Learning outcomes

The course’s purpose is to provide the fundamental concepts of knowledge representation both respect to the abstract problem of defining a domain ontology and to the problem of indexing documental domains. Specifically, both logical techniques and machine learning techniques for classification and analysis of documents. At the end of the course the student shall have acquired knowledge bunches on knowledge representation and its applications, and also shall be comfortable with the technical aspects of statistical natural language processing, understanding and connecting both aforementioned aspects while relating them to document repositories, especially the world wide web. These bunches of knowledge shall habilitate the student in: i) building formal ontologies; ii) managing ontology alignement; iii) managing document retrieval with indices based on text content; iv) using formal methods for text analysis while combining these with automated reasoning techniques. At the end of the course the student will be able to: i) presenting a conceptual semantic analysis, describing the process that leads a domain expert to the delivery of information needed by the knowledge engineer to deliver a formal ontology describing the interest domain; ii) going further, potentially autonomously, study and research in the field of semantic technologies in several different application fields.