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IIT TREC-9 -Entity Based Feedback with Fusion A. Chowdhury, S. Beitzel, E. Jensen, M. Sai-lee, D. Grossman, O.Frieder
 

Summary: IIT TREC-9 - Entity Based Feedback with Fusion
A. Chowdhury, S. Beitzel, E. Jensen, M. Sai-lee, D. Grossman, O.Frieder
Information Retrieval Laboratory
Department of Computer Science
Illinois Institute of Technology
Chicago, IL 60616
{abdur, beitzel, jensen, lee, grossman, frieder} @ ir.iit.edu
M.C. McCabe
Office of Advanced Analytical Tools
U.S. Government
D. Holmes
NCR Corporation
Rockville, Maryland
David.Holmes@WashingtonDC.NCR.COM
Abstract
For TREC-9, we focused on effectiveness in the web track. The key techniques we employed
were information fusion, entity-based relevance feedback, Wordnet-based query parsing and a
user interface designed to assist with web-based manual queries. Our initial results are positive.
For the manual task, forty of fifty queries are over the median. In the adhoc, title-only task,
thirty-four of fifty queries are over the median.

  

Source: Argamon, Shlomo - Department of Computer Science, Illinois Institute of Technology

 

Collections: Computer Technologies and Information Sciences