LemonAid: selection-based crowdsourced contextual help for web applications
Abstract
Web-based technical support such as discussion forums and social networking sites have been successful at ensuring that most technical support questions eventually receive helpful answers. Unfortunately, finding these answers is still quite difficult, since users' textual queries are often incomplete, imprecise, or use different vocabularies to describe the same problem. We present LemonAid, a new approach to help that allows users to find help by instead selecting a label, widget, link, image or other user interface (UI) element that they believe is relevant to their problem. LemonAid uses this selection to retrieve previously asked questions and their corresponding answers. The key insight that makes LemonAid work is that users tend to make similar selections in the interface for similar help needs and different selections for different help needs. Our initial evaluation shows that across a corpus of dozens of tasks and thousands of requests, LemonAid retrieved a result for 90% of help requests based on UI selections and, of those, over half had relevant matches in the top 2 results.
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Prior research has focused mostly on collaboration while learning IT/ICT applications and videogames.
“prior research has focused mostly on collaboration while learning IT/ICT applications and videogames [4,13,35,48,58,71]”
From Older Adults' Collaborative Learning Dynamics When Exploring Feature-Rich Software (2024) · cites this paper as [13]
Studies on collaborative learning in IT/ICT and videogames reported positive outcomes.
“These studies reported positive outcomes of collaborative learning”
From Older Adults' Collaborative Learning Dynamics When Exploring Feature-Rich Software (2024) · cites this paper as [13]
Cited by
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"Why would anybody do this?": Understanding Older Adults' Motivations and Challenges in Crowd Work
Brewer, R., Morris, M. R., & Piper, A. M. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858198 · Cited by 111 · see citing works
Understanding How Programmers Can Use Annotations on Documentation
Horvath, A., Liu, M. X., Hendriksen, R., Shannon, C., Paterson, E., Jawad, K., Macvean, A., & Myers, B. A. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502095 · Cited by 26 · see citing works
TaggedComments: promoting and integrating user comments in online application tutorials
Bunt, A., Dubois, P., Lafreniere, B., Terry, M. A., & Cormack, D. T. (2014) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557118 · Cited by 19 · see citing works
Older Adults' Collaborative Learning Dynamics When Exploring Feature-Rich Software
Baghestani, A., Latulipe, C., & Bunt, A. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637378 · Cited by 7 · see citing works
- Authors
- Chilana, P. K., Ko, A. J., & Wobbrock, J. O.
- Affiliations
- University of Washington (US)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2012-05-05
- Pages
- 1549-1558
- OpenAlex
- W2111009050
- Cited by
- 79
- References
- 0
- Citations by year
- 2026: 6 · 2025: 1 · 2024: 6 · 2023: 5 · 2022: 7 · 2021: 3 · 2020: 6 · 2019: 5 · 2018: 4 · 2017: 6 · 2016: 8 · 2015: 13 · 2014: 4 · 2013: 5
- FWCI
- 5.54
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- technical support, visual question answering, user interface design, query ambiguity
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