« Back to Projects list

Personalized Command Recommendations based on Web Documentation (2016)

Personalized Command Recommendations based on Web Documentation (2016)

Prior work on command recommendations for feature-rich software has relied on data supplied by a large community of users to generate personalized recommendations. In this work, we explore the feasibility of using an alternative data source: web documentation. Specifically, our approach uses QF-Graphs, a previously proposed technique that maps higher-level tasks (i.e., search queries) to commands referenced in online documentation. Our approach uses these command-to-task mappings as an automatically generated plan library, enabling our prototype system to make personalized recommendations for task-relevant commands. Through both offline and online evaluations, we explore potential benefits and drawbacks of this approach.

Project Publications

Exploring User Attitudes Towards Different Approaches to Command Recommendation

Michelle Wiebe, Denise Y. Geiskkovitch, and Andrea Bunt. "Exploring User Attitudes Towards Different Approaches to Command Recommendation in Feature-Rich Software." Proceedings of the 21st International Conference on Intelligent User Interfaces - IUI'16

Exploring Personalized Command Recommendations based on Information Found in Web Documentation

Khan, Md Adnan Alam, Volodymyr Dziubak, and Andrea Bunt. "Exploring Personalized Command Recommendations based on Information Found in Web Documentation." Proceedings of the 20th International Conference on Intelligent User Interfaces. ACM, 2015.

Collaborators

Volodymyr Dziubak

Volodymyr Dziubak

PhD Student
Michelle Wiebe

Michelle Wiebe

Undergraduate Student
Andrea Bunt

Andrea Bunt

Associate Professor