Name
Abstract | ||
|---|---|---|
This article presents classifiers based on SVM and Convolutional Neural Networks (CNN) for the TASS 2017 challenge on tweets sentiment analysis. The classifier with the best performance in general uses a combination of SVM and CNN. The use of word embeddings was particularly useful for improving the classifiers performance. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Computation and Language | Sentiment analysis,Computer science,Convolutional neural network,Support vector machine,Natural language processing,Artificial intelligence,Classifier (linguistics),Machine learning |
DocType | Volume | ISSN |
Journal | abs/1710.06393 | ISSN 1613-0073, TASS 2017: Workshop on Semantic Analysis at SEPLN,
Sep 2017, pages 77-83 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aiala Rosá | 1 | 0 | 1.69 |
| Luis Chiruzzo | 2 | 6 | 11.53 |
| Mathías Etcheverry | 3 | 0 | 2.70 |
| Santiago Castro | 4 | 0 | 2.03 |