We are primarily concerned with functionalizing a definition of context.
Following many findings within and outside Human Computer Interaction, we think
human activity provides the proper framework for defining context and for
identifying relevant contextual information. Accordingly, we are exploring
methods for automatically detecting activity patterns.
We have built an automatic task support system called CAAD, for Context-Aware
Activity Display. CAAD reliably detects patterns that correspond to people's
stable working contexts by applying a tailored data mining algorithm to detailed
computer logs. Preliminary experiments demonstrate that users find CAAD useful and
easy to use.