Affiliation:
1. Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 24 Tsar Assen St., Plovdiv 4000, BULGARIA
2. College of Artificial Intelligence, North China University of Science and Technology, Caofeidian, Tangshan City, CHINA
Abstract
In this paper, a new vision is presented for highly personalized, customized, and contextualized real-time recommendation of services to mobile users (consumers) by considering the current consumer-, network-, and service context. A smart service recommendation system is elaborated, which builds up and dynamically manages personal profiles of consumers, aiming to facilitate and optimize the service discovery and recommendation process, in support of consumers’ choices, thereby achieving the best quality of experience (QoE) as perceived by those consumers when utilizing different mobile services. The algorithm-driven recommended mobile services, accessible anytime-anywhere-anyhow through any kind of mobile devices via heterogeneous wireless access networks, range from typical telecommunication services (e.g., outgoing voice calls) to Internet services (e.g., multimedia streaming). These algorithms also may be further enriched by their being adapted and expanded to cover more sophisticated services such as helping the consumer’s health and security needs, an example being the finding (with subsequent dynamic changing, if required) of the most 'healthy' or 'secure' driving/biking/jogging/walking route to follow so as to avoid areas posing particular, consumer-specific, health or safety risk.
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
Subject
Artificial Intelligence,General Mathematics,Control and Systems Engineering
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