University of Glasgow at the Robust Track- A Query-based Model Selection Approach for the Poorly-Performing Queries.
Ben He, Iadh Ounis · Text REtrieval Conference · 2003
In this newly introduced Robust Track, we mainly tested a novel query-based approach for the selection of the most appropriate term-weighting model. In our approach, we cluster the queries according to their statistics and associate the best-performing term-weighting model to each cluster. For a given new query, we assign a cluster to the query according to its statistical features, then apply the model associated to the cluster. As shown by the experimental results, our query-based model selection approach does improve the poorly-performing queries compared to a baseline where a unique retrieval model is applied indifferently to all queries. Moreover, it seems that query expansion has detrimental effect on the poorly-performing queries, although it significantly achieves a higher mean average precision over all the 100 queries.