Paper Info
Title
Semi-Autonomous Rule Acquisition Framework using Controlled Language and Ontology
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.
Year
Venue
Keywords
2009
ICAART 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE
Rule extraction,Controlled language set,Ontology,Rule Markup Language,XRML
Field
DocType
Citations 
Ontology (information science),Ontology,RDF query language,Computer science,Data control language,Object language,Artificial intelligence,Natural language processing,Universal Networking Language,Upper ontology,Semantic Web Rule Language
Conference
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Mye M. Sohn18316.87
Yungyu Choi200.34