University of Iowa at TREC 2008 Legal and Relevance Feedback Tracks

Abstract

This 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. Our index remains unchanged from our submission to TREC Legal in 2007, and new changes to our retrieval system are accomplished through the selection of topic fields for input and post-retrieval processing.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2008
Accession Number
ADA512705

Entities

People

  • Brian Almquist
  • Padmini Srinivasan
  • Viet Ha-thuc
  • Yelena Mejova

Organizations

  • University of Iowa

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Closed Loop Systems
  • Computer Science
  • Data Mining
  • Databases
  • Feedback
  • Information Science
  • Judgment
  • Language
  • Machine Learning
  • Network Science
  • Numbers
  • Preprocessing
  • Standards
  • Supervised Machine Learning
  • Training
  • Universities

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Information Retrieval