Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web

• Authors: Dennis Fetterly;Zoltán Gyöngyi
• Venue: AIRWeb '09, 5th International Workshop on Adversarial Information Retrieval on the Web
• Year: 2009

Before the advent of the World Wide Web, information retrieval algorithms were developed for relatively small and coherent document collections such as newspaper articles or book catalogs in a library. In comparison to these collections, the Web is massive, much less coherent, changes more rapidly, and is spread over geographically distributed computers. Scaling information retrieval algorithms to the World Wide Web is a challenging task. Success to date is depicted by the ubiquitous use of search engines to access Internet content. Adversarial Information Retrieval addresses tasks such as gathering, indexing, filtering, retrieving, and ranking information from collections wherein a subset has been manipulated maliciously. On the Web, the predominant form of such manipulation is "search engine spamming" or spamdexing, i.e., malicious attempts to influence the outcome of ranking algorithms, aimed at getting an undeserved high ranking for some items in the collection. There is an economic incentive to rank higher in search engines, considering that a favorable position in search engine result pages is strongly correlated with more traffic, which often translates to more revenue. As in previous years, automatic detection of search engine spam was the dominant theme of this workshop. A significant fraction of the accepted papers utilized temporal information to aid in detection of adversarial behavior. In addition to short and long papers that had been accepted in previous years, this year we introduced an additional category: position papers on challenges in Adversarial Information Retrieval, and we were excited to have two papers accepted in that category, as we believe in their potential to stimulate discussion at the workshop and beyond.