Experiments with query acquisition and use in document retrieval systems
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
The Utility of Knowledge in Inductive Learning
Machine Learning
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Incorporating Prior Knowledge into Boosting
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Incorporating prior knowledge with weighted margin support vector machines
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Document classification through interactive supervision of document and term labels
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
The sentimental factor: improving review classification via human-provided information
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Text clustering with extended user feedback
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Constructing informative prior distributions from domain knowledge in text classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Reducing the human overhead in text categorization
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Active Learning with Feedback on Features and Instances
The Journal of Machine Learning Research
Improving active learning recall via disjunctive boolean constraints
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Non-negative matrix factorization for semi-supervised data clustering
Knowledge and Information Systems
Knowledge Supervised Text Classification with No Labeled Documents
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Active Learning Strategies for Multi-Label Text Classification
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Interactive clustering of text collections according to a user-specified criterion
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Interactive feature selection for document clustering
Proceedings of the 2011 ACM Symposium on Applied Computing
Semi-supervised document clustering with dual supervision through seeding
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Enhancing semi-supervised document clustering with feature supervision
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Using multiple models to understand data
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
A unified framework for document clustering with dual supervision
ACM SIGAPP Applied Computing Review
Personalized document clustering with dual supervision
Proceedings of the 2012 ACM symposium on Document engineering
Attributes for classifier feedback
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Improving consensus clustering of texts using interactive feature selection
Proceedings of the 22nd international conference on World Wide Web companion
Interactive text document clustering using feature labeling
Proceedings of the 2013 ACM symposium on Document engineering
On Knowledge-Enhanced Document Clustering
International Journal of Information Retrieval Research
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We study the effects of feature selection and human feedback on features in active learning settings. Our experiments on a variety of text categorization tasks indicate that there is significant potential in improving classifier performance by feature reweighting, beyond that achieved via selective sampling alone (standard active learning) if we have access to an oracle that can point to the important (most predictive) features. Consistent with previous findings, we find that feature selection based on the labeled training set has little effect. But our experiments on human subjects indicate that human feedback on feature relevance can identify a sufficient proportion (65%) of the most relevant features. Furthermore, these experiments show that feature labeling takes much less (about 1/5th) time than document labeling. We propose an algorithm that interleaves labeling features and documents which significantly accelerates active learning.