Topics and Entities in HeinOnline
Using a combination of human curation along with natural language processing and machine learning, we’ve extracted narrow research concepts and interesting entities from each article in the Law Journal Library database. This has provided a robust foundation of more than 1,500 distinct multidisciplinary concepts (Topics) as well as relevant location, person, and organization information (Entities) which we’ve used to categorize each and every Law Journal Library document.
As we refine and expand our machine learning, our collection of more than 1,500 of these Topics continues to grow. To make Topics even more intuitive, discoverable, and user friendly, we’ve further categorized them into a multi-level taxonomy that we call PathFinder.
Discover how to use HeinOnline’s Topics within PathFinder, or learn more about Entities below.