Search the World's Largest Database of Information Science & Technology Terms & Definitions
InfInfoScipedia LogoScipedia
A Free Service of IGI Global Publishing House
Below please find a list of definitions for the term that
you selected from multiple scholarly research resources.

What is NKRL Inference Engine(s)

Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
Software modules that, following the ‘inference by resolution’ general paradigm and making use of (complex) chronological backtracking techniques, implement the different ‘reasoning steps’ included in the NKRL inference rules.
Published in Chapter:
Using Rules in the Narrative Knowledge Representation Language (NKRL) Environment
Gian Piero Zarri (University Paris Est and LISSI Laboratory, France)
DOI: 10.4018/978-1-60566-402-6.ch003
Abstract
NKRL is a semantic language expressly designed to deal with all sort of ‘narratives’, in particular with those (‘non-fictional narratives’) of an economic interest. From a knowledge representation point of view, its main characteristics consists in the use of two different sorts of ontologies, a standard, binary ontology of concepts, and an ontology of n-ary templates, where each template corresponds to the formal representation of a class of elementary events. Rules in NKRL correspond to high-level reasoning paradigms like the search for causal relationships or the use of analogical reasoning. Given i) the conceptual complexity of these paradigms, and ii) the sophistication of the underlying representation language, rules in NKRL cannot be implemented in a (weak) ‘inference by inheritance’ style but must follow a powerful ‘inference by resolution’ approach. After a short reminder about these two inference styles, and a quick introduction of the NKRL language, the chapter describes in some depth the main characteristics of the NKRL inference rules.
Full Text Chapter Download: US $37.50 Add to Cart
eContent Pro Discount Banner
InfoSci OnDemandECP Editorial ServicesAGOSR