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Opacity to Transparency: A Journey into Explainable Recommender Systems

  • Unique Paper ID: 160819
  • Volume: 10
  • Issue: 1
  • PageNo: 1617-1626
  • Abstract:
  • Recommender systems have become an integral part of our daily lives, assisting users in discovering the relevant products, services, and information. However, the lack of transparency in the decision-making process of traditional recommender systems has raised concerns regarding user trust and understanding. To address this issue, explainable recommender systems have emerged as a promising research direction. This paper provides a comprehensive overview of explainable recommender systems, focusing on their significance & need, areas of usability, rationale, expected outcomes and challenges. Further it provides a comparative analysis of three approaches used in XAI. To provide a holistic perspective, we review existing literature and highlight key research trends and open challenges in the field of explainable recommender systems. Overall, this paper aims to serve as a comprehensive resource for researchers, practitioners, and decision-makers interested in understanding the state of the art in explainable recommender systems.
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  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 1
  • PageNo: 1617-1626

Opacity to Transparency: A Journey into Explainable Recommender Systems

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Journal no 47859

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