Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Building Data Mining Applications for CRM
Building Data Mining Applications for CRM
Relational Data Mining
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Relational Data Mining
Three companions for data mining in first order logic
Relational Data Mining
How to upgrade propositional learners to first order logic: case study
Relational Data Mining
Propositionalization approaches to relational data mining
Relational Data Mining
Learning Logical Definitions from Relations
Machine Learning
Combination of multiple classifiers for the customer's purchase behavior prediction
Decision Support Systems - Special issue: Agents and e-commerce business models
Learning Nonrecursive Definitions of Relations with LINUS
EWSL '91 Proceedings of the European Working Session on Machine Learning
Some Lower Bounds for the Computational Complexity of Inductive Logic Programming
ECML '93 Proceedings of the European Conference on Machine Learning
Multi-relational Decision Tree Induction
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Transformation-Based Learning Using Multirelational Aggregation
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Tree induction vs. logistic regression: a learning-curve analysis
The Journal of Machine Learning Research
Link mining: a new data mining challenge
ACM SIGKDD Explorations Newsletter
An intelligent system for customer targeting: a data mining approach
Decision Support Systems
Machine Learning
Propositionalization-based relational subgroup discovery with RSD
Machine Learning
The dynamics of viral marketing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Customer Metrics and Their Impact on Financial Performance
Marketing Science
Using Online Conversations to Study Word-of-Mouth Communication
Marketing Science
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Identification of influencers - Measuring influence in customer networks
Decision Support Systems
Firm-Created Word-of-Mouth Communication: Evidence from a Field Test
Marketing Science
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
RSD: relational subgroup discovery through first-order feature construction
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Managing information diffusion in Name-Your-Own-Price auctions
Decision Support Systems
A novel evolutionary data mining algorithm with applications to churn prediction
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Neural Networks
MCBANTA'11 Proceedings of the 12th WSEAS international conference on Mathematics and computers in biology, business and acoustics
Collective Churn Prediction in Social Network
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
The influence of online word-of-mouth on long tail formation
Decision Support Systems
Networked individuals predict a community wide outcome from their local information
Decision Support Systems
Hi-index | 0.00 |
Much has been written about word of mouth and customer behavior. Telephone call detail records provide a novel way to understand the strength of the relationship between individuals. In this paper, we predict using call detail records the impact that the behavior of one customer has on another customer's decisions. We study this in the context of churn (a decision to leave a communication service provider) and cross-buying decisions based on an anonymized data set from a telecommunications provider. Call detail records are represented as a weighted graph and a novel statistical learning technique, Markov logic networks, is used in conjunction with logit models based on lagged neighborhood variables to develop the predictive model. In addition, we propose an approach to propositionalization tailored to predictive modeling with social network data. The results show that information on the churn of network neighbors has a significant positive impact on the predictive accuracy and in particular the sensitivity of churn models. The results provide evidence that word of mouth has a considerable impact on customers' churn decisions and also on the purchase decisions, leading to a 19.5% and 8.4% increase in sensitivity of predictive models.