A review of data mining techniques for research in online shopping behaviour through frequent navigation paths

Authors

Wing Lok YEUNG, Lingnan University, Hong KongFollow

Document Type

Paper Series

Publication Date

1-2016

No.

075-1516

Abstract

Knowing how consumers navigate online shopping web sites enables retailers to not only better design their sites for navigation but also place buying recommendations at strategic points and personalise the flow of content. Frequent navigation paths can be derived from browsing histories or clickstreams with sequence-oriented data mining techniques. In this working paper, we highlight, with examples, the relevance of frequent navigation paths to online shopping behaviour research and review some relevant data mining techniques.

Comments

HKIBS Working Paper Series 075-1516

Recommended Citation

Yeung, W. L. (2016). A review of data mining techniques for research in online shopping behaviour through frequent navigation paths (HKIBS Working Paper Series 075-1516). Retrieved from Lingnan University website: http://commons.ln.edu.hk/hkibswp/76