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Exploring Personalized Command Recommendations based on Information Found in Web Documentation

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.

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.

Bibtext Entry

@inproceedings{khan2015exploring,
  title={Exploring Personalized Command Recommendations based on Information Found in Web Documentation},
  author={Khan, Md Adnan Alam and Dziubak, Volodymyr and Bunt, Andrea},
  booktitle={Proceedings of the 20th International Conference on Intelligent User Interfaces},
  pages={225--235},
  year={2015},
  organization={ACM}
}

Authors

Volodymyr Dziubak

Volodymyr Dziubak

PhD Student
Andrea Bunt

Andrea Bunt

Associate Professor