Data-Driven Exploration of Web Browsing Habits: A Visual Analysis with BHVis

Authors

  • Abdul Qayoom School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, P.R. China, and Department of Computer Science, Lasbela University of Agriculture, Water and Marine Sciences, Baluchistan 90150, Pakistan.
  • Shafiq Ur Rehman Mir Chakar Khan Rind University of Technology, Dera Ghazi Khan Pakistan, and Lasbela University of Agriculture, Water and Marine Sciences, Baluchistan 90150, Pakistan
  • Muhammad Waqas School of Software Engineering, University of Electronic Science and Technology of China, Chengdu, China
  • Muhammad Aoun Department of Computer Science and Information Technology, Ghazi University, Dera Ghazi Khan, 32200, Pakistan
  • Umair Saeed Department of Computer Science, Bahria University, Islamabad Campus, Pakistan
  • Wu Yadong
  • Wang Song School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, P.R. China

DOI:

https://doi.org/10.62019/abbdm.v3i1.59

Abstract

Browsing history is an eminent tool for internet users to keep track of the daily and specially visited webpages without bookmarking them. Traditional history tools have become insufficient to satisfy their purpose of addressing complex browsing patterns. Graphical interfaces are the critical solutions for these complexities. Therefore, visualising the browsing histories interactively can be helpful in this case. There are many built-in basic visualisation browsing icons for the ease of the users in different browsers, which help the user quickly access the visited pages. But these tools lack in-depth analysis of users' browsing habits. In this study, we propose a novel approach for visualising the browsing history data and browsing habits of the user. We named this system BHVis (Browsing Habits Visualisation), which visualises the user’s web page visits using different visualisation methods and visual representations to make the browsing habits of the users explicable. The main contribution of this system is to enable users to gain insight into their browsing patterns and enable self-analysis and self-improvement. The system is evaluated based on different case studies. The study shows that this system enables users to gain insights into their web usage and monitor their web browsing habits.

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Published

2023-12-31

How to Cite

Qayoom , A., Rehman , S. U., Waqas , M., Aoun , M., Saeed , U., Yadong , W. ., & Song , W. (2023). Data-Driven Exploration of Web Browsing Habits: A Visual Analysis with BHVis. The Asian Bulletin of Big Data Management, 3(1), 125–134. https://doi.org/10.62019/abbdm.v3i1.59