Entity Disambiguation and Link Prediction

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 1 of 4

Information Extraction & Knowledge Inference

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

Entity Disambiguation

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

Knowledge Inference: Entity Disambiguation and Graph Embeddings

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

Entity Disambiguation

Explores entity disambiguation techniques, including NER, Viterbi algorithm, and GPT models, emphasizing prompt design and in-context learning.

Information Extraction: Methods and Applications

Explores methods for information extraction, including traditional and embedding-based approaches, supervised learning, distant supervision, and taxonomy induction.

Knowledge Inference for Graphs

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

Knowledge Modeling: Introduction

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

Semantic Web & Information Extraction

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

Entity & Information Extraction

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

Information Extraction: Algorithms and Techniques

Explores algorithms and techniques for information extraction, including Viterbi algorithm, named entities recognition, and distant supervision.