A framework for ontology based rule acquisition from web documents

Authors:
Sangun Park;Juyoung Kang;Wooju Kim
Affiliations:
Division of Business Administration, Kyonggi University, Suwon, South Korea;Department of E-Business, School of Business, Ajou University, Suwon, Korea;Department of Information and Industrial Engineering, Yonsei University, Seoul, Korea
Venue:
RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
Year:
2007

Citing 9
Cited 1

Heuristics: intelligent search strategies for computer problem solving

Heuristics: intelligent search strategies for computer problem solving
WordNet: a lexical database for English

Communications of the ACM
Extracting focused knowledge from the semantic web

International Journal of Human-Computer Studies
Automatic Ontology-Based Knowledge Extraction from Web Documents

IEEE Intelligent Systems
An Information-Theoretic Definition of Similarity

ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information

DS-8 Proceedings of the IFIP TC2/WG2.6 Eighth Working Conference on Database Semantics- Semantic Issues in Multimedia Systems
Rule identification from web pages by the XRML approach

Decision Support Systems
Using information content to evaluate semantic similarity in a taxonomy

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
F-OWL: an inference engine for semantic web

FAABS'04 Proceedings of the Third international conference on Formal Approaches to Agent-Based Systems

Ontology population and enrichment: state of the art

Knowledge-driven multimedia information extraction and ontology evolution

Quantified Score

Hi-index	0.00

Visualization

Abstract

Rule based systems and agents are important applications of the Semantic Web constructs such as RDF, OWL, and SWRL. While there are plenty of utilities that support ontology generation and utilization, rule acquisition is still a bottleneck as an obstacle to wide propagation of rule based systems. To automatically acquire rules from unstructured texts, we develop a rule acquisition framework that uses a rule ontology. The ontology can be acquired from the rule base of a similar site, and then is used for rule acquisition in the other sites of the same domain. The procedure of ontology-based rule acquisition consists of rule component identification and rule composition. The former uses stemming and semantic similarity to extract variables and values from the Web page and the latter uses the best-first search method in composing the variables and values into rules.