Mining Structures of Factual Knowledge from Text

Discover innovative insights in "Mining Structures of Factual Knowledge from Text" by Xiang Ren, published by Springer International Publishing AG in 2018. This engaging paperback edition spans 183 pages and offers a fresh perspective on structure extraction methods. Unlike traditional techniques that heavily depend on human-annotated data for model training, Ren introduces an effort-light approach that utilizes human-curated facts from external knowledge bases as distant supervision. This method effectively harnesses the rich data redundancy found in extensive text corpora to enhance context understanding. Ideal for researchers and practitioners in the field, this book is a must-have for anyone looking to advance their knowledge in the extraction of factual information from text. Explore the future of knowledge mining with this essential resource.