Cross domain author profiling task in spanish language: an experimental study
Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to the potential applications in security, crime detection and marketing, among others. An interesting point is to stud...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | Argentina |
| Institución: | Universidad Nacional de La Plata |
| Repositorio: | SEDICI (UNLP) |
| Idioma: | inglés |
| OAI Identifier: | oai:sedici.unlp.edu.ar:10915/50187 |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/50187 |
| Access Level: | acceso abierto |
| Palabra clave: | Ciencias Informáticas Natural Language Processing Data mining text mining cross domain classification |
| Sumario: | Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to the potential applications in security, crime detection and marketing, among others. An interesting point is to study the robustness of a classifier when it is trained with a data set and tested with others containing different characteristics. Commonly this is called cross domain experimentation. Although different cross domain studies have been done for data sets in English language, for Spanish it has recently begun. In this context, this work presents a study of cross domain classification for the author profiling task in Spanish. The experimental results showed that using corpora with different levels of formality we can obtain robust classifiers for the author profiling task in Spanish language. |
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