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A human-centered design and evaluation framework for information search.

Yang Gong1, Jiajie Zhang

  • 1The University of Texas Health Science Center at Houston, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|June 17, 2006
PubMed
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Effective information search relies on how data is distributed between users and systems. This study introduces a model and task taxonomy to optimize distributed information search across various interfaces.

Area of Science:

  • Human-Computer Interaction
  • Information Science

Background:

  • Information search is an interactive process influenced by information distribution between users and artifacts.
  • Understanding this distribution is key to improving search efficacy.

Purpose of the Study:

  • To develop an information search model and a taxonomy of search tasks.
  • To investigate the relationship between search tasks and interface types using prototypes.

Main Methods:

  • Employed a human-centered method, UFuRT, for model and taxonomy development.
  • Developed prototypes to explore task-interface relationships.
  • Analyzed preliminary results to understand information distribution needs.

Main Results:

  • Identified the necessity of distributed information for effective search tasks.

Related Experiment Videos

  • Gained insights into the complexity of search tasks across different interface types.
  • Conclusions:

    • The distribution of information significantly impacts search task efficacy.
    • Different interface types present varying levels of complexity for distributed information search.