C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mailing decisions in the catalog sales industry
Management Science
Fast discovery of association rules
Advances in knowledge discovery and data mining
MetaCost: a general method for making classifiers cost-sensitive
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining needle in a haystack: classifying rare classes via two-phase rule induction
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Learning and making decisions when costs and probabilities are both unknown
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
Profit Mining: From Patterns to Actions
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Item selection by "hub-authority" profit ranking
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting Actionable Knowledge from Decision Trees
IEEE Transactions on Knowledge and Data Engineering
Data quality awareness: a case study for cost optimal association rule mining
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Cost-Sensitive-Data Preprocessing for Mining Customer Relationship Management Databases
IEEE Intelligent Systems
Response modeling with support vector regression
Expert Systems with Applications: An International Journal
Employing data mining to identify the significant rules for classifying body types
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Using data mining to identify customer needs in quality function deployment for software design
AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6
Using innovative technology in QFD to improve marketing quality
MATH'07 Proceedings of the 11th WSEAS International Conference on Applied Mathematics
Expert Systems with Applications: An International Journal
A new marketing strategy map for direct marketing
Knowledge-Based Systems
Mining important association rules based on the RFMD technique
International Journal of Data Analysis Techniques and Strategies
Measuring and prioritising value of mobile phone usage
International Journal of Mobile Communications
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
WSEAS Transactions on Computers
Quality-Aware association rule mining
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Preprocessing time series data for classification with application to CRM
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Mining the change of customer behavior in fuzzy time-interval sequential patterns
Applied Soft Computing
Exploring customer perceived value in mobile phone services
International Journal of Mobile Communications
AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
Pattern selection for support vector regression based response modeling
Expert Systems with Applications: An International Journal
Direct marketing with fewer mistakes
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Effects of data set features on the performances of classification algorithms
Expert Systems with Applications: An International Journal
Mining frequent patterns and association rules using similarities
Expert Systems with Applications: An International Journal
Incorporating frequency, recency and profit in sequential pattern based recommender systems
Intelligent Data Analysis
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Direct marketing is a modern business activity with an aim to maximize the profit generated from marketing to a selected group of customers. A key to direct marketing is to select a subset of customers so as to maximize the profit return while minimizing the cost. Achieving this goal is difficult due to the extremely imbalanced data and the inverse correlation between the probability that a customer responds and the dollar amount generated by a response. We present a solution to this problem based on a creative use of association rules. Association rule mining searches for all rules above an interestingness threshold, as opposed to some rules in a heuristic-based search. Promising association rules are then selected based on the observed value of the customers they summarize. Selected association rules are used to build a model for predicting the value of a future customer. On the challenging KDD-CUP-98 dataset, this approach generates 41% more profit than the KDD-CUP winner and 35% more profit than the best result published thereafter, with 57.7% recall on responders and 78.0% recall on non-responders. The average profit per mail is 3.3 times that of the KDD-CUP winner.