Estas semanas se leen varios trabajos fin de titulación, estáis todos invitados a las lecturas.


El jueves 4/7/2019 en el aula B225, los TFGs:

  • 9:00 Fernando Loro, "Development of Intrusion Detection Models for CyberSecurity in Computer Networks applying Machine Learning Algorithms"
  • 10:20 Adrián González, "Design and development of a developer sentiment analysis system based on GitHub commit comments"
  • 10:40 Luis Caballero, "Development of a Mobile Nutritional Assistant for Supermarkets with the technology DialogFlow"
  • 11:00 Alejandro López, "Design and development of gamified smart objects for museums based on automatically generated quizzes exploiting Linked Data. Application: Telecommunications Museum at ETSIT."

El viernes 5/7/2019 en el aula B225, los TFGs: 

  • 9:40 Pablo Lostao, "Development of a Mobile augmented reality virtual assistant for a smart office"
  • 10:00 Gonzalo Osende, "Design and Development of a song recommender system based on user experience and emotions"

El martes 9/7/2019 en el aula B223, el TFM:

  • 9:20, Fernando Benayas, "Design of an architecture for cyber-attack detection on an SDN environment"

El miércoles 10/7/2019 en el aula B222, el TFG:

  • 9:40, Luis García, "Design and Development of a Lexicon-based Emotion Classifier for the Sports Domain on Twitter"

El viernes 12/7/2019 en el aula B22, los TFMs:

  • 9:00 José Fernández, "Design of an Emotional Lighting System based on Sentiment Analysis of Twitter"
  • 9:20 Enrique Sánchez, "Design and Development of an Emotion-aware Learning Analytics system based on Machine Learning Techniques and Semantic Task Automation"
  • 9:40 Eduardo Merino, "Design and Development of a Social Choice Model Simulation for occupant welfare in Smart Buildings based on a Blockchain solution"

This week the results of the project H2020 Trivalent are being evaluated in Rome by the LEA (Law Enforcement Agency) partners.

In particular, the LEAs participating in the meeting are Madrid Municipal Police (Spain), Royal Military Academy (Belgium),  Local Police Voorkempen (Belgium), Ministero della Giustizia – Polizia Penitenziaria (Italy), Regional Police  Headquarters in Radom (Poland)Bureau of Prevention of the National Police Headquarters of the Republic of Poland (Poland), Ministry of the Interior – Department of Public Security (Italy), The State Police of Latvia (Latvia), Portuguese Prison and Probation Service (Portugal), Local Police of Turin (Italy), Provincial Police Headquarters in Gdansk (Poland) and Albanian State Police (Albania). 

The project has developed a dashboard for radicalization monitoring in news, lead by GSI, Universidad Politécnica de Madrid, as well as a tool for evaluating the social and private radicalization level of Twitter accounts, lead by Open University.


The paper GSI-UPM at SemEval-2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual detection of Hate speech against Immigrants and Women on Twitter, by Diego Benito, Óscar Araque, and Carlos A. Iglesias has been published at the Thirteenth International Workshop on Semantic Evaluation (SemEval-2019).

The SemEval workshop focuses on the evaluation and comparison of systems that can alyse diverse semantic phenomena in text with the aim of extending the current state of the art in semantic analysis and creating high quality annotated datasets in a range of increasingly challenging problems in natural language semantics. In particular, SemEval-2019 task 5 aims at detecting hate speech featured by two specific different targets, immigrants and women, in a multilingual perspective, for Spanish and English.

The publication represents the first major achievement of the Intelligent Systems Group in the field of hate speech, reflected in an honorable fifth position in the Spanish sub-task A and in the development of the best European system in the same sub-task.

Abstract. This paper describes the GSI-UPM system for SemEval-2019 Task 5, which tackles multilingual detection of hate speech on Twitter. The main contribution of the paper is the use of a method based on word embeddings and semantic similarity combined with traditional paradigms, such as n-grams, TF-IDF and POS. This combination of several features is fine-tuned through ablation tests, demonstrating the usefulness of different features. While our approach outperforms baseline classifiers on different sub-tasks, the best of our submitted runs reached the 5th position on the Spanish sub-task A.

The SemEval-2019 workshop was held June 6-7, 2019 in Minneapolis, USA, collocated with the Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019).