We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically,knowledge of effective term weights on past queries is used to estimate term weights for new queries. This generalization is achieved by introducing secondary features correlated with term weights and applying regression to predict term weights given features. To improve support for more focused retrieval like question answering, we conduct document retrieval experiments with TREC description queries on three document collections. Results show significantly improved retrieval accuracy.
CITATION STYLE
Lease, M., Allan, J., & Croft, W. B. (2009). Regression rank: Learning to meet the opportunity of descriptive queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5478 LNCS, pp. 90–101). https://doi.org/10.1007/978-3-642-00958-7_11
Mendeley helps you to discover research relevant for your work.