Knowledge Inference

Related lectures (32)

Explores Semantic Web, ontologies, information extraction, key phrases, named entities, and knowledge bases.

Explores manual creation of knowledge bases and challenges in knowledge extraction from text.

Explores data modeling concepts, SQL implementations, and practical applications in handling missing data.

Covers the overview of information systems, including real-world models, data types, and model evaluation.

Covers the origins and types of NoSQL databases, focusing on MongoDB and CRUD operations.

Covers Distributed Information Systems, key tasks, methods, projects, evaluation, and exam support.

Explores knowledge extraction from text, covering key concepts like keyphrase extraction and named entity recognition.

Introduces fundamental concepts of data management, including data models, databases, and key tasks.

Covers the representation of mathematical models, functions, and data structures in information systems.

Discusses link prediction in knowledge graphs and models like TransE.

Explores information extraction using classifiers, features, and syntactic analysis.

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