Concept

Semantic network

Related lectures (24)

Explores lexical semantics, word sense, semantic relations, and WordNet, highlighting applications in language engineering and information retrieval.

Semantic Web & Information Extraction

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

Understanding Knowledge Graphs

Explores the concept of Knowledge Graphs and their role in data integration and semantic understanding, showcasing real-world examples and applications.

Word Embeddings: Modeling Word Context and Similarity

Covers word embeddings, modeling word context and similarity in a low-dimensional space.

Using Enums: Coding Information with Constants

Covers the use of the enum keyword to define integer constants and improve code readability in programming.

Human Body Capture: Motion Reconstruction and Synthesis

Explores human body capture, motion reconstruction, and synthesis in 3D scenes, including markerless capture and generative motion models.

Distributed Information Systems: Overview and Challenges

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

Word Embeddings: Glove and Semantic Relationships

Explores word embeddings, Glove model, semantic relationships, subword embeddings, and syntactic relationships.

Data Privacy in eHealth Research

Explores data privacy challenges and perspectives in eHealth research, focusing on GDPR compliance, sensitive health data management, and decentralized agents.

Virtual Human Crowds: Behavior and Simulation

Explores virtual human crowds, object manipulation, visual attention, and crowd simulation techniques, including path planning and exposure therapy.

How to get robots to understand the world

Discusses enabling robots to understand the world like humans through semantic understanding and affordance learning.

Word Embeddings: Introduction and Applications

Introduces word embeddings, explaining how they capture word meanings based on context and their applications in natural language processing tasks.

Semantic Modelling: Tabular Data and RDF

Introduces semantic modelling through tabular data and RDF, covering relational databases, schema migration, future-proof schemata, SPARQL querying, and metaknowledge limitations.

Metadata Ontologies and Brain Atlases

Explores metadata standards, the Gene Ontology, and brain atlases in neuroscience.

Word Embeddings: Models and Applications

Explores word embeddings, models like CBOW and Skipgram, Fasttext, Glove, subword embeddings, and their applications in document search and classification.

Neural Word Embeddings: Learning Representations for Natural Language

Covers neural word embeddings and methods for learning word representations in natural language processing.

Music and Emotion: Understanding Expressive Communication

Explores the communication differences between music and language, models of emotion, and how emotions can be measured in music.

Discrete Optimization: Traveling Salesman Problem

Covers the traveling salesman problem, modeling, constraints, additional constraints, and network representation.

Natural Language Generation: Evaluating Text Quality

Covers the evaluation methods for natural language generation systems, including metrics and human assessments of generated text quality.

Scanning Electron Microscopy: Basics

Covers the basics of Scanning Electron Microscopy, including electron-sample interactions, detectors, sample preparation, image formation, resolution, and contrasts in SEM images.