Lectura TFG / TFM

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Vinaora Nivo Slider 3.x

El Grupo de Sistemas Inteligentes (GSI), reconocido oficialmente por la Universidad Politécnica de Madrid (UPM), está integrado por 14 profesores, 8 investigadores y 7 estudiantes de grado de diferentes departamentos de la universidad, la mayoría de ellos del Departamento de Ingeniería de Sistemas Telemáticos (DIT) de la Escuela Técnica Superior de Ingenieros de Telecomunicación (ETSIT-UPM).

Desde 1982, nuestro grupo ha llevado a cabo la investigación, el desarrollo y la innovación de teorías, métodos y aplicaciones de técnicas de inteligencia artificial, especialmente en los campos de Aprendizaje automático, Big Data, Tecnologías semánticas y Linked Data, Agentes inteligentes y Simulación social, e Ingeniería web y de servicios.

Nuestro grupo ofrece trabajos fin de grado y trabajos fin de máster en temas relacionados con Aprendizaje Automático, Big Data y la Web de Datos. Ofrecemos la posibilidad de publicar el resultado en congresos internacionales.

“Highly organized research is guaranteed to produce nothing new.” ― Frank Herbert, Dune

“An expert is one who knows more and more about less and less until he knows absolutely everything about nothing.” ― Nicholas Murray Butler

“Science is simply common sense at its best, that is, rigidly accurate in observation, and merciless to fallacy in logic.” ― Thomas Henry Huxley

If we knew what we were doing, it wouldn't be research

“I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” - Alan Turing

GSI ha desarrollado un sistema multiagente de diagńostico de red que está siendo usado por Telefónica en España y O2 en la República Checa

GSI participa en un proyecto de simulación social de evaluación de grandes instalaciones financiado por la Comunidad de Madrid

The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. - Tim Berners-Lee

Investigación

Proyectos

Canal GSI

Software

Publicaciones

Últimas noticias

Published Paper: "Contextualization of a Radical Language Detection System Through Moral Values and Emotions"

The article Contextualization of a Radical Language Detection System Through Moral Values and Emotions has been recently published in the IEEE Access journal (JCR Q2 2022, 3.9 IF). The publicacion is authored by Pat ...

Final Conference Project PARTICIPATION

GSI is participating in the final conference of the project PARTICIPATION in Rome. The conference showcases the innovative and participatory methods and tools that the project has developed and tested for analysing ...

Published paper "Detection of the Severity Level of Depression Signs in Text Combining a Feature-Based Framework with Distributional Representations" in Applied Sciences

The article "Detection of the Severity Level of Depression Signs in Text Combining a Feature-Based Framework with Distributional Representations ", by Sergio Muñoz and Carlos A. Iglesias has been published in the A ...

Canal GSI

Lectura TFG / TFM

Miércoles 31/01/2018 B-225 10:00	Development of a Real Time Classification System of Twitter Trends based on Machine Learning Techniques Daniel Mata-Nieves. (2018). Development of a Real Time Classification System of Twitter Trends based on Machine Learning Techniques. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 10:25	Design and Implementation of an embodied cognitive conversational agent for assisting in a web site based on the API.AI conversational platform. Ángel Silván. (2018). Design and Implementation of an embodied cognitive conversational agent for assisting in a web site based on the API.AI conversational platform.. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 11:50	Development of a Classifier of Radical Tweets using Machine Learning Algorithms Mario Hernando. (2018). Development of a Classifier of Radical Tweets using Machine Learning Algorithms. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 12:15	Design and development of a System for Detecting Cyberbullying in Twitter based on Machine Learning Techniques Jaime Palos. (2018). Design and development of a System for Detecting Cyberbullying in Twitter based on Machine Learning Techniques. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 12:40	Design and Development of a Lyrics Emotion Analysis System for Creative Industries José María Izquierdo-Mora. (2018). Design and Development of a Lyrics Emotion Analysis System for Creative Industries. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 13:05	Development of a YouTube videos feelings analiser José Miguel Valle Salas. (2018). Development of a YouTube videos feelings analiser. Trabajo de fin de carrera (TFG).
Miércoles 31/01/2018 B-225 13:30	Design and development of a classification system of political messages in social networks using Natural Language Processing and Machine Learning techniques Carlos Bermúdez Cruces. (2018). Design and development of a classification system of political messages in social networks using Natural Language Processing and Machine Learning techniques. Trabajo de fin de carrera (TFG).
Jueves 01/02/2018 B-225 10:00	Design and Implementation of a Google Action enabled Smart Agent System for Mobile App Review Monitoring based on Sentiment Analysis Techniques Antonio Fernández. (2017). Design and Implementation of a Google Action enabled Smart Agent System for Mobile App Review Monitoring based on Sentiment Analysis Techniques. Trabajo de fin de carrera (PFC). ETSI Telecomunicación, Universidad Politécnica de Madrid.
Jueves 01/02/2018 B-225 11:15	Design and Evaluation of a Conversational Agent Prototype based on Recurrent Neural Networks using Tensorflow. Diego San Cristobal. (2018). Design and Evaluation of a Conversational Agent Prototype based on Recurrent Neural Networks using Tensorflow.. Trabajo de fin de carrera (Master Thesis).
Jueves 01/02/2018 B-225 11:40	Development of a Deep Learning Based Sentiment Analysis and Evaluation Service Ignacio Corcuera-Platas. (2018). Development of a Deep Learning Based Sentiment Analysis and Evaluation Service. Trabajo de fin de carrera (Master Thesis).