Language variety identification using distributed representations of words and documents
In this work we focus on the use of distributed representations of words and documents using the continuous Skip-gram model. We compare this model with three recent approaches: Information Gain Word-Patterns, TF-IDF graphs and Emotion-labeled Graphs, in addition to several baselines. We evaluate the...
| Autores: | , , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/64372 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/64372 |
| Access Level: | acceso abierto |
| Palabra clave: | Author profiling Language variety identification Distributed representations Information Gain Word-Patterns TF-IDF graphs Emotion-labeled Graphs LENGUAJES Y SISTEMAS INFORMATICOS |
| Sumario: | In this work we focus on the use of distributed representations of words and documents using the continuous Skip-gram model. We compare this model with three recent approaches: Information Gain Word-Patterns, TF-IDF graphs and Emotion-labeled Graphs, in addition to several baselines. We evaluate the models introducing the Hispablogs dataset, a new collection of Spanish blogs from five different countries: Argentina, Chile, Mexico, Peru and Spain. Experimental results show state-of-the-art performance in language variety identification. |
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