Web metasearch as belief aggregation
Sergio A. Álvarez · 2000
Web metasearch requires a mechanism for combining rank-ordered lists of ratings returned by multiple search engines in response to a given user query. We view this as being analogous to the need for combining degrees of belief in probabilistic and uncertain reasoning in artificial intelligence. This paper describes a practical method for performing web metasearch based on a novel transformationbased theory of belief aggregation. The consensus ratings produced by this method take into account the item ratings/rankings output by individual search engines as well as the user's preferences. Copyright c fl 2000, American Association for Artificial Intelligence (www.aaai.org). All rights reserved. Introduction Web search engines (WSE) use tools ranging from simple text-based search to more sophisticated methods that attempt to understand the intended meanings of both queries and data items. There has been much work in this area in recent years. The link structure of the web has...