Recent Experiments with INQUERY

Abstract

Past TREC experiments by the University of Massachusetts have focused primarily on ad hoc query creation. Substantial effort was directed towards automatically translating TREC topics into queries using a set of simple heuristics and query expansion. Less emphasis was placed on the routing task although results were generally good. The Spanish experiments in TREC-3 concentrated on simple indexing sophisticated stemming and simple methods of creating queries. The TREC-4 experiments were a departure from the past. The ad hoc experiments involved "fine tuning" existing approaches and modifications to the INQUERY term weighting algorithm. However, much of the research focus in TREC-4 was on the routing, Spanish, and collection merging experiments. These tracks more closely match our broader research interests in document routing document filtering distributed IR, and multilingual retrieval. The University of Massachusetts experiments were conducted with version 3.0 of the INQUERY information retrieval system. INQUERY is based on the Bayesian inference network retrieval model. It is described elsewhere [7, 5, 12, 11], so this paper focuses on relevant differences to the previously published algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1995
Accession Number
ADA470554

Entities

People

  • James Allan
  • James P. Callan
  • Lisa Ballesteros
  • W. Bruce Croft
  • Zhihong Lu

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Automatic
  • Bayesian Inference
  • Computer Science
  • Databases
  • European Communities
  • Foreign Languages
  • Frequency
  • Information Processing
  • Information Retrieval
  • Massachusetts
  • Online Systems
  • Precision
  • Standards
  • Test And Evaluation
  • Training
  • Universities

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Networking
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval