Comparative Study of the Internet of Things Recommender System

• Published in: Advances in Data Science, Cyber Security and IT Applications pp. 278 - 285
• Main Authors: Bouazza, Halima, Zohra, Laallam Fatima, Said, Bachir
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Collaborative filtering; Content based filtering; IoT; Knowledge based filtering; Ontology; Recommender system
• ISBN: 3030363678; 9783030363673
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-36368-0_23

The Internet of things is a technological revolution which brings the virtual and physical world into the same ecosystem. Hence, the growing proliferation of data, objects and services provided by many IoT objects and platforms which has contributed to the problem of information overload. Thus, it makes difficulties to discover and offer products and services that may be in the interest of users. Suggesting suitable items, things and services to IoT users based the data generated from objects owned by those users is discussed in many papers, the purpose of this paper is to illustrate how recommendations can be applied in the IoT area, taking into account the characteristics of the domain and proposing new recommendation approach for the IoT domain. In this context, we also provide a review of some remarkable existing works in the recommendation technologies in IoT.