Almquist, BrianMejova, YelenaHa-Thuc, VietSrinivasan, Padmini2020-07-242022-05-312022-05-312008Almquist, B., Mejova, Y., Ha-Thuc, V. and Srinivasan, P. The University of Iowa at TREC 2008 Legal and Relevance Feedback Tracks. Proceedings of the 17th Text REtrieval Conference (2008).https://hdl.handle.net/20.500.14078/1652This is the second year that our research group has participated in the TREC Legal Track. Our ad hoc retrieval system has been modified to extract the additional Boolean query fields added to the 2008 topics, and to privilege documents found by the Boolean reference run when conducting our queries. We have also submitted runs that fuse the results from existing runs. For the relevance feedback task, our system uses ranking information of relevant and non-relevant documents from previously submitted runs to the TREC Legal Track to train a classifier. The classifier is applied to the remaining unjudged documents to create a new ranked list. This approach is applied to sets of input runs, including a hybrid run where a classifier trained on one set of runs is applied to the unjudged documents from another set of runs.215.65KBPDFenAll Rights Reservedinformation retrievalrank aggregationPresentation