We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. We d e v elop a set of techniques for the rank aggregation problem and compare their performance to that of well-known methods. A primary goal of our work is to design rank aggregation techniques that can e ectively combat \spam," a serious problem in Web searches. Experiments show that our methods are simple, e cient, and e ective.
Another related work in the area of web search REF deals with rank aggregation methods for the web, and presents a theoretical groundwork for building and evaluating rank aggregation methods.
Rank aggregation methods for the Web
WWW '01
Computer Science