Association rules: Normalizing the lift

Keywords

Lift (data mining), Association rule learning, Database transaction, Computer science, Data mining

References

• THE VALUE OF INTELLIGENT TRANSPORT SYSTEMS TO ELDERLY AND DISABLED TRAVELLERSS Ling Suen, Cgb Mitchell — 1998
• Understanding spatial concentrations of road accidents using frequent item sets.Karolien Geurts, Isabelle Thomas, Geert Wets — 2005
• Dynamic itemset counting and implication rules for market basket dataSergey Brin, Rajeev Motwani, Jeffrey D. Ullman — 1997
• K-Optimal Rule DiscoveryGeoffrey I. Webb, Songmao Zhang — 2005
• Standardising the lift of an association rulePaul D. McNicholas, Thomas Brendan Murphy, M O'Regan — 2008
• Identifying crash contributory factors at urban roundabouts and using association rules to explore their relationships to different crash types.Alfonso Montella — 2011
• ‘Now without my car I don’t know what I’d do’: The transportation needs of older people in rural LincolnshireMichael R. M. Ward, Peter Somerville, Gary Bosworth — 2013
• Mining association rules between sets of items in large databasesRakesh Agrawal, Tomasz Imieliński, Arun Swami — 1993
• Mining association rules between sets of items in large databasesRakesh Agrawal, Tomasz Imieliński, Arun Swami — 1993

Cited by

• Web usage prediction and recommendation using web session clusteringVinh-Trung Luu, Germain Forestier, Mathis Ripken — 2016
• Using event sequence alignment to automatically segment web users for prediction and recommendationVinh Luu — 2016
• A Multidomain Layered Approach in Development of Industrial Ontology to Support Domain Identification for Unstructured TextRajbabu Kumaravel, Sudha Selvaraj, C. Mala — 2018
• Research on the Value Domains of Several Interest Measures in Association Rule Mining鑫 万 — 2024
• Exploration of the Relationship between Interest Measures Lift and Conviction in Association Rule Analysis and Education Data Validation鑫 万 — 2024
• An AI-Based Framework for Interpretable Mental Health Literacy Segmentation and Decision SupportAntara Ravindra Sarode, M. Vimala Rani, Basudeb Das — 2025
• Comparison of Matrix Factorization Methods for Item-Based RecommendationsM. A. Zharova, V. I. Tsurkov — 2025

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