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Structured text representations and relevance judgments: an exploratory study

P Srinivasan1

  • 1School of Library & Information Science, University of Iowa, Iowa City 52242.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1994
PubMed
Summary
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This study explores a structured retrieval model, moving beyond keywords to represent text and queries using concepts within complex objects. Results show structure-based similarity correlates with user-judged relevance, indicating potential for more precise information retrieval.

Area of Science:

  • Information Science
  • Computer Science
  • Data Analysis

Background:

  • Traditional information retrieval relies heavily on keyword-based models.
  • Keyword models may not capture the nuanced relationships and semantic context within texts.
  • Analyzing user relevance judgments is crucial for improving retrieval systems.

Purpose of the Study:

  • To investigate a structured text and query model for analyzing user relevance judgments.
  • To compare the precision of structure-based retrieval against keyword-based models.
  • To support the development of advanced information retrieval techniques.

Main Methods:

  • Developed a structured model representing texts and queries using concepts within complex objects.
  • Preserved text-based links between concepts within the model's framework.

Related Experiment Videos

  • Analyzed user relevance judgments based on structure-based similarity.

    • Main Results:

    • A tendency was observed for relevance potential to decrease as structure-based similarity decreased.
    • Structure-based retrieval demonstrated potential for higher precision compared to keyword-based methods.
    • The findings support the efficacy of the proposed structured retrieval model.

    Conclusions:

    • The structured retrieval model offers a promising alternative to keyword-based approaches.
    • Incorporating structural information enhances the analysis of text-query relevance.
    • Further research and development of structured retrieval models are warranted.