LemonAid: selection-based crowdsourced contextual help for web applications

  • Authors:
  • Parmit K. Chilana;Andrew J. Ko;Jacob O. Wobbrock

  • Affiliations:
  • University of Washington, Seattle, Washington, United States;University of Washington, Seattle, Washington, United States;University of Washington, Seattle, Washington, United States

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2012

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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.