Intelligently Recommending Key Bindings on Physical Keyboards with Demonstrations in Emacs

Physical keyboards have been peripheral input devices to electronic computers since early 1970s and become ubiquitous during the past few decades, especially in professional areas such as software programming, professional game playing, and document processing. In these real-world applications, key bindings, a fundamental vehicle for human to interact with software systems using physical keyboards, play a critical role in users' productivity. However, as essential applications of artificial intelligence research, research on intelligent user interfaces and recommender systems barely relates to key bindings on physical keyboards. In this paper, we develop a recommender system (referred to as EKBRS) for intelligently recommending key bindings with demonstration in Emacs, which we use as a base user interface. This is a brand new direction of intelligent user interface research and also a novel application of recommender systems. To the best of our knowledge, this is the world's first intelligent user interface that heavily exploits key bindings of physical keyboards and the world's first recommender system for recommending key bindings. We empirically show the effectiveness of our recommender system and briefly discuss the applicability of this recommender system to other software systems.