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Related lectures (32)

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Covers the creation and encoding of ontologies, modeling RDF statements, syntax, and classification.

Covers Distributed Information Systems challenges, including autonomy, heterogeneity, trust evaluation, and privacy protection.

Covers knowledge representation in AI, logical inference, and applications in various domains.

Explores information extraction, knowledge inference, taxonomy induction, and entity disambiguation.

Explores adjacency lists, locality, similarity, and efficient representation in link indexing.

Explores Text Understanding, focusing on Named Entities, Information Extraction, and Machine Reading methods.

Explores matrix factorization for information extraction, Bayesian ranking, and relation embeddings.

Explores data-driven sustainability, emphasizing the importance of data representation in design and manufacturing processes.

Explores Semantic Web concepts, RDF syntax, and knowledge representation using RDF statements and Schema.org.