COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
C4.5: programs for machine learning
C4.5: programs for machine learning
A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Machine Learning
Support Vector Machine Active Learning with Application sto Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Selective Sampling with Redundant Views
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Active learning using pre-clustering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Proceedings of the 13th annual ACM international conference on Multimedia
Sample Selection for Statistical Parsing
Computational Linguistics
Batch mode active learning and its application to medical image classification
ICML '06 Proceedings of the 23rd international conference on Machine learning
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning from labeled features using generalized expectation criteria
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
ECML '07 Proceedings of the 18th European conference on Machine Learning
A web survey on the use of active learning to support annotation of text data
HLT '09 Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing
An analysis of active learning strategies for sequence labeling tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Representative sampling for text classification using support vector machines
ECIR'03 Proceedings of the 25th European conference on IR research
Incorporating diversity and density in active learning for relevance feedback
ECIR'07 Proceedings of the 29th European conference on IR research
An improved algorithm finding nearest neighbor using Kd-trees
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Asking Generalized Queries to Domain Experts to Improve Learning
IEEE Transactions on Knowledge and Data Engineering
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Advances in Engineering Software
Active learning from relative queries
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Active learning methods are used to improve the classification accuracy when little labeled data is available. Most traditional active learning methods pose a very specific query to the oracle, i.e. they ask for the label of an unlabeled example. This paper proposes a novel active learning method called RIQY (Rule Induced active learning QuerY). It can construct generic active learning queries based on rule induction from multiple unlabeled instances. These queries are shorter and more readable for the oracle and encompass many similar cases. Also the learning algorithm can achieve higher accuracy rates by asking fewer queries. We evaluate our algorithm on 12 different real datasets. Our results show that we can achieve higher accuracy rates using fewer queries compared to the traditional active learning methods.