LCS Publication Details
Publication Title: An Efficient Boosting Algorithm for Combining Preferences
Publication Author: Iyer Jr., Raj Dharmarajan
Additional Authors:
LCS Document Number: MIT-LCS-TR-811
Publication Date: 8-24-1999
LCS Group: Theory of Computation
Additional URL: No URL Given
The problem of combining preferences arises in several applications, such as combining the results of di erent search engines. This work describes an effcient algorithm for combining multiple preferences. We rst give a formal framework for the problem. We then describe and analyze a new boosting algorithm for combining preferences called RankBoost. We also describe an effcient implementation of the algorithm for certain natural cases. We discuss two experiments we carried out to assess the performance of RankBoost. In the rst experiment, we used the algorithm to combine di erent WWW search strategies, each of which is a queryexpansion for a given domain. For this task, we compare the performance of RankBoost to the individual search strategies. The second experiment is a collaborative-filtering task for making movie recommendations. Here, we present results comparing RankBoost to nearest-neighbor and regression algorithms.
To obtain this publication:

To purchase a printed copy of this publication please contact MIT Document Services.