Inferring Calendar Event Attendance Elizabeth Mynatt and Joe Tullio Graphics, Visualization, and Usability Center College of Computing Georgia Institute of Technology

Informal Communication Brief face-to-face conversation –Regular meetings –Irregular personal schedules –Overwhelmed communication channels “Ambushing” –“I’ll ask my advisor during the seminar” –“You can find him at the faculty meeting”

Problems with Calendars Accuracy –Recurring appointments never removed –Conflicting appointments – which will user attend? –All-day events supercede routine ones Privacy Push vs. Pull –Primarily for personal use

Overview A Probabilistic Calendar –Bayesian model –System implementation –Learning through attendance logs Application: Group calendar display –Visualizations Related Work Future Work – Calendars as Sensors

Ambush System Diagram

Attendance Model

Priority –Recurring? –Role? –Type of event? Availability –Location –Length All-day event?

Ambush Experiences Evaluation –Single user –2.5 months, 200 appointments Routine events stabilize Novel events a problem –Hard to parse into node evidence –No prior knowledge

Simple Visualizations

Inside the Black Box Graphical explanation of Bayesian model –Skeptical of output –Diagnosis of model Build sense of trust with inference system Provide quick analysis of relative node influences

Black Box Visualization

Related Work Office Studies: –Groupware calendars: Palen, 1999 –Office communication: Ehrlich 1987 Applications –Context-Aware Office Assistant: Yan, 2000 –Attention-sensitive Alerting: Horvitz et al, 1999 Visualizing uncertainty/explanations –Visual Calendar: Beard et al, 1990 –Explanation: Druzdel, 1996 –Graphical Explanations: Madigan et al, 1996

Future Work Automatic sensing of attendance –Active badges –iButtons More training, more users Formal studies - iterate visualizations Calendars as Sensors –Other application domains? –Ubicomp, Context-aware computing