Semantic Web & Information Extraction

This lecture covers the concepts of Semantic Web and Information Extraction. It delves into popular ontologies like WordNet, WikiData, and Google Knowledge Graph, explaining semantic relationships such as synonymy, antonymy, hypernymy, and meronymy. The lecture also discusses the process of information extraction, including key phrase extraction and named entity recognition. Tools like Schema.org and Linked Open Data are explored, along with the use of knowledge bases for structured search. The instructor provides insights into the challenges and methods involved in extracting knowledge from documents and creating domain-specific thesauri.