York University at TREC 2009: Relevance Feedback Track

Abstract

We describe a series of experiments conducted in our participation in the Relevance Feedback Track. We evaluate two traditional weighting models (BM25 and DFR) for the phase 1 task, which are widely used in text retrieval domain. We also evaluate a statistics-based feedback model and our proposed feedback model for the phase 2 task. Currently, we are waiting for the overview paper to facilitate further analyses.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2009
Accession Number
ADA517818

Entities

People

  • Ben He
  • Hongfei Lin
  • Xiangji Huang
  • Zheng Ye

Organizations

  • University of York

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computer Science
  • Education
  • Feedback
  • Frequency
  • Information Operations
  • Information Retrieval
  • Information Science
  • Models
  • New York
  • Probabilistic Models
  • Probability
  • Standards
  • Statistics
  • Universities
  • Weighting Functions

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Information Retrieval