Benefits of InterSite Pre-Processing and Clustering Methods in E-Commerce Domain
Sergiu Theodor Chelcea, Alzennyr Da Silva, Yves Lechevallier, Doru Tanasa, Brigitte Trousse
Abstract
This paper presents our preprocessing and clustering analysis on the clickstream dataset proposed for the ECMLPKDD 2005 Discovery Challenge. The main contributions of this article are double. First, after presenting the clickstream dataset, we show how we build a rich data warehouse based an advanced preprocesing. We take into account the intersite aspects in the given ecommerce domain, which offers an interesting data structuration. A preliminary statistical analysis based on time period clickstreams is given, emphasing the importance of intersite user visits in such a context. Secondly, we describe our crossed-clustering method which is applied on data generated from our data warehouse. Our preliminary results are interesting and promising illustrating the benefits of our WUM methods, even if more investigations are needed on the same dataset.
Create a lesson
Related papers
Compositional Online Learning for Semantic Data Processing Systems
Paweł Liskowski, Fuheng Zhao, Benjamin Han et al.
Incremental Delta-Shapley: A Standalone Runtime for Predicate Attribution on Sliding Windows
Pouya Khani, Ira Assent
Size Bounds for CQs Under Acyclic Constraints
Stefan Mengel, Andrei Romashchenko
IBLTs Measure Before They Decode: Self-Sizing Set Reconciliation from Pre-Peeling Counts
Min Wu, Ji Qi, Chengdui Luo et al.
VoS: Variate Ordering Strategies for Skyline Query Optimization
Abhinav Gorantla, Pratanu Mandal, K. Selçuk Candan et al.
Realistic Counterfactual Explanations via Denial Constraints
Avia Asael, Nave Frost, Amir Gilad et al.