Seven good reasons for mobile agents
Communications of the ACM
User needs for location-aware mobile services
Personal and Ubiquitous Computing
Enabling Technology for Personalizing Mobile Services
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 3 - Volume 3
Learning User Preferences for Wireless Services Provisioning
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
An Architecture and Business Model for Making Software Agents Commercially Viable
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 3 - Volume 03
Context-aware middleware for mobile multimedia applications
Proceedings of the 3rd international conference on Mobile and ubiquitous multimedia
Enhancing traditional local search recommendations with context-awareness
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
An approach to social recommendation for context-aware mobile services
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
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In this paper, we present SmartCon, a context-aware system forthe discovery and selection of mobile services using ArtificialNeural Networks (ANNs). The solution we have developed is a mobileagent-enabled system that adaptively and iteratively learns toselect the best available mobile service derived from theextraction of a series of features utilising contextual informationsuch as the Composite Capabilities/Preference Profiles (CC/PP),service-specific and non-uniform user-specific features which aresupplied to a Back-Propagation Neural Network. Based on thefeatures provided, the neural network classifies the most relevantmobile service. In the present work, the system is also capablethrough iterative learning to generalise and gather informationusing cognitive feedback based on the user's decisions andinteractivity with a Mobile Device. SmartCon is evaluated using aseries of preliminary empirical data and results show an 87%success rate in the discovery and selection of the best or mostrelevant mobile service.