Authors:
Mye M. Sohn
and
Yungyu Choi
Affiliation:
Department of Systems Management Engineering, Sungkyunkwan University, Korea, Republic of
Keyword(s):
Rule extraction, Controlled language set, Ontology, Rule Markup Language, XRML.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Ontologies
;
Formal Methods
;
Knowledge Representation and Reasoning
;
Ontologies
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
This paper presents a framework for rule extraction from unstructured web documents. To do so, we adopted the controlled language technique to reduce the burden as well as error of a domain expert and suggest a rule extraction framework that uses ontology, to solve the problem of missing variable and value that may be caused by incomplete natural language. Here, it is referred to as NEXUCE (New rule EXtraction Using ontology and Controlled natural languagE). To evaluate the performance of the NEXUCE framework, the natural language statements were collected from the websites of Internet bookstores and the rule extraction capability was analyzed. As a result, it was proven that NEXUCE can have more than 70% of rule extraction from unstructured web documents.