 08 May 2007 Publication History

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Abstract

In this paper, we propose a new system extracting potentially copyright infringement texts from the Web, called EPCI. EPCI extracts them in the following way: (1) generating a set of queries based on a given copyright reserved seed-text, (2) putting every query to search engine API, (3) gathering the search result Web pages from high ranking until the similarity between the given seed-text and the search result pages becomes less than a given threshold value, and (4) merging all the gathered pages, then re-ranking them in the order of their similarity. Our experimental result using 40 seed-texts shows that EPCI is able to extract 132 potentially copyright infringement Web pages per a given copyright reserved seed-text with 94% precision in average.

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[2]

C. J. Neill and G. Shanmuganthan, "A Web-Enabled Plagiarism Detection Tool," IT Professional, Vol. 6, No. 5, pp. 19--23, 2004.

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S. Brin, J. Davis and H. Carcia-Molina, "Copy Detection Mechanisms for Digital Documents," Proc. of the ACM SIGMOD Ann. Conf., pp. 398--409, 1995.

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S. Niezgoda and T. P. Way, "SNITCH: A Software Tool for Detecting Cut and Paste Plagiarism," Proc. of the 37th SIGCSE Tech. Symp. on Computer Science Education, pp. 51--55, 2006.

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Pera MNg Y(2011)SimPaD: A word-similarity sentence-based plagiarism detection tool on Web documentsWeb Intelligence and Agent Systems10.5555/1971931.19719339:1(27-41)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.5555/1971931.1971933
Gustafson NPera MNg Y(2008)Nowhere to HideProceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 0110.1109/WIIAT.2008.16(690-696)Online publication date: 9-Dec-2008
https://dl.acm.org/doi/10.1109/WIIAT.2008.16

Index Terms

EPCI: extracting potentially copyright infringement texts from the web
1. Information systems
  1. Information retrieval

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Published In

WWW '07: Proceedings of the 16th international conference on World Wide Web

May 2007

1382 pages

ISBN:9781595936547

DOI:10.1145/1242572

General Chairs:
Carey Williamson
University of Calgary, Canada
,
Mary Ellen Zurko
IBM, USA
,
Program Chairs:
Peter Patel-Schneider
Bell Labs Research, USA
,
Prashant Shenoy
University of Massachusetts at Amherst, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 May 2007

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WWW'07

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WWW'07: 16th International World Wide Web Conference

May 8 - 12, 2007

Alberta, Banff, Canada

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Pera MNg Y(2011)SimPaD: A word-similarity sentence-based plagiarism detection tool on Web documentsWeb Intelligence and Agent Systems10.5555/1971931.19719339:1(27-41)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.5555/1971931.1971933
Gustafson NPera MNg Y(2008)Nowhere to HideProceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 0110.1109/WIIAT.2008.16(690-696)Online publication date: 9-Dec-2008
https://dl.acm.org/doi/10.1109/WIIAT.2008.16

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Identifying popular search goals behind search queries to improve web search ranking

An Empirical Evaluation on Semantic Search Performance of Keyword-Based and Semantic Search Engines: Google, Yahoo, Msn and Hakia

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