Navigation in degree of interest trees

We present an experiment that compares how people perform search tasks in a degree-of-interest browser and in a Windows-Explorer-like browser. Our results show that, whereas users do attend to more information in the DOI browser, they do not complete the task faster than in an Explorer-like browser. However, in both types of browser, users are faster to complete high information scent search tasks than low information scent tasks. We present an ACTR computational model of the search task in the DOI browser. The model describes how a visual search strategy may combine with semantic aspects of processing, as captured by information scent. We also describe a way of automatically estimating information scent in an ontological hierarchy by querying a large corpus (in our case, Google's corpus). Categories and Subject Descriptors H.52 [User Interfaces]: Theory and methods; D.2.8 [Software Engineering]: Metrics--complexity measures, performance measures General Terms Measurement, Human ...

• Type: Conference
• Year: 2006
• Where: AVI
• Authors: Raluca Budiu, Peter Pirolli, Michael Fleetwood
• Keywords: AVI 2006, DOI Browser, Information Scent, Search Task, Software Engineering