| Título |
Author Profiling with doc2vec Neural Network-Based Document Embeddings |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
15th Mexican International Conference on Artificial Intelligence (MICAI 2016) |
| Resumen |
To determine author demographics of texts in social media such as Twitter, blogs, and reviews, we use doc2vec document embeddings to train a logistic regression classifier. We experimented with age and gender identification on the PAN author profiling 2014–2016 corpora under both single- and cross-genre conditions. We show that under certain settings the neural network-based features outperform the traditional features when using the same classifier. Our method outperforms existing state of the art under some settings, though the current state-of-the-art results on those tasks have been quite weak. |
| Observaciones |
DOI 10.1007/978-3-319-62428-0_9
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 10062 |
| Lugar |
Cancún |
| País |
Mexico |
| No. de páginas |
117-131 |
| Vol. / Cap. |
10062 LNAI |
| Inicio |
2016-10-23 |
| Fin |
2016-10-28 |
| ISBN/ISSN |
9783319624273 |
