Follow The Clicks: Learning and Anticipating Mouse Interactions During Exploratory Data Analysis. (10th July 2019)

• Record Type: Journal Article
• Authors: Ottley, Alvitta; Garnett, Roman; Wan, Ran
• Is Part Of: Computer graphics forum. Volume 38:Number 3(2019)
• Page Start: 41
• Page End: 52
• Publication Date: 2019-07-10
• Subjects: CCS Concepts -- Human‐centered computing → Visual analytics -- Visualization theory, concepts and paradigms; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.13670
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: The goal of visual analytics is to create a symbiosis between human and computer by leveraging their unique strengths. While this model has demonstrated immense success, we are yet to realize the full potential of such a human‐computer partnership. In a perfect collaborative mixed‐initiative system, the computer must possess skills for learning and anticipating the users' needs. Addressing this gap, we propose a framework for inferring attention from passive observations of the user's click, thereby allowing accurate predictions of future events. We demonstrate this technique with a crime map and found that users' clicks can appear in our prediction set 92% ‐ 97% of the time. Further analysis shows that we can achieve high prediction accuracy typically after three clicks. Altogether, we show that passive observations of interaction data can reveal valuable information that will allow the system to learn and anticipate future events.