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Machine Learning - A New Trend in Web User Behavior Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 5 |
| Year of Publication: 2021 |
| Authors: Chinedum Eunice Chibudike, Haruna Abdu, Henry Okwudili Chibudike, Ogochukwu Constance Ngige, Olubamike Adetutu Adeyoju, Nkemdilim Ifeanyi Obi |
10.5120/ijca2021921247
|
Chinedum Eunice Chibudike, Haruna Abdu, Henry Okwudili Chibudike, Ogochukwu Constance Ngige, Olubamike Adetutu Adeyoju, Nkemdilim Ifeanyi Obi . Machine Learning - A New Trend in Web User Behavior Analysis. International Journal of Computer Applications. 183, 5 ( May 2021), 19-25. DOI=10.5120/ijca2021921247
Abstract
Many disciplines, including political economy, linguistics, psychology, social science, and marketing and engineering science, have studied human behavior. As a result, machine learning could be a broad theoretical framework with a wide range of applications, especially in the analysis of internet user browsing behavior. - Aben E. NLANR PMA knowledge, 2010. For testing and calibrating their theoretical models, the aforementioned disciplines used surveys and experimental sampling. The internet logs dealings that store and register each visitor's action on an internet website are the most important sources of information in terms of internet user browsing behavior. Such files may contain incalculable registers, based on the traffic of a web site, and represent a valuable source of human behavior data. This paper examines the rise of machine learning as a trend in analyzing online user behavior, as well as some novel approaches such as knowledge collection and preparation, understanding human behavior, characterization of information analysis in human behavior, internet application, and global application for defining what internet users are looking for in a computing machine..
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