论文信息 - Cengage Learning at the TREC 2010 Session Track

Cengage Learning at the TREC 2010 Session Track

This paper details Cengage Leaning’s TREC 2010 Session track submission and our efforts to improve retrieval performance over a user’s session. We use a number of different techniques to achieve this goal including query term weighting, query expansion and re-ranking. In this paper we detail these techniques and the results of our submission. Using our query term weighting technique combined with our corpus term collocation query expansion we were able to achieve 0.2375 for the nsDCG@10.RL13 metric.

Benjamin King | Ivan Provalov

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