Fondazione Ugo Bordoni at TREC 2003: robust and web track
Giambattista Amati, Claudio Carpineto, Giovanni Romano · 2003
Our participation in TREC 2003 aims to adapt the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) to the robust track and the topic distillation task of the Web track. We focus on the robust track, where the utilization of QE improves the global performance but hurts the performance on the worst topics. In particular, we study the problem of the selective application of the query expansion. We define two information theory based functions, InfoDFR and InfoQ, predicting respectively the AP (Average Precision) of queries and the AP increment of queries after the application of QE. InfoQ is used to selectively apply QE. We show that the use of InfoQ achieves the same performance comparable of the unexpanded method on the set of the worst topics, but a better performance than full QE on the entire set of topics. 1 Robust Track FUB participation in the robust track deals with the adaptation of the DFR modular probabilistic framework[2, 3, 1] together with query expansion based on distribution analysis[5, 6, 1] to this new task. In the robust track there are two new evaluation measures, the