Comparing Effectiveness in TDT and IR

Abstract

Many of the research tasks in Topic Detection and Tracking have counterparts in Information Retrieval research. However, the two research communities evaluate their tasks differently, which makes it very difficult to determine the extent to which they can help each other. In this study, we compare the performance of TDT tracking task to the IR filtering task, and show that they have nearly identical effectiveness. We also show a method for using tracking to predict error rates for the TDT First Story Detection (FSD) task. We then show that FSD performance is what tracking predicts. More importantly, we show that with current approaches, FSD performance has probably reached the limits of effectiveness.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA478126

Entities

People

  • Hubert Jin
  • James Allan
  • Victor Lavrenko

Organizations

  • University of Massachusetts Amherst

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Contracts
  • Detection
  • False Alarms
  • Filtration
  • Information Operations
  • Information Retrieval
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Sensor Fusion and Tracking Systems.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks