An analytical model of website relationships based on browsing history embedding considerations of page transitions
by Taiju Hosaka; Haruka Yamashita; Masayuki Goto
Asian J. of Management Science and Applications (AJMSA), Vol. 6, No. 1, 2021

Abstract: In recent years, obtaining a large amount of information and receiving various services through websites has become possible. Consequently, web browsing activities are increasing and numerous companies are conducting their businesses online. In this scenario, users' web browsing behaviour is one of the important topics in web marketing analysis. Several studies have been conducted with distributed representation model to analyse web browsing history. This method can capture the relationships between the websites continuously browsed as similar representations. However, the browsing behavior without a clear browsing purpose in web browsing history can deteriorate the representations. In this paper, we propose the sparse skip gram model using the regularised online learning approach for analysing website relationships robustly. In addition, we apply our method to actual browsing history data and discuss the findings acquired from the analytical results. We show that our proposed model represents the characteristics of websites with subspaces in the embedding space.

Online publication date: Mon, 25-Oct-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the Asian J. of Management Science and Applications (AJMSA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com