Learning Boolean Functions in an Infinite Attribute Space
Machine Learning
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Text clustering with extended user feedback
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Learning question classifiers: the role of semantic information
Natural Language Engineering
An interactive algorithm for asking and incorporating feature feedback into support vector machines
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Learning from labeled features using generalized expectation criteria
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Modeling annotators: a generative approach to learning from annotator rationales
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Active learning for pipeline models
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Explanation-based feature construction
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Object search: supporting structured queries in web search engines
SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search
End-user feature labeling: a locally-weighted regression approach
Proceedings of the 16th international conference on Intelligent user interfaces
Which clustering do you want? inducing your ideal clustering with minimal feedback
Journal of Artificial Intelligence Research
Toward interactive training and evaluation
Proceedings of the 20th ACM international conference on Information and knowledge management
Unified expectation maximization
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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Specifying an appropriate feature space is an important aspect of achieving good performance when designing systems based upon learned classifiers. Effectively incorporating information regarding semantically related words into the feature space is known to produce robust, accurate classifiers and is one apparent motivation for efforts to automatically generate such resources. However, naive incorporation of this semantic information may result in poor performance due to increased ambiguity. To overcome this limitation, we introduce the interactive feature space construction protocol, where the learner identifies inadequate regions of the feature space and in coordination with a domain expert adds descriptiveness through existing semantic resources. We demonstrate effectiveness on an entity and relation extraction system including both performance improvements and robustness to reductions in annotated data.