Surf Wiki
Save to docs
general/information-retrieval-genres

From Surf Wiki (app.surf) — the open knowledge base

Adversarial information retrieval

Information retrieval strategies in datasets

Information retrieval strategies in datasets

Adversarial information retrieval (adversarial IR) is a topic in information retrieval related to strategies for working with a data source where some portion of it has been manipulated maliciously. Tasks can include gathering, indexing, filtering, retrieving and ranking information from such a data source. Adversarial IR includes the study of methods to detect, isolate, and defeat such manipulation.

On the Web, the predominant form of such manipulation is search engine spamming (also known as spamdexing), which involves employing various techniques to disrupt the activity of web search engines, usually for financial gain. Examples of spamdexing are link-bombing, comment or referrer spam, spam blogs (splogs), malicious tagging. Reverse engineering of ranking algorithms, click fraud, and web content filtering may also be considered forms of adversarial data manipulation.

Topics

Topics related to Web spam (spamdexing):

  • Link spam
  • Keyword spamming
  • Cloaking
  • Malicious tagging
  • Spam related to blogs, including comment spam, splogs, and ping spam

Other topics:

  • Click fraud detection
  • Reverse engineering of search engine's ranking algorithm
  • Web content filtering
  • Advertisement blocking
  • Stealth crawling
  • Troll (Internet)
  • Malicious tagging or voting in social networks
  • Astroturfing
  • Sockpuppetry

History

The term "adversarial information retrieval" was first coined in 2000 by Andrei Broder (then Chief Scientist at Alta Vista) during the Web plenary session at the TREC-9 conference.

References

References

  1. Jansen, B. J. (2007) [https://faculty.ist.psu.edu/jjansen/academic/jansen_click_fraud.pdf Click fraud]. IEEE Computer. 40(7), 85-86.
  2. B. Davison, M. Najork, and T. Converse (2006), [https://web.archive.org/web/20090320173324/http://www.acm.org/sigs/sigir/forum/2006D/2006d_sigirforum_davison.pdf SIGIR Worksheet Report: Adversarial Information Retrieval on the Web (AIRWeb 2006)]
  3. D. Hawking and N. Craswell (2004), [http://es.csiro.au/pubs/trecbook_for_website.pdf Very Large Scale Retrieval and Web Search (Preprint version)] {{Webarchive. link. (2007-08-29)
Info: Wikipedia Source

This article was imported from Wikipedia and is available under the Creative Commons Attribution-ShareAlike 4.0 License. Content has been adapted to SurfDoc format. Original contributors can be found on the article history page.

information-retrieval-genres internet-fraud
Want to explore this topic further?

Ask Mako anything about Adversarial information retrieval — get instant answers, deeper analysis, and related topics.

Research with Mako

Free with your Surf account

Content sourced from Wikipedia, available under CC BY-SA 4.0.

This content may have been generated or modified by AI. CloudSurf Software LLC is not responsible for the accuracy, completeness, or reliability of AI-generated content. Always verify important information from primary sources.

Report