Adversarial information retrieval
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
data manipulation.[2]
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
See also
References
- ^ Jansen, B. J. (2007) Click fraud. IEEE Computer. 40(7), 85-86.
- ^ B. Davison, M. Najork, and T. Converse (2006), SIGIR Worksheet Report: Adversarial Information Retrieval on the Web (AIRWeb 2006)
- ^ D. Hawking and N. Craswell (2004), Very Large Scale Retrieval and Web Search (Preprint version) Archived 2007-08-29 at the Wayback Machine
External links
- AIRWeb: series of workshops on Adversarial Information Retrieval on the Web
- Web Spam Challenge: competition for researchers on Web Spam Detection
- Web Spam Datasets: datasets for research on Web Spam Detection