Recommender Systems for IoT Enabled m-Health Applications

被引：22

作者：

Erdeniz, Seda Polat ^{[1
]}

Maglogiannis, Ilias ^{[2
]}

Menychtas, Andreas ^{[3
]}

Felfernig, Alexander ^{[1
]}

Thi Ngoc Trang Tran ^{[1
]}

机构：

[1] Graz Univ Technol, A-8010 Graz, Austria

[2] Univ Piraeus, Dept Digital Syst, Piraeus 18532, Greece

[3] Bioassist, Athens 11524, Greece

来源：

ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2018 | 2018年 / 520卷

关键词：

INTERNET; THINGS; IDENTIFICATION;

D O I：

10.1007/978-3-319-92016-0_21

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recommender systems can help to more easily identify relevant artifacts for users and thus improve user experiences. Currently recommender systems are widely and effectively used in the e-commerce domain (online music services, online bookstores, etc.). On the other hand, due to the rapidly increasing benefits of the emerging topic Internet of Things (IoT), recommender systems have been also integrated to such systems. IoT systems provide essential benefits for human health condition monitoring. In our paper, we propose new recommender systems approaches in IoT enabled mobile health (m-health) applications and show how these can be applied for specific use cases. In this context, we analyze the advantages of proposed recommendation systems in IoT enabled m-health applications.

引用

页码：227 / 237

页数：11

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