Titlebook: Recommender Systems: Algorithms and their Applications; Pushpendu Kar,Monideepa Roy,Sujoy Datta Book 2024 The Editor(s) (if applicable) an

Pelago

978-981-97-0540-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

凝視

Recommender Systems: Algorithms and their Applications978-981-97-0538-2Series ISSN 2730-7484 Series E-ISSN 2730-7492

機構(gòu)

Steps in Building a Recommendation Engine,In this chapter, we discuss the steps one needs to keep in mind while designing an efficient recommender system. We also see what are the design parameters for rating the efficiency of a recommender system. Then the steps to build such a system are discussed along with a generic architecture.

flamboyant

警告

高腳酒杯

受辱

FOIL

2730-7484 of recommender system in healthcare monitoring and military.The book includes a thorough examination of the many types of algorithms for recommender systems, as well as a comparative analysis of them. It addresses the problem of dealing with the large amounts of data generated by the recommender sy

fixed-joint

Collaborative Filtering and Content-Based Systems, model-based methods. The chapter discusses what are the features of and differences between the two methods. The basic components of the content-based systems are also discussed. Both the systems have their advantages and disadvantages which are also discussed here.

crescendo

Big Data Behind Recommender Systems,mportant. We also see how recommender systems can benefit from using big data, what the types of data stored and what the challenges are. Finally, some examples show how exactly it is used by the recommender systems by taking the example of Twitter.