Detecting Negative Emotion for Mixed Initiative Visual Analytics

被引：1
|
作者：
Panwar, Prateek [1 ]
Collins, Christopher [1 ]
机构：
[1] Univ Ontario, Inst Technol, Oshawa, ON, Canada
来源：
CHI 2018: EXTENDED ABSTRACTS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS | 2018年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Data Analysis; Emotion Detection; GSR; Eye Tracking;
D O I：
10.1145/3170427.3188664
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper describes an efficient model to detect negative mind states caused by visual analytics tasks. We have developed a method for collecting data from multiple sensors, including GSR and eye-tracking, and quickly generating labelled training data for the machine learning model. Using this method we have created a dataset from 28 participants carrying out intentionally difficult visualization tasks. We have concluded the paper by a discussing the best performing model, Random Forest, and its future applications for providing just-in-time assistance for visual analytics.
引用
收藏
页数：6
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