The Distinction Between Search and Discovery Systems : A Scholarly Analysis

This comprehensive analysis explores the fundamental distinctions between search and discovery systems in the context of information retrieval and user interaction. The article examines the underlying principles, methodologies, and user experiences associated with each system, elucidating their unique roles in the modern digital landscape. By comparing key aspects such as user intent, interaction models, algorithmic foundations, and evaluation metrics, the article highlights the complementary strengths of these paradigms. The research also investigates emerging hybrid approaches that combine elements of both search and discovery, addressing evolving user expectations and the challenges of information overload. Through this in-depth exploration, the article contributes to the ongoing discourse on the future of information access and informs the development of more effective, user-centric systems capable of meeting diverse information needs in an increasingly complex digital ecosystem.

Authors

Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-10-16
DOI
https://doi.org/10.32628/cseit241051049
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

The Distinction Between Search and Discovery Systems : A Scholarly Analysis

Mehul Thakkar
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International Journal of Scientific Research in Computer Science Engineering and Information Technology
Recommender Systems and Techniques
article

The Distinction Between Search and Discovery Systems : A Scholarly Analysis

Mehul Thakkar
article en

Abstract

This comprehensive analysis explores the fundamental distinctions between search and discovery systems in the context of information retrieval and user interaction. The article examines the underlying principles, methodologies, and user experiences associated with each system, elucidating their unique roles in the modern digital landscape. By comparing key aspects such as user intent, interaction models, algorithmic foundations, and evaluation metrics, the article highlights the complementary strengths of these paradigms. The research also investigates emerging hybrid approaches that combine elements of both search and discovery, addressing evolving user expectations and the challenges of information overload. Through this in-depth exploration, the article contributes to the ongoing discourse on the future of information access and informs the development of more effective, user-centric systems capable of meeting diverse information needs in an increasingly complex digital ecosystem.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(5)
Openalex Percentile: Top 72%
Recommender Systems and Techniques
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