Crynodeb
Sentiment analysis mines people's opinions and attitudes regarding a certain issue from source materials. Recently, it has drawn significant attention in a number of application areas. The sentiment analysis of healthcare in general and that of users' drug experience in particular could shed significant light on how to improve public health and make the right decisions. However, one of the major challenges in sentiment classification lies in the very large number of extracted features. Fuzzy-rough feature selection provides a means by which discrete or real-valued noisy data can be effectively reduced without human intervention. This paper proposes an implementation for automatic sentiment classification of drug reviews employing fuzzy rough feature selection. Experimental results demonstrate that the employment of fuzzy-rough feature selection can indeed significantly reduce the complexity of feature space and the classification run-time overheads while maintaining classification accuracy.
Iaith wreiddiol | Saesneg |
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Teitl | 2019 IEEE International Conference on Fuzzy Systems |
Is-deitl | FUZZ-IEEE |
Cyhoeddwr | IEEE Press |
Nifer y tudalennau | 6 |
ISBN (Electronig) | 9781538617281 |
ISBN (Argraffiad) | 9781538617298 |
Dynodwyr Gwrthrych Digidol (DOIs) | |
Statws | Cyhoeddwyd - 11 Hyd 2019 |
Digwyddiad | Fuzzy Systems - J W Marriott, New Orleans, Unol Daleithiau America Hyd: 23 Meh 2019 → 26 Meh 2019 Rhif y gynhadledd: 28 |
Cyfres gyhoeddiadau
Enw | IEEE International Conference on Fuzzy Systems |
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Cyhoeddwr | IEEE |
Cyfrol | 2019 |
ISSN (Argraffiad) | 1098-7584 |
ISSN (Electronig) | 1558-4739 |
Cynhadledd
Cynhadledd | Fuzzy Systems |
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Teitl cryno | FUZZ-IEEE-2019 |
Gwlad/Tiriogaeth | Unol Daleithiau America |
Dinas | New Orleans |
Cyfnod | 23 Meh 2019 → 26 Meh 2019 |