PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Predictive Text Input in a Mobile Shopping Assistant: Methods and Interface Design
Petteri Nurmi, Andreas Forsblom, Patrik Floréen, Peter Peltonen and Petri Saarikko
In: IUI 2009, 8-11 February 2009, Sanibel Island, Florida, USA.


The fundamental nature of grocery shopping makes it an interesting domain for intelligent mobile assistants. Even though the central role of shopping lists is widely recognized, relatively little attention has been paid to facilitating shopping list creation and management. In this paper we introduce a predictive text input technique that is based on association rules and item frequencies. We also describe an interface design for integrating the predictive text input with a web-based mobile shopping assistant. In a user study we compared two interfaces, one with text input support and one without. Our results indicate that, even though shopping list entries are typically short, our technique makes text input significantly faster, decreases typing error rates and increases overall user satisfaction.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:4716
Deposited By:Patrik Floréen
Deposited On:24 March 2009