For detailed information please refer to:
On completion of this course, students should be able:
• To understand the basic concepts and tasks of Natural Language Processing (NLP), especially for analyzing written textual resources
• To understand the modelling principles, rationale, and possible usages, of popular linguistic resources (e.g, WordNet) used in NLP-enabled applications
• To understand the basic concepts and technologies behind Semantic Web, Linked Data, and Knowledge Graphs
• To query the content of Semantic Web repositories to inspect and access their content
• To understand the modelling principles, rationale, and possible usages, of popular Semantic Web resources (e.g., DBpedia)
The main part of the lesson will be dedicated to present and discuss the tools, techniques, and resources used in NLP for analyzing written textual resources, as well as in the Semantic Web, while the remaining part will be a “hands-on” session with some of them.
The course will cover:
• Natural Language Processing (NLP) resources: WordNet, etc.
• Natural Language Processing (NLP) tasks, such as tokenization, Part-Of-Speech tagging, Dependency tagging, Word Sense Disambiguation, Named Entity Recognition and Classification, Coreference Resolution, Entity Linking, Semantic Role Labeling
• Text Analysis tools, such as Voyant
• Semantic Web and Linked Data technologies: RDF, OWL, SPARQL
• Semantic Web and Linked Data resources: LOD cloud, DBpedia, etc.
|Francesca Tomasi||Metodologie informatiche e discipline umanistiche (Edizione 1)||Carocci||2008||9788843043033|
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