Users often describe what they want to accomplish with an application in a language that is very different from the application's domain language. To address this gap between system and human language, we propose modeling an application's domain language by mining a large corpus of Web documents about the application using deep learning techniques. A high dimensional vector space representation can model the relationships between user tasks, system commands, and natural language descriptions and supports mapping operations. We demonstrate the feasibility of this approach with a system, CommandSpace, for the popular photo editing application Adobe Photoshop.
Eytan Adar, Mira Dontcheva, and Gierad Laput. 2014. CommandSpace: modeling the relationships between tasks, descriptions and features. In Proceedings of the 27th annual ACM symposium on User interface software and technology (UIST '14). ACM, New York, NY, USA, 167-176. DOI=10.1145/2642918.2647395 http://doi.acm.org/10.1145/2642918.2647395