Name
Abstract | ||
|---|---|---|
The diversity and the scale of available online instructions introduce opportunities but also user challenges in currently used software interfaces; Users have limited computational resources, and thus often make strategic decisions when browsing, navigating, and understanding instructions to accomplish a task. These strategic user interactions possess nuanced semantics such as users' interpretations, intents, and contexts in which the task is carried out. My dissertation research introduces techniques in constructing data structures that capture the diverse strategies users employ in which the collective nuanced semantics across multiple strategies are preserved. These computational representations are then used as building blocks for designing novel interactions that allow users to effectively browse and navigate instructions, and provide contextual task guidance. Specifically, I investigate 1) structure of instructions for task analysis at scale, 2) structure of collective user task demonstrations, and 3) structure of object uses in how-to videos to support tracking, guiding and searching task states. My research demonstrates that the user-centered organization of information extracted from interaction traces enables novel interfaces with contextual task support.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3332167.3356874 | The Adjunct Publication of the 32nd Annual ACM Symposium on User Interface Software and Technology |
Keywords | Field | DocType |
computational interaction, computational representations | Data structure,Computer science,Human–computer interaction,Task support,Multimedia | Conference |
ISBN | Citations | PageRank |
978-1-4503-6817-9 | 0 | 0.34 |
References | Authors | |
0 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minsuk Chang | 1 | 5 | 5.16 |