Papers
arxiv:2408.10394

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

Published on Aug 19, 2024
Authors:
,
,

Abstract

A unified deep learning model is presented that efficiently addresses core components of search and recommendation systems, reducing maintenance complexity and technical debt.

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.

Community

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2408.10394
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2408.10394 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2408.10394 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2408.10394 in a Space README.md to link it from this page.

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.