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Title: An analytical model of website relationships based on browsing history embedding considerations of page transitions

Authors: Taiju Hosaka; Haruka Yamashita; Masayuki Goto

Addresses: Graduate School of Creative Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan ' Faculty of Science and Technology, Sophia University, Chiyoda-ku, Tokyo, Japan ' School of Creative Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan

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.

Keywords: distributed representation; word2vec; sparse regularisation; browsing history data; business analytics.

DOI: 10.1504/AJMSA.2021.10042070

Asian Journal of Management Science and Applications, 2021 Vol.6 No.1, pp.1 - 16

Received: 15 Mar 2020
Accepted: 14 Jul 2020

Published online: 25 Oct 2021 *

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