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2016
ACM

Exploring User Attitudes Towards Different Approaches to Command Recommendation in Feature-Rich Software

4 years 3 months ago
Exploring User Attitudes Towards Different Approaches to Command Recommendation in Feature-Rich Software
Feature-rich software applications offer users hundreds of commands, yet most people use only a very small fraction of the available command set. Command recommenders aim to increase awareness of an application’s capabilities by generating personalized recommendations for new commands. A primary distinguishing characteristic of these recommenders concerns the manner in which they determine command relevance. Social approaches do so by analyzing community usage logs, whereas, task-based approaches mine web documentation for logical command clusters. Through a qualitative study with sixteen participants, in this work we explored user attitudes towards these different approaches and the supplemental information they enable. Author Keywords Software learnability; Recommender systems; Explanations ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.
Michelle Wiebe, Denise Y. Geiskkovitch, Andrea Bun
Added 06 Apr 2016
Updated 06 Apr 2016
Type Journal
Year 2016
Where IUI
Authors Michelle Wiebe, Denise Y. Geiskkovitch, Andrea Bunt
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