Lectures related to Inference engine

Inference Engines: Resolution and Horn Clauses

Covers inference engines based on resolution, Horn clauses, filtering, and unification in artificial intelligence.

Information Extraction & Knowledge Inference

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

Expert Systems: Backward Chaining

Explores expert systems, backward chaining, and uncertainty through fuzzy logic in practical applications.

Knowledge Inference: Entity Disambiguation and Graph Embeddings

Explores entity disambiguation, graph embeddings, scoring functions, and learning methods.

Semantic Web: Exercise Solutions

Explains exercise solutions on the semantic web using dictionaries and inference rules.

Knowledge Inference for Graphs

Explores knowledge inference for graphs, discussing label propagation, optimization objectives, and probabilistic behavior.

Knowledge Representation: Introduction

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

Link Prediction: Knowledge Inference

Discusses link prediction in knowledge graphs and models like TransE.

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Brain region atlases: Evolution

Explores the evolution of brain region atlases through connectivity-based parcellation and cluster formation criteria.

Semantic Web: Modeling and Ontologies

Explores the Semantic Web, database schemas, XML data model, and ontologies.

Knowledge Inference

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Knowledge Modeling: Introduction

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

Entity Disambiguation

Explores Entity Disambiguation, linking text mentions to a knowledge base, coherence in entity graphs, and Personalized PageRank.

Bayesian Extremes: MCMC Analysis

Explores Bayesian techniques for extreme value problems, focusing on MCMC analysis and the importance of proper prior information.

Foundations of Information Systems: Course Overview and Key Concepts

Introduces the course on information systems, covering its structure, objectives, and foundational concepts essential for understanding data management and decision-making.

Diagnostic: Abduction and Consistency

Explores diagnostic problems, emphasizing abduction and consistency in finding faulty components based on observed symptoms and measurements.