Book contents
- Deep Learning Recommender Systems
- Reviews
- Deep Learning Recommender Systems
- Copyright page
- Contents
- Foreword
- Preface
- 1 Growth Engine of the Internet
- 2 Pre-Deep Learning Era
- 3 Top of the Tide
- 4 Application of Embedding Technology in Recommender Systems
- 5 Recommender Systems from Multiple Perspectives
- 6 Engineering Implementations in Deep Learning Recommender Systems
- 7 Evaluation in Recommender Systems
- 8 Frontier Practice of Deep Learning Recommender Systems
- 9 Build Your Own Recommender Systems Knowledge Framework
- Afterword
- References
5 - Recommender Systems from Multiple Perspectives
Published online by Cambridge University Press: 08 May 2025
Book contents
- Deep Learning Recommender Systems
- Reviews
- Deep Learning Recommender Systems
- Copyright page
- Contents
- Foreword
- Preface
- 1 Growth Engine of the Internet
- 2 Pre-Deep Learning Era
- 3 Top of the Tide
- 4 Application of Embedding Technology in Recommender Systems
- 5 Recommender Systems from Multiple Perspectives
- 6 Engineering Implementations in Deep Learning Recommender Systems
- 7 Evaluation in Recommender Systems
- 8 Frontier Practice of Deep Learning Recommender Systems
- 9 Build Your Own Recommender Systems Knowledge Framework
- Afterword
- References
Summary
Building an effective recommender system requires more than just a strong model; it involves addressing a range of complex technical issues that contribute to the overall performance. This chapter explores recommender systems from seven distinct angles, covering feature selection, retrieval layer strategies, real-time performance optimization, scenario-based objective selection, model structure improvements based on user intent, the cold start problem, and the “exploration vs. exploitation” challenge. By understanding these critical aspects, machine learning engineers can develop robust recommender systems with comprehensive capabilities.
Keywords
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- Type
- Chapter
- Information
- Deep Learning Recommender Systems , pp. 143 - 190Publisher: Cambridge University PressPrint publication year: 2025
References
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