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Article

Using spam farm to boost PageRank

Authors:

Xin ZhaoAuthors Info & Claims

AIRWeb '07: Proceedings of the 3rd international workshop on Adversarial information retrieval on the web

Pages 29 - 36

https://doi.org/10.1145/1244408.1244415

Published: 08 May 2007 Publication History

Abstract

Nowadays web spamming has emerged to take the economic advantage of high search rankings and threatened the accuracy and fairness of those rankings. Understanding spamming techniques is essential for evaluating the strength and weakness of a ranking algorithm, and for fighting against web spamming. In this paper, we identify the optimal spam farm structure under some realistic assumptions in the single target spam farm model. Our result extends the optimal spam farm claimed by Gyöngyi and Garcia-Molina through dropping the assumption that leakage is constant. We also characterize the optimal spam farms under additional constraints, which the spammer may deploy to disguise the spam farm by deviating from the unconstrained optimal structure.

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Cited By

Ni XBu SAdams LMarkov IDemartini GZuccon GCulpepper JHuang ZTong H(2021)Prioritizing Original News on FacebookProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481943(4046-4054)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481943
Bahri LGirdzijauskas S(2019)Trust Mends Blockchains: Living up to Expectations2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2019.00136(1358-1368)Online publication date: Jul-2019
https://doi.org/10.1109/ICDCS.2019.00136
Bahri LGirdzijauskas SChampin PGandon FMédini LLalmas MIpeirotis P(2018)When Trust Saves EnergyCompanion Proceedings of the The Web Conference 201810.1145/3184558.3191553(1165-1169)Online publication date: 23-Apr-2018
https://dl.acm.org/doi/10.1145/3184558.3191553
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Index Terms

Using spam farm to boost PageRank
1. Information systems
  1. Information retrieval

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Published In

cover image ACM Other conferences

AIRWeb '07: Proceedings of the 3rd international workshop on Adversarial information retrieval on the web

May 2007

98 pages

ISBN:9781595937322

DOI:10.1145/1244408

Conference Chairs:
Carlos Castillo
Yahoo! Research
,
Kumar Chellapilla
Microsoft Live Labs
,
Brian D. Davison
Lehigh University

Copyright © 2007 ACM.

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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AIRWeb'07

AIRWeb'07: AIRWeb'07, Third International Workshop on Adversarial Information Retrieval on the Web

May 8, 2007

Alberta, Banff, Canada

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Cited By

Ni XBu SAdams LMarkov IDemartini GZuccon GCulpepper JHuang ZTong H(2021)Prioritizing Original News on FacebookProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481943(4046-4054)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481943
Bahri LGirdzijauskas S(2019)Trust Mends Blockchains: Living up to Expectations2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2019.00136(1358-1368)Online publication date: Jul-2019
https://doi.org/10.1109/ICDCS.2019.00136
Bahri LGirdzijauskas SChampin PGandon FMédini LLalmas MIpeirotis P(2018)When Trust Saves EnergyCompanion Proceedings of the The Web Conference 201810.1145/3184558.3191553(1165-1169)Online publication date: 23-Apr-2018
https://dl.acm.org/doi/10.1145/3184558.3191553
Ziqian YWenhui ZHuijuan FZhixiao T(2017)A PageRank-improved ranking algorithm based on cheating similarity and cheating relevance2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)10.1109/ICIS.2017.7960003(257-263)Online publication date: May-2017
https://doi.org/10.1109/ICIS.2017.7960003
Jachimczyk AChrapek MChrapek Z(2016)Web directories: selected features and their impact on directory qualityProgram10.1108/PROG-08-2014-006050:3(340-352)Online publication date: 4-Jul-2016
https://doi.org/10.1108/PROG-08-2014-0060
Yang BChen HZhao XNaka MHuang J(2015)On characterizing and computing the diversity of hyperlinks for anti-spamming page rankingKnowledge-Based Systems10.1016/j.knosys.2014.12.02877:C(56-67)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1016/j.knosys.2014.12.028
Al-Kabi MAlsmadi IWahsheh H(2015)Evaluation of Spam Impact on Arabic Websites PopularityJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2014.04.00527:2(222-229)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.1016/j.jksuci.2014.04.005
Likitkhajorn CSurarerks ARungsawang A(2012)An approach of two-way spam detection based on boosting pages analysis2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology10.1109/ECTICon.2012.6254182(1-4)Online publication date: May-2012
https://doi.org/10.1109/ECTICon.2012.6254182
Adal SLiu TMagdon-Ismail M(2012)An analysis of optimal link bombsTheoretical Computer Science10.1016/j.tcs.2012.02.019437(1-20)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1016/j.tcs.2012.02.019
Bjelland JCanright GEngø‐Monsen K(2012)Link Analysis and Web SearchComputational Complexity10.1007/978-1-4614-1800-9_112(1746-1766)Online publication date: 2012
https://doi.org/10.1007/978-1-4614-1800-9_112
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