Using salience to segment desktop activity into projects

Knowledge workers must manage large numbers of simultaneous, ongoing projects that collectively involve huge numbers of resources (documents, emails, web pages, calendar items, etc). An activity database that captures the relationships among projects, resources, and time can drive a variety of tools that save time and increase productivity. To maximize net time savings, we would prefer to build such a database automatically, or with as little user effort as possible. In this paper, we present several sets of features and algorithms for predicting the project associated with each action a user performs on the desktop. Key to our methods is salience, the notion that more recent activity is more informative. By developing novel features that represent salience, we were able to learn models that outperform both a simple benchmark and an expert system tuned specifically for this task on real-world data from five users. ACM Classification Keywords H.5.2 Information Interfaces and Present...

• Type: Conference
• Year: 2009
• Where: IUI
• Authors: Daniel Lowd, Nicholas Kushmerick
• Keywords: IUI 2009, Keywords Information Workers, Little User Effort, Net Time Savings, Software Engineering