On October 3rd, Professor Gabriel Valiente was appointed as director of the Computer Science Department, UPC for the next four years.
More information available at:
Date: Thursday July 7 2022
Where: FIB Sala de Juntes B6-planta 1, Campus Nord UPC
Speaker: Renzo Angles, Department of Computer Science, Universidad de Talca, Chile.
Title: “Harnessing the Knowledge: Languages and Models underlying Knowledge Graphs”
A knowledge graph is a large database that integrates information from different data sources with the aim of generating additional information and knowledge. This database is represented by a graph. Thus, the entities are represented by nodes, and the relationships among these entities are represented by edges. The purpose of this presentation is to review the data models used to represent knowledge graphs, the query languages that allow extracting information and the deductive and inductive methods that allow generating knowledge.
Renzo Angles received a degree of Bachelor in Systems Engineering from Universidad Católica de Santa María (Arequipa, Perú), and a Ph.D. degree in Computer Science from Universidad de Chile. He is professor at the Universidad de Talca (Chile) since 2009, and currently is Director of the Department of Computer Science. He is also a researcher in the Millenium Institute for Foundational Research on Data (Chile). His research interests dwell in the intersection of graph databases and the Semantic Web. Specifically, he is currently working on the theory and design of graph query languages, benchmarking of graph/RDF databases, and analysis of proteins using graph technologies.
Professor Miquel Sànchez-Marrè, from Computer Science Department, and KEMLG (link=>https://kemlg.upc.edu/en) Research Group member and IDEAI-UPC (link => https://ideai.upc.edu/en) Research Center member, has published a new book:
M. Sànchez-Marrè (2022). Intelligent Decision Support Systems. Springer Nature Switzerland AG, 2022.
Presents the emergent interdisciplinary field of Intelligent Decision Support Systems (IDSS). It shows how to analyze, to design, to implement, and to validate IDSS in complex systems and describes current issues in integration of different intelligent/numerical/statistical methods.
References and availability:
ISBN: 978-3-030-87789-7 (Print), 978-3-030-87790-3 (eBook)