Graciely Nunes Rosa Borges I would be happy to provide you with some good references on recommender system development. There are several books and research papers that are widely regarded as excellent resources for learning about recommender systems. Here are some recommendations:

These references should provide you with a good starting point for learning about recommender systems. It is always a good idea to explore multiple sources and evaluate their relevance to your specific research objectives.

Hello, Graciely Nunes Rosa Borges !

In addition to the references cited above, I suggest looking at these:

• Recommender systems survey (BOBADILLA et al., 2013) - https://doi.org/10.1016/j.knosys.2013.03.012 - This article presents an overview of recommender systems, including collaborative filtering methods and algorithms. It also describes their evolution and explores selected areas of past, present, and future importance.
• Recommender Systems Handbook (RICCI et al., 2015) - https://doi.org/10.1007/978-1-4899-7637-6 - This book is a comprehensive guide to the major concepts, methodologies, and challenges in recommender systems. It includes a variety of real-world applications and case studies and covers topics such as decision-making, privacy, and semantic-based recommender systems.
• Mymedialite: A free recommender system library (GANTNER et al., 2011) - https://doi.org/10.1145/2043932.2043989 - MyMediaLite is a library of recommender system algorithms for rating prediction and item prediction from positive-only implicit feedback.

Graciely Nunes Rosa Borges you can read the next references. I guess they have brief yet concise information on what you want.

https://www.sciencedirect.com/science/article/abs/pii/S0950705121001052

Article Advanced Cosine Measures for Collaborative Filtering

https://arxiv.org/abs/2111.12202

Dear Graciely Nunes Rosa Borges

If you are interested in use recommender system based on user reviews, I recommend you to have a look to these two references:

1.

Recommender systems based on user reviews: the state of the art | SpringerLink

2.

Multi-Criteria Review-Based Recommender System–The State of the Art | IEEE Journals & Magazine | IEEE Xplore

Good Luck!