On the use of graph embedding techniques for clustering user browsing navigational behaviours

Taşgetiren N., Kılıç T., AKTAŞ M. S.

International Journal of Web and Grid Services, cilt.20, sa.4, ss.482-504, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 4
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1504/ijwgs.2024.143176
  • Dergi Adı: International Journal of Web and Grid Services
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, FRANCIS, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.482-504
  • Anahtar Kelimeler: clickstream data, clustering, DeepWalk, Node2Vec, understanding the user behaviour, user gestures, Word2Vec
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

E-commerce websites offer a multitude of features to their customers through visually appealing interfaces. A significant rise in interest in e-commerce websites has been seen since the onset of the COVID-19 pandemic. Therefore, there is a growing need to incorporate methodologies that can help understand user navigational behaviour on such platforms. This study presents a business process software architecture, which is designed to understand user behaviour through the clustering of similar patterns. To achieve this, graph-based embedding approaches have been utilised. A prototype implementation is presented to demonstrate the proposed business process’s efficiency, and the approach’s technical details are discussed. Furthermore, the performance of the prototype implementation is evaluated by analysing the quality metrics for clustering. The results of this study show that the proposed business process is successful in analysing and comprehending user navigational behaviour on e-commerce websites.