Volume 4, Issue 2 (9-2017)
Human Information Interaction 2017, 4(2): 71-87 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Sohrabi B, Raeesi Vanani I, Khorami M R. Designing a System for Trend Analysis of Users in Website Surfing in Iran Using Data Mining and Text Mining Algorithms. Human Information Interaction 2017; 4 (2)
URL: http://hii.khu.ac.ir/article-1-2683-en.html
URL: http://hii.khu.ac.ir/article-1-2683-en.html
university of tehran
Abstract: (5318 Views)
Background and Aim: As of the entrance of web surfing to the lifestyle of a vast majority of people in the society and the need for a more accurate social and cultural policy making in the field, authors intended to analyze the behavior of the society users in viewing different websites so as to help politicians and practitioners.
Methods: Design science research method is used in this research. The data sample of research consists of all available users that surf Iranian and foreign websites. For gathering data from various active users, some add-ons were designed and published over browsers so as to gather sufficient data.
Results: Through the utilization of text mining algorithms, the browsed webpages were differentiated and using data mining algorithms, the pages were categorized and interpreted.
Conclusion: Finally, a comprehensive system was designed for the analysis of internet users’ web browsing trends which contains the data gathering phase and innovative report preparation that can be used as an effective sample for analysis, design, and implementation of web-based analytical systems.
Methods: Design science research method is used in this research. The data sample of research consists of all available users that surf Iranian and foreign websites. For gathering data from various active users, some add-ons were designed and published over browsers so as to gather sufficient data.
Results: Through the utilization of text mining algorithms, the browsed webpages were differentiated and using data mining algorithms, the pages were categorized and interpreted.
Conclusion: Finally, a comprehensive system was designed for the analysis of internet users’ web browsing trends which contains the data gathering phase and innovative report preparation that can be used as an effective sample for analysis, design, and implementation of web-based analytical systems.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
