Скачать или смотреть BIGFile: Bayesian Information Gain for Fast File Retrieval

In CHI'18: Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, ACM (2018).

Wanyu Liu, Olivier Rioul, Joanna McGrenere, Wendy E. Mackay and Michel Beaudouin-Lafon

30-second preview video can be found here:    • BIGFile Preview  

We introduce BIGFile, a new fast file retrieval technique based on the Bayesian Information Gain framework. BIGFile provides interface shortcuts to assist the user in navigating to a desired target (file or folder). BIGFile’s split interface combines a traditional list view with an adaptive area that displays shortcuts to the set of file paths estimated by our computationally efficient algorithm. Users can navigate the list as usual, or select any part of the paths in the adaptive area. A pilot study of 15 users informed the design of BIGFile, revealing the size and structure of their file systems and their file retrieval practices. Our simulations show that BIGFile outperforms Fitchett et al.’s AccessRank, a best-of-breed prediction algorithm. We conducted an experiment to compare BIGFile with ARFile (AccessRank instantiated in a split interface) and with a Finder-like list view as baseline. BIGFile was by far the most efficient technique (up to 44% faster than ARFile and 64% faster than Finder), and participants unanimously preferred the split interfaces to the Finder.