Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Advances in Neural Information Processing Systems 5, [NIPS Conference]
A Semantic Web Primer
Discovering complex matchings across web query interfaces: a correlation mining approach
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Ontology-Driven Web Services Composition Platform
CEC '04 Proceedings of the IEEE International Conference on E-Commerce Technology
Semantic integration: a survey of ontology-based approaches
ACM SIGMOD Record
Towards Ontology Generation from Tables
World Wide Web
Efficiently Mining Frequent Embedded Unordered Trees
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Discovering shared conceptualizations in folksonomies
Web Semantics: Science, Services and Agents on the World Wide Web
PORSCHE: Performance ORiented SCHEma mediation
Information Systems
Complex Schema Match Discovery and Validation through Collaboration
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
A hybrid approach for learning concept hierarchy from Malay text using artificial immune network
Natural Computing: an international journal
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Today, ontologies are being used to model a domain of knowledge in semantic web. OWL is considered to be the main language for developing such ontologies. It is based on the XML model, which inherently follows the hierarchical structure. In this paper we demonstrate an automatic approach for emergent semantics modeling of ontologies. We follow the collaborative ontology construction method without the direct interaction of domain users, engineers or developers. A very important characteristic of an ontology is its hierarchical structure of concepts. We consider large sets of domain specific hierarchical structures as trees and apply frequent sub-tree mining for extracting common hierarchical patterns. Our experiments show that these hierarchical patterns are good enough to represent and describe the concepts for the domain ontology. The technique further demonstrates the construction of the taxonomy of domain ontology. In this regard we consider the largest frequent tree or a tree created by merging the set of largest frequent sub-trees as the taxonomy. We argue in favour of the trustabilty for such a taxonomy and related concepts, since these have been extracted from the structures being used with in the specified domain.