Finding and learning explanatory connections from scientific texts
Fernando Gómez, Carlos Segami · 2003
A theory for detecting and learning the explanatory connections between sentences in scientific texts is presented. A program called SNOWY that embodies the theory is also described. The knowledge in the program is organized around the notions of analytic and empirical knowledge. Analytic knowledge encompasses very general rules which are valid across any domain, while empirical knowledge includes rules whose validity is domain dependent. Examples of these rules and their representation are given.>