User Interaction Modeling and Profile Extraction in Interactive Systems: A Groupware Application Case Study

Abstract

A relevant goal in human–computer interaction is to produce applications that are easy to use and well-adjusted to their users’ needs. To address this problem it is important to know how users interact with the system. This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides, using machine learning techniques, generative models of how users behave. Additionally, these models are transformed into a text that describes in natural language the main characteristics of the interaction of the users with the system.

Keywords

• human–computer interaction
• user modeling
• mobile interfaces
• weighted automaton
• clustering