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Subject name: Knowledge Graph Engineering |
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Author : Topic content : |
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The course aims to providing motivations, definitions, theorems and techniques for a concrete and effective understanding of what (in the context of computer science) is meant for knowledge and data. Providing also, the basic techniques for analyzing and modelling knowledge and data as well as the basic techniques for data and knowledge integration. Stimulating the students to continue their career with higher interest into data and knowledge representation in their own field of expertise, and to produce computer-processable solutions of relevant problems. This course will cover the following topics: a general methodology (iTelos) for knowledge and data analysis, modeling and integration, an analysis of the state of the art tools and methodologies for data analysis, modeling and integration, an introduction to ontologies, Extended HR models and linguistic resources. This is a hands-on, lab and experiment-based course. Students will be given a data analysis/modelling/integration problem that they will have to solve, possibly, while taking the class. During the experiment, students will have to apply to the problem the notions introduced in class.
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