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Related lectures (30)
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Neuro-symbolic Representations: Commonsense Knowledge & Reasoning
Delves into neuro-symbolic representations for commonsense knowledge and reasoning in natural language processing applications.
Knowledge Representation: Introduction
Covers knowledge representation in AI, logical inference, and applications in various domains.
Matrix Factorization: Information Extraction
Explores matrix factorization for information extraction, Bayesian ranking, and relation embeddings.
Knowledge Inference
Explores knowledge inference, embedding techniques, and schema matching in data integration.
Information Systems Overview
Covers the overview of information systems, including real-world models, data types, and model evaluation.
Entity & Information Extraction
Explores knowledge extraction from text, covering key concepts like keyphrase extraction and named entity recognition.
Knowledge Representation: Semantics and Data Structures
Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.
Expert Systems: Backward Chaining
Explores expert systems, backward chaining, and uncertainty through fuzzy logic in practical applications.
Semantic Web: Knowledge Graphs
Explores knowledge representation, information extraction, and the Semantic Web vision, emphasizing standardization, mapping, and ontologies in structuring data.
Information Systems: Overview
Covers the overview of information systems, data modeling, managing data, and the distinction between data and information.
