Interactive control and visualization of difficulty inferences from user-interface commands

Duri Long, Nicholas Dillon, Kun Wang, Jason Carter, Prasun Dewan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Recently, there has been research on inferring user emotions. Like other inference research, it requires an iterative process in which what-if scenarios are played with different features and algorithms. Traditional, general-purpose data mining tools such as Weka have played an important part in promoting this process. We have augmented this toolset with an additional interactive test-bed designed for prediction and communication of programmer difficulties from user-interface commands. It provides end-user interfaces for communicating, correcting, and reacting to the predictions. In addition, it offers researchers user-interfaces for interacting with the prediction process as it is executed rather than, as in traditional mining tools, after it has generated data for a set of experimental subjects. These user-interfaces can be used to determine key elements of the prediction process, why certain wrong or right predictions have been made, and change parameters of the process. A video demonstration this work is available at http://youtu.be/09LpDIPG5h8.

Original languageEnglish (US)
Title of host publicationIUI 2015 Companion - Companion of the 20th ACM International Conference on Intelligent User Interfaces
PublisherAssociation for Computing Machinery
Pages25-28
Number of pages4
ISBN (Electronic)9781450333085
DOIs
StatePublished - Mar 29 2015
Event20th ACM International Conference on Intelligent User Interfaces, ACM IUI 2015 - Atlanta, United States
Duration: Mar 29 2015Apr 1 2015

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI
Volume29-March-2015

Other

Other20th ACM International Conference on Intelligent User Interfaces, ACM IUI 2015
Country/TerritoryUnited States
CityAtlanta
Period3/29/154/1/15

Keywords

  • Recommender Systems

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

Fingerprint

Dive into the research topics of 'Interactive control and visualization of difficulty inferences from user-interface commands'. Together they form a unique fingerprint.

Cite this