Temporal Mood Variation: at the CLEF eRisk-2018 Tasks for Early Risk Detection on The Internet
| Autor: | Ragheb, Waleed, Moulahi, Bilel, Azé, Jérôme, Bringay, Sandra, Servajean, Maximilien |
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| Přispěvatelé: | Ragheb, Waleed, ADVanced Analytics for data SciencE (ADVANSE), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] Depression Word2vec [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG] Classification MLP Doc2vec [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] Temporal variation Anorexia |
| Zdroj: | Working Notes of CLEF 2018-Conference and Labs of the Evaluation Forum Working Notes of CLEF 2018-Conference and Labs of the Evaluation Forum, Sep 2018, Avignon, France |
| Popis: | International audience; Two tasks are proposed at CLEF eRisk-2018 on predicting mental disorder using Users posts on Reddit. Depression and anorexia disorders are considered to be detected as early as possible. In this paper we present the participation of LIRMM (Laboratoire d’Informatique, de Robotique et de Micro´electronique de Montpellier) in both tasks. The proposed architectures and models use only text information without any hand-crafted features or dictionaries to model the temporal mood variation detected from users posts. The proposed models use two learning phases through exploration of state-of-the-art text vectorization. The proposed models perform comparably to other contributions while experiments shows that document-level outperformed word-level vectorizations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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