Web Site Audience Segmentation Using Hybrid Alignment Techniques

We are working on behavioral marketing in the Internet. On one hand we observe the behavior of visitors, and on the other hand we trigger (in real-time) stimulations intended to alter this behavior. Real-time and mass-customization are the two challenges that we have to address. In this paper, we present a hybrid approach for clustering visitor sessions, based on a combination of global and local sequence alignments, such as Needleman-Wunsch and Smith-Waterman. Our goal is to define very simple approaches able to address about 80% of visitor sessions to be segmented, and which can be easily turned into small pieces of program, to be run in parallel in thousands of web browsers.

• Type: Journal
• Year: 2015
• Where: PAKDD
• Authors: Vinh-Trung Luu, Germain Forestier, Frédéric Fondement, Pierre-Alain Muller
• Keywords: Data Mining, PAKDD 2015