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: | 9783031851025 |
| Publication date: | 28th February 2025 |
| Author: | James Neve |
| Publisher: | Springer an imprint of Springer Nature Switzerland |
| Format: | Paperback |
| Pagination: | 107 pages |
| Series: | SpringerBriefs in Computer Science |
| Genres: |
Information retrieval Machine learning Data warehousing |
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.
Reciprocal Recommender Systems features in the following genres: Information retrieval, Machine learning, Data warehousing
Paperback. £40.49, down from the £44.99 cover price. Not Available.
Reciprocal Recommender Systems was written by James Neve and published by Springer an imprint of Springer Nature Switzerland
Reciprocal Recommender Systems has 107 pages
Yes it is part of SpringerBriefs in Computer Science series
£40.49, reduced from £44.99. Not Available.