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Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.

Ilyes Khennak1, Habiba Drias2

  • 1Laboratory for Research in Artificial Intelligence, Computer Science Department, USTHB, BP 32 El Alia 16111, Bab Ezzouar, Algiers, Algeria. ikhennak@usthb.dz.

Journal of Medical Systems
|January 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a Bat Algorithm for medical query expansion, improving search result accuracy for health information seekers. The method efficiently identifies optimal expanded queries, enhancing information retrieval from medical databases.

Keywords:
Bat algorithmMEDLINEMedical data managementQuery expansionRetrieval feedbackSwarm intelligenceWeb intelligence

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence
  • Information Retrieval

Background:

  • Growing volume of online medical data necessitates effective information retrieval.
  • Laypeople often struggle with imprecise search queries due to limited medical knowledge.
  • Existing search engines fail to provide accurate results for vague medical queries.

Purpose of the Study:

  • To enhance the effectiveness of query expansion in the medical domain.
  • To propose an original approach using the Bat Algorithm for optimizing medical search queries.
  • To address the challenge of imprecise user queries in accessing online health information.

Main Methods:

  • An novel approach utilizing the Bat Algorithm for query expansion in the medical field.
  • The Bat Algorithm is employed to select the optimal expanded query from candidate sets.
  • Empirical determination of the expanded query length is incorporated.

Main Results:

  • The proposed Bat Algorithm-based approach demonstrates improved retrieval effectiveness.
  • The method achieves higher efficiency compared to baseline approaches.
  • Numerical results on the MEDLINE database validate the approach's performance.

Conclusions:

  • The Bat Algorithm offers an effective and efficient solution for medical query expansion.
  • This approach improves the accuracy and relevance of search results for health information.
  • The method successfully overcomes limitations of imprecise user queries in medical information retrieval.