A fast method for discovering critical edge sequences in e-commerce catalogs

DOI10.1016/j.ejor.2006.06.055zbMath1131.90424OpenAlexW2022257338MaRDI QIDQ877071

Krithi Ramamritham, Anindya Datta, Kaushik Dutta, Pinar Keskinocak, Debra VanderMeer

Publication date: 19 April 2007

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2006.06.055

zbMATH Keywords

graph theorydata mininge-commerceapplied probability

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Operations research and management science (90B99)

Related Items (1)

A framework for configuring collaborative filtering-based recommendations derived from purchase data

Uses Software

• PlanMine
• SPADE

Cites Work

• Unnamed Item
• Unnamed Item
• Data mining for measuring and improving the success of web sites
• On algorithms for finding the k shortest paths in a network
• Finding the k Shortest Paths
• SPADE: An efficient algorithm for mining frequent sequences
• An architecture to support scalable online personalization on the Web
• PlanMine: Prediction plan failures using sequence mining

This page was built for publication: A fast method for discovering critical edge sequences in e-commerce catalogs