Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)

Search and recommendation systems are essential in many services, and they are often developed separately, leading to complex maintenance and technical debt. In this paper, we present a unified deep learning model that efficiently handles key aspects of both tasks.

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Publication Details

Published
2024-10-08
DOI
https://doi.org/10.1145/3640457.3688034
Citations
3
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
2.34
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article

Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)

Sudarshan Lamkhede, Moumita Bhattacharya, Vito Ostuni
3 citations
Recommender Systems and Techniques
2.34
article

Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)

Sudarshan Lamkhede, Moumita Bhattacharya, Vito Ostuni
article en
3 citations

Abstract

Search and recommendation systems are essential in many services, and they are often developed separately, leading to complex maintenance and technical debt. In this paper, we present a unified deep learning model that efficiently handles key aspects of both tasks.

Netflix (United States) (US)
Openalex Percentile: Top 9%
Recommender Systems and Techniques
2.34
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Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn) — Sudarshan Lamkhede, Moumita Bhattacharya, et al. · (2024) | TGRS Research Map | TGRS