Logical foundations of object-oriented and frame-based languages
Journal of the ACM (JACM)
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
2nd International Conference on Formal Ontology in Information Systems
FOIS introduction: Ontology---towards a new synthesis
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
The impact of culture and gender on web sites: an empirical study
ACM SIGMIS Database
Modern Information Retrieval
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Experimental Comparison of Schemes for Interpreting Boolean Queries
Experimental Comparison of Schemes for Interpreting Boolean Queries
A Comparison of Two Methods For Soft Boolean Operator Interpretation In Information Retrieval
A Comparison of Two Methods For Soft Boolean Operator Interpretation In Information Retrieval
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Determining the semantic orientation of terms through gloss classification
Proceedings of the 14th ACM international conference on Information and knowledge management
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
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.