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Collaborative Search Engine for Enhancing Personalized User Search Based on Domain Knowledge.

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  • 1School of Information Technology and Engineering, VIT, Vellore, India. ncsenthilkumar@vit.ac.in.

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Summary
This summary is machine-generated.

This study introduces a personalized search engine that re-ranks results based on user domain and preferences. It improves information retrieval by using collaborative filtering and fuzzy logic for enhanced relevance.

Keywords:
Fuzzy decision treeFuzzy rulesWeb search engine

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Area of Science:

  • Information Science
  • Computer Science
  • Artificial Intelligence

Background:

  • Users face challenges retrieving relevant information from vast data due to context misinterpretation.
  • Existing search engines often provide generic results, failing to meet specific user needs.
  • Personalized information retrieval is crucial for efficient data access in daily life.

Purpose of the Study:

  • To design and implement a personalized search engine tailored to user-specific domains and constraints.
  • To enhance search result relevancy by incorporating domain-specific context and collaborative feedback.
  • To reduce time wasted on irrelevant links through improved information retrieval.

Main Methods:

  • Developed a search engine utilizing web content from document corpora and cloud databases.
  • Implemented a re-ranking mechanism for generic search results based on domain-specific context.
  • Integrated a collaborative search service with a fuzzy decision tree and fuzzy rules for customized feedback.

Main Results:

  • The proposed system effectively re-ranks search results, prioritizing domain-relevant information.
  • Collaborative feedback mechanisms significantly improve the accuracy and relevance of search outcomes.
  • The personalized approach caters to specific user needs, optimizing information retrieval.

Conclusions:

  • The personalized search engine successfully addresses the limitations of generic search by incorporating user domain and preferences.
  • Collaborative filtering and fuzzy logic enhance search relevancy and user satisfaction.
  • This approach offers a more efficient and customized way for users to navigate and retrieve information.