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