Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data

This paper describes some of the key properties of the proposed solution for the RecSys 2015 Challenge from the team Tøyvind thørrud. Three contributions will be highlighted: i) Feature extraction, ii) Classifier design, and iii) Decision rules to optimize the prediction results towards the RecSys Challenge’s score. We finished sixth out of more than 250 active teams in the competition. Categories and Subject Descriptors H.2.8 [Database Applications]: Data mining General Terms Recommender systems; Consumer behaviour; Classification Keywords Feature extraction; Random forest; Decision rules

• Type: Journal
• Year: 2015
• Where: RECSYS
• Authors: Øyvind H. Myklatun, Thorstein K. Thorrud, Hai Thanh Nguyen 0001, Helge Langseth, Anders Kofod-Petersen
• Keywords: Control Systems, RECSYS 2015