Name
Abstract | ||
|---|---|---|
Opinions are central in almost all human activities, because they are a relevant influence on peoples behavior. The internet and the web have created mechanisms that made possible for people to share their opinions and for other people and organizations to find out more about opinions and experiences from individuals and help in decision making. Still, opinions involve sentiments that are vague and inaccurate textual descriptions. Hence, due to data's nature, Fuzzy Logic can be a promising approach. This paper proposes a fuzzy system to perform opinion classification across different domains. Almost 70 features were extracted from documents and multiple feature selection algorithms were applied to select the most fitted features to classify documents. Over the selected features, the Wang-Mendel (WM) method was used to generate fuzzy rules and classify documents. The WM fuzzy system based achieved 71,25% of accuracy in a 10-fold cross-validation. |
Year | Venue | Field |
|---|---|---|
2015 | FLinAI@IJCAI | Feature selection,Computer science,Fuzzy logic,Artificial intelligence,Fuzzy control system,Machine learning,The Internet |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matheus Cardoso | 1 | 0 | 1.35 |
| Angelo Loula | 2 | 25 | 6.70 |
| Giovanni Pires | 3 | 0 | 0.34 |