CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Fuzzy Tier-based User Experience Prediction Scheme

by Ahmed. A. A. Gad-ElRab, Kamal A. ElDahshan, Mahmoud Embabi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 10
Year of Publication: 2015
Authors: Ahmed. A. A. Gad-ElRab, Kamal A. ElDahshan, Mahmoud Embabi
10.5120/ijca2015907063

Ahmed. A. A. Gad-ElRab, Kamal A. ElDahshan, Mahmoud Embabi . Fuzzy Tier-based User Experience Prediction Scheme. International Journal of Computer Applications. 130, 10 ( November 2015), 8-15. DOI=10.5120/ijca2015907063

@article{ 10.5120/ijca2015907063,
author = { Ahmed. A. A. Gad-ElRab, Kamal A. ElDahshan, Mahmoud Embabi },
title = { Fuzzy Tier-based User Experience Prediction Scheme },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 10 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 8-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number10/23244-2015907063/ },
doi = { 10.5120/ijca2015907063 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:25:00.557705+05:30
%A Ahmed. A. A. Gad-ElRab
%A Kamal A. ElDahshan
%A Mahmoud Embabi
%T Fuzzy Tier-based User Experience Prediction Scheme
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 10
%P 8-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Building professional and efficient systems by using user experience became one of the important research activities that focus on the interactions between products, applications, designers, and users. Unfortunately, using user experience faces many problems. One of these problems is how to predict a user experience efficiently to build robust, effective, and flexible applications. To solve this problem, it is needed to design an optimal and efficient method for predicting user experience which includes behavior and emotions experiences. In this paper, a two-tier ranking scheme by using two multi-criteria decision making approaches is proposed. This proposed scheme considers a user experience as a sequence of executed actions or operations and it can predicate the most efficient user experience sequence of operations among a group of user experiences or experiences of individual users on a certain system or application. It uses the combination of two multi-criteria decision making approaches, the analytic hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) in Fuzzy environments to rank each operation or action in a user sequence. Based on operation rank, in the first tier, the proposed algorithm selects all sequential operations with the highest ranks. If there are sub goals are not satisfied in the first tier, then in the second tier, the algorithm ranks all unselected operations and add all operations with the highest ranks which satisfy these sub goals. This new scheme is presented as a flexible and efficient method for predicting user experience which will be help designers and developers in building professional systems and applications.

References
  1. Nielsen , Z. J. 2008. Usability ROI Declining, But Still Strong, in Nielsen Norman research group, Jan. 22.
  2. Law, E. L. C. and van Schaik, P. 2010. Modelling user experience, at an agenda for research and practice,” Interact. Comput., 22(5), 313-322,.
  3. Gould , D. 2010. Product ecosystems and service design, Available: http://www.psfk.com/2010/01.
  4. Picard, R.W. 1997. Affective Computing, in the MIT Press, Cambridge, Massachusetts.
  5. Hekkert, P. and Schifferstein, H. N. J. 2008. Introducing product experience, in Product Experience, P. Hekkert and H. N. J. Schifferstein, Eds. New York: Elsevier, 1-8.
  6. Brown, A.S. 2008. The New Point of View: Focus on Design for Human Factors, ASME Mechanical Engineering Magazine.
  7. Papalambros, P.Y. 2010. The human dimension, in ASME Journal of Mechanical Engineering, 132(5).
  8. Ahn, H. 2010. Modeling and analysis of affective influences on human experience, prediction, decision making, and behavior, MIT, thesis, America.
  9. BrandstÃdtter, E., Gigerenzer, G., and Hertwig, R. 2006. The priority heuristic: Making choices without trade-offs, Psychological Review, 113(2), 409-432,.
  10. Ahn, H. and Picard, R.W. 2005. Affective-cognitive learning and decision making: a motivational reward framework for affective agents, in the 1stInternational Conference on Affective Computing and Intelligent Interaction (ACII 2005), Beijing, China.
  11. Scherer, K.R., Shorr, A., and Johnstone, T. 2001. Appraisal processes in emotion: theory, methods, research, in Oxford University Press, Canary, NC.
  12. Zhou, F. and Jiao, R. J. 2013. An improved user experience model with cumulative prospect theory, in Procedia Computer Science, 16, 870-S877.
  13. Johnson, C. M. and Turley, J. P. 2006. The significance of cognitive modeling in building healthcare interfaces, Int. J. Med. Inf., 75(2), 163-172.
  14. Hassenzahl, M., Diefenbach, S., and Goritz, A. 2010. Needs, affect, and inter- active products, and facets of user experience, Interact. Comput., 22(5), 353-362.
  15. Jiao, J., Zhang, Y., and Helander, M. G. 2006. A Kansei mining system for affective design, in Expert Syst. Appl., 30(4), 658-673.
  16. Griffin, A. and Hauser, J.R. 1993. The voice of the customer, Marketing Science, 12, 1-27.
  17. Scott, M. and Antonsson, E.K. 1998. Aggregation functions for engineering design tradeoffs, Fuzzy Sets and Systems, 99(3), 253-264.
  18. Mazur, G.H. 2005. Life QFD: Incorporating emotional appeal in product development, in 17th Symposium on Quality Function Deployment, Portland.
  19. Lisetti, C.L. and Nasoz, F. 2002. MAUI: A multimodal affective user interface, in: The tenth ACM international conference on Multimedia, Juan-les- Pins, France, 161-170.
  20. Storbeck, J. and Clore, G.L. 2007. On the interdependence of cognition and emotion, in Cognition and Emotion, 21(6), 1212 -1237.
  21. Ahmed A. A. G., ElDahshan, K. A., and Embabi M. E. 2014. Conditional Activity-Based Model for Describing User Experience Using Category Theory, in International Journal of Computer Trends and Technology (IJCTT), 18(6).
  22. Ahmed A. A. G., ElDahshan, K. A., and Embabi M. E. 2015. Fuzzy Predictable Algorithm for User Experience, in International Journal of Computer Trends and Technology (IJCTT), 20(1), 50-58.
Index Terms

Computer Science
Information Sciences

Keywords

Human computer interaction User experience design Fuzzy sets AHP TOPSIS.

Powered by PhDFocusTM