Statistical analysis with missing data
Statistical analysis with missing data
Counting your customers: who are they and what will they do next?
Management Science
Inferring decision trees using the minimum description length principle
Information and Computation
Cause-effect relationships and partially defined Boolean functions
Annals of Operations Research
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Information-based objective functions for active data selection
Neural Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
On kernel rules and prime implicants
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The nature of statistical learning theory
The nature of statistical learning theory
Fab: content-based, collaborative recommendation
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Logical analysis of numerical data
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Statistics and data mining techniques for lifetime value modeling
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
Bringing order to the Web: automatically categorizing search results
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Enabling scalable online personalization on the Web
Proceedings of the 2nd ACM conference on Electronic commerce
Mining web logs to improve website organization
Proceedings of the 10th international conference on World Wide Web
KDD-Cup 2000 organizers' report: peeling the onion
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Principles of data mining
Personalization from incomplete data: what you don't know can hurt
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
Specification-Based Browsing of Software Component Libraries
Automated Software Engineering
Mathematical Programming in Data Mining
Data Mining and Knowledge Discovery
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Expert-Driven Validation of Rule-Based User Models in Personalization Applications
Data Mining and Knowledge Discovery
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
IEEE Transactions on Knowledge and Data Engineering
Selected Papers from AISB Workshop on Evolutionary Computing
Feature Selection Via Mathematical Programming
INFORMS Journal on Computing
INFORMS Journal on Computing
Mathematical Programming for Data Mining: Formulations and Challenges
INFORMS Journal on Computing
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Customer lifetime value modeling and its use for customer retention planning
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
A Genetic Algorithm-Based Approach for Building Accurate Decision Trees
INFORMS Journal on Computing
On the Existence and Significance of Data Preprocessing Biases in Web-Usage Mining
INFORMS Journal on Computing
On convergence properties of the em algorithm for gaussian mixtures
Neural Computation
Active learning with statistical models
Journal of Artificial Intelligence Research
Active learning for class probability estimation and ranking
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Training neural nets with the reactive tabu search
IEEE Transactions on Neural Networks
E-Business and Management Science: Mutual Impacts (Part 1 of 2)
Management Science
Editorial: introduction to operations research and data mining
Computers and Operations Research
Revenue Management Through Dynamic Cross Selling in E-Commerce Retailing
Operations Research
Marketing Models of Service and Relationships
Marketing Science
Safely delegating data mining tasks
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
Designing evolving user profile in e-CRM with dynamic clustering of Web documents
Data & Knowledge Engineering
Data mining performance on perturbed databases: important influences on classification accuracy
International Journal of Information and Computer Security
Internet Technologies, ECRM Capabilities, and Performance Benefits for SMEs: An Exploratory Study
International Journal of Electronic Commerce
Customer relationship management and Web mining: the next frontier
Data Mining and Knowledge Discovery
Data-Mining-Driven Neighborhood Search
INFORMS Journal on Computing
Hi-index | 0.01 |
Previous work on the solution to analytical electronic customer relationship management (eCRM) problems has used either data-mining (DM) or optimization methods, but has not combined the two approaches. By leveraging the strengths of both approaches, the eCRM problems of customer analysis, customer interactions, and the optimization of performance metrics (such as the lifetime value of a customer on the Web) can be better analyzed. In particular, many eCRM problems have been traditionally addressed using DM methods. There are opportunities for optimization to improve these methods, and this paper describes these opportunities. Further, an online appendix (mansci.pubs.informs.org/ecompanion.html) describes how DM methods can help optimization-based approaches. More generally, this paper argues that the reformulation of eCRM problems within this new framework of analysis can result in more powerful analytical approaches.