Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Wrappers for performance enhancement and oblivious decision graphs
Wrappers for performance enhancement and oblivious decision graphs
Machine Learning - Special issue on inductive transfer
Machine Learning - Special issue on learning with probabilistic representations
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Semisupervised learning of classifiers with application to human-computer interaction
Semisupervised learning of classifiers with application to human-computer interaction
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning as search optimization: approximate large margin methods for structured prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Stylistic text classification using functional lexical features: Research Articles
Journal of the American Society for Information Science and Technology
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Predicting Structured Data (Neural Information Processing)
Predicting Structured Data (Neural Information Processing)
Multi-Objective Learning of Multi-Dimensional Bayesian Classifiers
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Affect Analysis of Web Forums and Blogs Using Correlation Ensembles
IEEE Transactions on Knowledge and Data Engineering
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Inference and Learning in Multi-dimensional Bayesian Network Classifiers
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A machine learning approach to sentiment analysis in multilingual Web texts
Information Retrieval
Automated heart wall motion abnormality detection from ultrasound images using Bayesian networks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Introduction to Semi-Supervised Learning
Introduction to Semi-Supervised Learning
Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-Supervised Learning
An analysis of Bayesian classifiers
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Multi-dimensional classification with Bayesian networks
International Journal of Approximate Reasoning
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Approximating discrete probability distributions with dependence trees
IEEE Transactions on Information Theory
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Sentiment Analysis is defined as the computational study of opinions, sentiments and emotions expressed in text. Within this broad field, most of the work has been focused on either Sentiment Polarity classification, where a text is classified as having positive or negative sentiment, or Subjectivity classification, in which a text is classified as being subjective or objective. However, in this paper, we consider instead a real-world problem in which the attitude of the author is characterised by three different (but related) target variables: Subjectivity, Sentiment Polarity, Will to Influence, unlike the two previously stated problems, where there is only a single variable to be predicted. For that reason, the (uni-dimensional) common approaches used in this area yield to suboptimal solutions to this problem. Somewhat similar happens with multi-label learning techniques which cannot directly tackle this problem. In order to bridge this gap, we propose, for the first time, the use of the novel multi-dimensional classification paradigm in the Sentiment Analysis domain. This methodology is able to join the different target variables in the same classification task so as to take advantage of the potential statistical relations between them. In addition, and in order to take advantage of the huge amount of unlabelled information available nowadays in this context, we propose the extension of the multi-dimensional classification framework to the semi-supervised domain. Experimental results for this problem show that our semi-supervised multi-dimensional approach outperforms the most common Sentiment Analysis approaches, concluding that our approach is beneficial to improve the recognition rates for this problem, and in extension, could be considered to solve future Sentiment Analysis problems.