Listar por autor "Pérez, Anxo"
Mostrando ítems 1-6 de 6
-
Asistente Virtual para sitios web
Pérez, Anxo (2019)[Resumen] El objetivo de este trabajo fin de grado es el desarrollo e implementación de un asistente virtual para el sitio web de la Facultad de Informática de la Universidad de A Coruña (UDC). Los usuarios serán capaces ... -
Automatic depression score estimation with word embedding models
Pérez, Anxo; Parapar, Javier; Barreiro, Álvaro (Elsevier, 2022)[Abstract]: Depression is one of the most common mental health illnesses. The biggest obstacle lies in an efficient and early detection of the disorder. Self-report questionnaires are the instruments used by medical experts ... -
BDI-Sen: a sentence dataset for clinical symptoms of depression
Pérez, Anxo; Parapar, Javier; Barreiro, Álvaro; López-Larrosa, Silvia (Association for Computing Machinery, 2023-07)[Abstract] People tend to consider social platforms as convenient media for expressing their concerns and emotional struggles. With their widespread use, researchers could access and analyze user-generated content related ... -
Depression Severity Estimation on the Internet: New Models and Resources
Pérez, Anxo (2023)[Abstract] On the one hand, there is extensive evidence from medicine and psycholinguistics fields of changes in language usage from people suffering from mental health problems. On the other hand, social media ... -
Designing an Open Source Virtual Assistant
Pérez, Anxo; López-Otero, Paula; Parapar, Javier (MDPI AG, 2020-08-21)[Abstract] A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most ... -
Multiple-Choice Question Answering Models for Automatic Depression Severity Estimation
Gabín, Jorge; Pérez, Anxo; Parapar, Javier (MDPI, 2021)[Abstract] Depression is one of the most prevalent mental health diseases. Although there are effective treatments, the main problem relies on providing early and effective risk detection. Medical experts use self-reporting ...