University of Glasgow at TREC 2004: Experiments in Web, Robust, and Terabyte Tracks with Terrier

With our participation in TREC2004, we test Terrier, a modular and scalable Information Retrieval framework, in three tracks. For the mixed query task of the Web track, we employ a decision mechanism for selecting appropriate retrieval approaches on a per-query basis. For the robust track, in order to cope with the poorlyperforming queries, we use two pre-retrieval performance predictors and a weighting function recommender mechanism. We also test a new training approach for the automatic tuning of the term frequency normalisation parameters. In the Terabyte track, we employ a distributed version of Terrier and test the effectiveness of techniques, such as using the anchor text, query expansion and selecting an optimal weighting model for each query. Overall, in all three tracks we participated, Terrier and the tested Divergence From Randomness models were shown to be stable and effective.

• Type: Conference
• Year: 2004
• Where: TREC
• Authors: Vassilis Plachouras, Ben He, Iadh Ounis
• Keywords: Divergence From Randomness Models, Mixed Query Task, TREC 2004, TREC 2008, Weighting Function Recommender