Systematic Literature Mapping on Eye Tracking and Data Mining
Article No.: 56, Pages 1 - 4
Abstract
The eye tracking technology has been applied in several fields, such as medicine, engineering and computation. In this last, one of the main uses of the eye tracking technology is for user testing, producing a large volume of data that must be analyzed effectively and efficiently. Of course, there is the idea of combining the concepts of mining the data from eye tracking devices. In order to address this issue, the goal of this work is to carry out a systematic survey of the literature on eye tracking and data mining. We selected some of the major digital libraries to search for articles related to these issues, and through formulated criteria we reached a final set of 16 articles to be analyzed. The analysis of such studies allowed us to reach to some conclusions, e.g., which techniques are the most used in data mining from eye tracking, which are the main forms of visualization of this data.
References
[1]
R. E. Anderson. 2008. Temporal Eye-Tracking Data: Evolution of Debugging Strategies with Multiple Representations. (2008), 99--102.
[2]
Aga Bojko. 2013. Eye Tracking the User Experience A Practical Guide to Research. Rosenfeld Media.
[3]
D.J. Hand, H. Mannila, and P. Smyth. 2001. Principles of Data Mining. MIT Press.
[4]
Naveen Kumar. 2016. A Comparative Study of User Experience in Online Social Media Branding Web Pages Using Eye Tracker. (2016), 01--08.
[5]
Hua Meili. 2010. An Evaluation Research on Usability of Taobao's Homepage and Main Search Engine Based on Eye tracking. (2010), 23--26.
[6]
Kai Petersen. 2008. Systematic Mapping Studies in Software Engineering. (2008), 01--09.
[7]
I.H. Witten and E. Frank. 2005. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Elsevier Science.
Index Terms
- Systematic Literature Mapping on Eye Tracking and Data Mining
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Published In
October 2016
431 pages
ISBN:9781450352352
DOI:10.1145/3033701
Copyright © 2016 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- SBC: Sociedade Brasileira de Computação
- CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
- CGIBR: Comite Gestor da Internet no Brazil
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 October 2016
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- Short-paper
- Research
- Refereed limited
Funding Sources
- FAPESP
Conference
IHC '16
IHC '16: XV Brazilian Symposium on Human Factors in Computing Systems
October 4 - 7, 2016
São Paulo, Brazil
Acceptance Rates
IHC '16 Paper Acceptance Rate 58 of 158 submissions, 37%;
Overall Acceptance Rate 331 of 973 submissions, 34%
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