The Web is the killer application of the Internet. Without doubt, such a useful application is destined to be the subject of abuse, as others like e-mail are. Spam has invaded the Search Engines, the Social Networks, and moreover, the Web is also abused by its users and not only the content providers. Adversarial Information Retrieval (AIR) deals with the classification of content (or use of content) regarding its abuse quality, and faces an adversary (the abuser), who is ever trying to mislead the classifier. Search Engine spam detection, Web content filtering, and others, are instances of AIR in the Web. In this work, we review a number of AIR problems in the Web, along with some proposed solutions. We pay special attention to link-based Search Engine spam detection, and to Web content filtering, as representatives of a range of proposed techniques to reach high effectiveness in controlling Web related abuse.
Adversarial information retrieval in the web / R. Baeza Yates, Paolo Boldi, J.M. Gómez Hidalgo. - In: UPGRADE. - ISSN 1684-5285. - 8:1(2007), pp. 33-41.
|Titolo:||Adversarial information retrieval in the web|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2007|
|Appare nelle tipologie:||01 - Articolo su periodico|