Information Extraction: Methods and Applications

This lecture covers various methods for information extraction, including traditional retrieval methods, embedding-based methods, and supervised learning. It explores topics such as hand-written patterns, supervised learning for IE, distant supervision, and matrix factorization. The lecture also delves into taxonomy induction, discussing the process of learning relevant terms and their relationships to build a taxonomy structure. Examples and approaches for finding hyponyms and hypernyms are presented, along with the use of distant supervision and matrix factorization for extracting related facts from documents.