IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Modeling Human Behavior to Reduce Navigation Time of Menu Items: Menu Item Prediction Based on Markov Chain

Modeling Human Behavior to Reduce Navigation Time of Menu Items: Menu Item Prediction Based on Markov Chain
View Sample PDF
Author(s): Tiantian Xie (Sichuan University, China), Yuxi Zhu (Sichuan University, China), Tao Lin (Sichuan University, China)and Rui Chen (Sichuan University, China)
Copyright: 2015
Pages: 26
Source title: Human Behavior, Psychology, and Social Interaction in the Digital Era
Source Author(s)/Editor(s): Anabela Mesquita (CICE – ISCAP/Polytechnic of Porto, Portugal & Algoritmi Centre, Minho University, Portugal)and Chia-Wen Tsai (Ming Chuan University, Taiwan)
DOI: 10.4018/978-1-4666-8450-8.ch008

Purchase

View Modeling Human Behavior to Reduce Navigation Time of Menu Items: Menu Item Prediction Based on Markov Chain on the publisher's website for pricing and purchasing information.

Abstract

With the increase in the number of menu items and the menu structure complexity, users have to spend more time in locating menu items when using menu-based interfaces. Recently, adaptive menu techniques have been explored to reduce the time and menu item prediction plays a crucial role in the techniques. Unfortunately, there still lacks effective prediction models for menu items. This chapter per the authors explores the potential of three prediction models based on Markov chain in predicting top n menu items with human behavior data while interacting with menus - the users' historical menu item selections. The results show that Weighted Markov Chain using Genetic Algorithm can obtain the highest prediction accuracy and significantly decrease navigation time by 22.6% when N equals 4 as compared to the static counterpart. Two application scenarios of these models on mobile devices and desktop also demonstrated the potentials in daily usage to reduce the time spent to search target menu items.

Related Content

Gülsüm Akarsu. © 2023. 19 pages.
Mitchell Alan Kaplan. © 2023. 18 pages.
Sonia Bhandari, Aarti Bhandari. © 2023. 21 pages.
Mehmet Hilmi Özkaya, Abdullatif Almukaddam, Maeen Alhuwesh. © 2023. 14 pages.
Oğuzhan Yelkesen. © 2023. 19 pages.
Lina Karabetyan. © 2023. 12 pages.
Özlem Yorulmaz. © 2023. 18 pages.
Body Bottom