Passage Feedback for News Tracking

Abstract

We extend the event tracking task of Topic Detection and Tracking (TDT) to create a framework in which a user can highlight relevant passages in addition to specifying the relevance of documents. A dual framework of combined document and passage feedback improves performance over a state-of-the-art system without feedback by over 70%. Although annotators vary in the content and length of the passages marked for feedback, improvements in performance are consistent, We demonstrate how events in news follow certain trends over time, making passage feedback critical to event tracking.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA449605

Entities

People

  • Hema Raghavan
  • James Allan

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Agreements
  • Automated Speech Recognition
  • Computer Science
  • Errors
  • False Alarms
  • Feedback
  • Filtration
  • Information Retrieval
  • Iterations
  • Judgment
  • Machine Translation
  • Personal Information Managers
  • Test And Evaluation
  • United States
  • Uss Cole
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design