@inproceedings{d694c18f427545ef9c8d2ed4e32f80d9,
title = "Emotiono: An ontology with rule-based reasoning for emotion recognition",
abstract = "Recently, the field of automatic recognition of users' affective states has gained a great deal of attention. Automatic, implicit recognition of affective states has many applications, ranging from personalized content recommendation to automatic tutoring systems. In this work, we propose an ontology called 'Emotiono' for the robust recognition of emotions through Electroencephalogram (EEG). In 'Emotiono', we define entities such as users' emotions, EEG features and their relationships. With inference rules obtained by Decision Tree algorithm, users' current emotional state can be reasoned based on their EEG data. We implement 'Emotiono' in Prot{\'e}g{\'e} 4.1 and evaluate its performance with EEG data gathered from the eNTERFACE06-EMOBRAIN Database. Using a 9-fold cross validation method for training and testing, 'Emotiono' reaches an average classification rate of 97.80% for recognizing 5 subjects' emotional states.",
keywords = "Decision Tree, EEG, Emotion, Ontology",
author = "Xiaowei Zhang and Bin Hu and Philip Moore and Jing Chen and Lin Zhou",
year = "2011",
doi = "10.1007/978-3-642-24958-7_11",
language = "English",
isbn = "9783642249570",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "89--98",
booktitle = "Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings",
edition = "PART 2",
note = "18th International Conference on Neural Information Processing, ICONIP 2011 ; Conference date: 13-11-2011 Through 17-11-2011",
}