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SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
A Mutually Beneficial Integration of Data Mining and Information Extraction
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Vocal communication of emotion: a review of research paradigms
Speech Communication - Special issue on speech and emotion
Document classification using a finite mixture model
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
SVM selective sampling for ranking with application to data retrieval
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
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HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
User Modeling and User-Adapted Interaction
E-Drama: Facilitating Online Role-play using an AI Actor and Emotionally Expressive Characters
International Journal of Artificial Intelligence in Education
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Recognition of affect, judgment, and appreciation in text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Planning Small Talk behavior with cultural influences for multiagent systems
Computer Speech and Language
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Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
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ICSC '10 Proceedings of the 2010 IEEE Fourth International Conference on Semantic Computing
Smile When You Read This, Whether You Like It or Not: Conceptual Challenges to Affect Detection
IEEE Transactions on Affective Computing
Part-of-speech tagging from 97% to 100%: is it time for some linguistics?
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
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IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
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ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Active learning for imbalanced sentiment classification
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
An adaptive ensemble classifier for mining concept drifting data streams
Expert Systems with Applications: An International Journal
Pattern classification and clustering: A review of partially supervised learning approaches
Pattern Recognition Letters
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Affect interpretation from open-ended drama improvisation is a challenging task. This article describes experiments in using latent semantic analysis to identify discussion themes and potential target audiences for those improvisational inputs without strong affect indicators. A context-based affect-detection is also implemented using a supervised neural network with the consideration of emotional contexts of most intended audiences, sentence types, and interpersonal relationships. In order to go beyond the constraints of predefined scenarios and improve the system's robustness, min-margin-based active learning is implemented. This active learning algorithm also shows great potential in dealing with imbalanced affect classifications. Evaluation results indicated that the context-based affect detection achieved an averaged precision of 0.826 and an averaged recall of 0.813 for affect detection of the test inputs from the Crohn's disease scenario using three emotion labels: positive, negative, and neutral, and an averaged precision of 0.868 and an average recall of 0.876 for the test inputs from the school bullying scenario. Moreover, experimental evaluation on a benchmark data set for active learning demonstrated that active learning was able to greatly reduce human annotation efforts for the training of affect detection, and also showed promising robustness in dealing with open-ended example inputs beyond the improvisation of the chosen scenarios.