Reciprocal Recommender Systems
Author:   James Neve
Publisher:   Springer International Publishing AG
ISBN:  

9783031851025


Pages:   107
Publication Date:   28 February 2025
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Reciprocal Recommender Systems


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Author:   James Neve
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
ISBN:  

9783031851025


ISBN 10:   3031851021
Pages:   107
Publication Date:   28 February 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface.- 1. Introduction.- 2. Theoretical Background.- 3. Collaborative Filtering.- 4. Content-Based Filtering.- 5. Hybrid Filtering and Additional Approaches.- 6. Matching Theory.- 7. Ethical Concerns and Future Work.

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Author Information

James Neve is a machine learning researcher with Eureka Inc. in Tokyo, designing AI systems including Reciprocal Recommender Systems (RRSs) for online dating services. He has a PhD in Machine Learning from the University of Bristol, specialized in RRSs, and he has published multiple papers on reciprocal recommendation in competitive conferences such as ACM RecSys.

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