Experience with a learning personal assistant
Communications of the ACM
Tracking Context Changes through Meta-Learning
Machine Learning - Special issue on multistrategy learning
Matching events in a content-based subscription system
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Selecting Examples for Partial Memory Learning
Machine Learning
Understanding and Using Context
Personal and Ubiquitous Computing
Project Aura: Toward Distraction-Free Pervasive Computing
IEEE Pervasive Computing
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Advanced Interaction in Context
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
User needs for location-aware mobile services
Personal and Ubiquitous Computing
PILGRIM: A Location Broker and Mobility-Aware Recommendation System
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
The many faces of publish/subscribe
ACM Computing Surveys (CSUR)
Using ubiquitous computing in interactive mobile marketing
Personal and Ubiquitous Computing
Context-Aware Systems for Mobile and Ubiquitous Networks
ICNICONSMCL '06 Proceedings of the International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies
Supporting Context-Aware Media Recommendations for Smart Phones
IEEE Pervasive Computing
A location-aware recommender system for mobile shopping environments
Expert Systems with Applications: An International Journal
The DYNAMOS approach to support context-aware service provisioning in mobile environments
Journal of Systems and Software
A profiling engine for converged service delivery platforms
Bell Labs Technical Journal - Applications and their Enablers in a Converged Communications World
Gain-based selection of ambient media services in pervasive environments
Mobile Networks and Applications
Contory: a middleware for the provisioning of context information on smart phones
Proceedings of the ACM/IFIP/USENIX 2006 International Conference on Middleware
A framework for human-centered provisioning of ambient media services
Multimedia Tools and Applications
Learning automaton based on-line discovery and tracking of spatio-temporal event patterns
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
A learning automata based solution to service selection in stochastic environments
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Service selection in stochastic environments: a learning-automaton based solution
Applied Intelligence
IEEE Communications Magazine
The Adaptive Ontology-Based Personalized Recommender System
Wireless Personal Communications: An International Journal
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The vision of pervasive environments is being realized more than ever with the proliferation of services and computing resources located in our surrounding environments. Identifying those services that deserve the attention of the user is becoming an increasingly-challenging task. In this paper, we present an adaptive multi-criteria decision making mechanism for recommending relevant services to the mobile user. In this context, "Relevance" is determined based on a user-centric approach that combines both the reputation of the service, the user's current context, the user's profile, as well as a record of the history of recommendations. Our decision making mechanism is adaptive in the sense that it is able to cope with users' contexts that are changing and drifts in the users' interests, while it simultaneously can track the reputations of services, and suppress repetitive notifications based on the history of the recommendations. The paper also includes some brief but comprehensive results concerning the task of tracking service reputations by analyzing and comprehending Word-of-Mouth communications, as well as by suppressing repetitive notifications. We believe that our architecture presents a significant contribution towards realizing intelligent and personalized service provisioning in pervasive environments.