Title
Finding And Learning Explanatory Connections From Scientific Texts
Abstract
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.
Publication Date
12-1-1989
Number of Pages
85-90
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0024917344 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0024917344
STARS Citation
Gomez, Fernando and Segami, Carlos, "Finding And Learning Explanatory Connections From Scientific Texts" (1989). Scopus Export 1980s. 397.
https://stars.library.ucf.edu/scopus1980/397