Multi-Agent-Based Recommender Systems: A Literature Review

Autor:	A. Jorge Morais, Ramiro Gonçalves, António Leça Coelho, Joaquim David Carneiro Neto
Rok vydání:	2021
Předmět:	Literature review Computer science Multi-agent system Multi-agent systems State-of-the-art Recommender systems Recommender system Performance improvement Survey Adaptation (computer science) Complex problems Data science
Zdroj:	Proceedings of Sixth International Congress on Information and Communication Technology ISBN: 9789811623769 ICICT (1)
DOI:	10.1007/978-981-16-2377-6_51
Popis:	Considering the growing volume of information and services available on the Web, it has become essential to provide Web sites and applications with tools, such as recommender systems, capable of helping their users to obtain the information and services appropriate to their interests. Due to the complexity of Web adaptation and the ability of multi-agent systems to deal with complex problems, the multi-agent systems technology have been increasing. In this paper, we present a thorough survey of the use of multi-agent-based recommender systems. The results show that the use of multi-agent systems in recommender systems is increasing. The review shows the diversity of applications of multi-agent systems in recommender systems, namely on what concerns to the diversity of domains, different types of approaches, contributing to improving the performance of the recommendation systems. info:eu-repo/semantics/publishedVersion
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1cbe90a23a7d39675b5613d6d67717d2 https://doi.org/10.1007/978-981-16-2377-6_51 Zobrazit plný text záznamu