Adaptive User Interface Design: A Case Study of Web Recommendation System

Authors

  • Wan Nur Liyana Wan Husain Human Computer Interaction (HCI) Research Lab, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.
  • Azrul Hazri Jantan Human Computer Interaction (HCI) Research Lab, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

Keywords:

Adaptive User Interface, Recommendation System, Personalization,

Abstract

Personalization is another special form of adaptation where it widely implements in the development of recommendation system that gives adaptive web environment for users. The main concept of recommendation system is to obtain user behavior factor from user interest or search history and predict the next request as they visit web pages. There are some issues arise in recommender systems which they need a lot of data to efficiently build recommendations. Large amount of items and user data are best for getting good recommendations. In practice, however many challenges exist and evaluation results of recommendation systems has been mixed. This paper presents the case study of Netflix and other case studies in the development of recommendation system and analyzes some of the problems and challenges in implementing recommender systems.

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Published

2017-10-20

How to Cite

Wan Husain, W. N. L., & Jantan, A. H. (2017). Adaptive User Interface Design: A Case Study of Web Recommendation System. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-3), 137–140. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2890

Issue

Vol. 9 No. 3-3: Special Issue on Software Engineering I

Section

Articles

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