Paper: Direct Maximization Of Average Precision By Hill-Climbing With A Comparison To A Maximum Entropy Approach

ACL ID N04-4024
Title Direct Maximization Of Average Precision By Hill-Climbing With A Comparison To A Maximum Entropy Approach
Venue Human Language Technologies
Session Short Paper
Year 2004
Authors

We describe an algorithm for choosing term weights to maximize average precision. The algorithm performs successive exhaustive searches through single directions in weight space. It makes use of a novel technique for considering all possible values of average pre- cision that arise in searching for a maximum in a given direction. We apply the algorithm and compare this algorithm to a maximum entropy approach.