Communications of the ACM
Statistical analysis with missing data
Statistical analysis with missing data
A model of decision-making with sequential information-acquisition (part 1)
Decision Support Systems
A model of decision-making with sequential information-acquisition (part 2)
Decision Support Systems
Information-based objective functions for active data selection
Neural Computation
Expert system design: minimizing information acquisition costs
Decision Support Systems
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Learning cost-sensitive active classifiers
Artificial Intelligence
On Active Learning for Data Acquisition
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Modeling Browsing Behavior at Multiple Websites
Marketing Science
Active learning with statistical models
Journal of Artificial Intelligence Research
Active learning for structure in Bayesian networks
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Active learning for class probability estimation and ranking
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Selectively acquiring ratings for product recommendation
Proceedings of the ninth international conference on Electronic commerce
Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce
Proceedings of the ninth international conference on Electronic commerce
Active learning for logistic regression: an evaluation
Machine Learning
Get another label? improving data quality and data mining using multiple, noisy labelers
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Maintaining Diagnostic Knowledge-Based Systems: A Control-Theoretic Approach
Management Science
Active Feature-Value Acquisition
Management Science
Efficiently learning the accuracy of labeling sources for selective sampling
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Identity matching and information acquisition: Estimation of optimal threshold parameters
Decision Support Systems
Repeated labeling using multiple noisy labelers
Data Mining and Knowledge Discovery
| Hi-index | 0.01 |
This paper presents a new information acquisition problem motivated by business applications where customer data has to be acquired with a specific modeling objective in mind. In the last two decades, there has been substantial work in two different fieldsoptimal experimental design and machine learningthat has addressed the issue of acquiring data in a selective manner with a specific objective in mind. We show that the problem presented here is different from the classic model-based data acquisition problems considered thus far in the literature in both fields. Building on work in optimal experimental design and in machine learning, we develop a new active learning technique for the information acquisition problem presented in this paper. We demonstrate that the proposed method performs well based on results from applying this method across 20 Web usage and machine learning data sets.