Research Issues in Mining User Behavioral Rules for Context-Aware Intelligent Mobile Applications

Context-awareness in smart mobile applications is a growing area of study,\nbecause of it's intelligence in the applications. In order to build\ncontext-aware intelligent applications, mining contextual behavioral rules of\nindividual smartphone users utilizing their phone log data is the key. However,\nto mine these rules, a number of issues, such as the quality of smartphone\ndata, understanding the relevancy of contexts, discretization of continuous\ncontextual data, discovery of useful behavioral rules of individuals and their\nordering, knowledge-based interactive post-mining for semantic understanding,\nand dynamic updating and management of rules according to their present\nbehavior, are investigated. In this paper, we briefly discuss these issues and\ntheir potential solution directions for mining individuals' behavioral rules,\nfor the purpose of building various context-aware intelligent mobile\napplications. We also summarize a number of real-life rule-based applications\nthat intelligently assist individual smartphone users according to their\nbehavioral rules in their daily activities.\n