Optimizing User Interaction for Web-Based Mobile Tasks

Abstract

the small form-factor of mobile handsets and the longer, variable latency of cellular networks are major hindrances to good user experience in mobile web related activities. Existing approaches have yet to adequately address the usability concerns caused by them. This paper describes the design and prototype implementation of MIntOS (Mobile Interaction Optimization System), a system for improving mobile interaction in web-based activities. MIntOS monitors users’ interactions both for gathering interaction history and for the runtime construction of interaction context. A simple approach based on interaction burstiness is used to break interaction sequences into Trails, which approximates user tasks. Such Trails are then used to generate rules for online, context-sensitive prediction of future interaction sequences. Predicted user interaction sequences are then optimized to reduce the amount of user input and user wait time using techniques such as interaction short-cuts, automatic text copying and form-filling, as well as page pre-fetching. Such optimized interaction sequences are, at real-time, recommended to the user through UI enhancements in a non-intrusive manner. MIntOS also uses content and structure based techniques to generalize prediction rules to extend to new but similar user tasks. Several sample applications are used to demonstrate the benefits of MIntOS.