An adaptive calendar assistant using pattern mining for user preference modelling

In this paper, we present SmartCal, a calendar assistant that suggests appointment attributes, such as time, day, duration, etc., given any combination of initial user input attributes. SmartCal uses closed pattern mining to discover patterns in past appointment data in order to represent user preferences and adapt to changing user preferences over time. The SmartCal interface is designed to be minimally intrusive: users are free to choose or ignore suggestions, which are dynamically updated as users enter new information. The user model as a collection of patterns is intuitive and transparent: users can view and edit existing patterns or create new patterns based on existing appointments. SmartCal was evaluated in a user study with four users over a four week period. The user study shows that pattern mining makes appointment creation more efficient and users regarded the appointment suggestion feature favourably. Author Keywords Data Mining, Personal Assistants, Calendar Management ...

• Type: Conference
• Year: 2010
• Where: IUI
• Authors: Alfred Krzywicki, Wayne Wobcke, Anna Wong
• Keywords: Initial User Input, IUI 2010, Mining Makes Appointment, Software Engineering, User Preferences