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Reciprocal recommender systems
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Reciprocal recommender systems
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Reciprocal recommender systems/ by James Neve.
作者:
Neve, James.
出版者:
Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:
xi, 107 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer Nature eBook
標題:
Recommender systems (Information filtering) -
電子資源:
https://doi.org/10.1007/978-3-031-85103-2
ISBN:
9783031851032
Reciprocal recommender systems
Neve, James.
Reciprocal recommender systems
[electronic resource] /by James Neve. - Cham :Springer Nature Switzerland :2025. - xi, 107 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..
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.
This book provides an introduction to reciprocal recommendation. It starts with theory, and then moves on to concrete examples of the most successful algorithms in the field. Researchers and developers with a little background in machine learning will find many of the algorithms are straightforward to implement, and code samples are included to help with this. In addition to accessible algorithms, the book also examines some more cutting-edge research such as the recent interest in applying matching theory to reciprocal recommendation. These parts will be of interest both to developers who are looking to optimize their systems, and to researchers who might find avenues to further advance the field and develop new methods of recommending people to people. By the end of this book, the reader will have a comprehensive understanding of the state of the art in reciprocal recommendation and will be equipped to design and implement their own systems.
ISBN: 9783031851032
Standard No.: 10.1007/978-3-031-85103-2doiSubjects--Topical Terms:
1002434
Recommender systems (Information filtering)
LC Class. No.: ZA3084
Dewey Class. No.: 005.56
Reciprocal recommender systems
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This book provides an introduction to reciprocal recommendation. It starts with theory, and then moves on to concrete examples of the most successful algorithms in the field. Researchers and developers with a little background in machine learning will find many of the algorithms are straightforward to implement, and code samples are included to help with this. In addition to accessible algorithms, the book also examines some more cutting-edge research such as the recent interest in applying matching theory to reciprocal recommendation. These parts will be of interest both to developers who are looking to optimize their systems, and to researchers who might find avenues to further advance the field and develop new methods of recommending people to people. By the end of this book, the reader will have a comprehensive understanding of the state of the art in reciprocal recommendation and will be equipped to design and implement their own systems.
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