Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A flexible learning system for wrapping tables and lists in HTML documents
Proceedings of the 11th international conference on World Wide Web
Bottom-Up Construction of Ontologies
IEEE Transactions on Knowledge and Data Engineering
RiboWeb: An Ontology-Based System for Collaborative Molecular Biology
IEEE Intelligent Systems
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
Ontology Learning and Its Application to Automated Terminology Translation
IEEE Intelligent Systems
Managing multiple and distributed ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Ontology Generation from Tables
WISE '03 Proceedings of the Fourth International Conference on Web Information Systems Engineering
A Probabilistic Approach for Adapting Information Extraction Wrappers and Discovering New Attributes
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Adaptive information extraction: core technologies for information agents
Intelligent information agents
OILing the way to machine understandable bioinformatics resources
IEEE Transactions on Information Technology in Biomedicine
Pattern-based semantic tagging for ontology population
SOCASE'08 Proceedings of the 2008 AAMAS international conference on Service-oriented computing: agents, semantics, and engineering
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Ontology plays an important role in semantic Web technology since it can effectively represent the domain knowledge. We develop a novel framework for automatically generating the domain knowledge by analyzing different Web sites in a given domain. The idea of our approach is to consider two kinds of information from the Web sites. The first kind of information is the text fragments corresponding to the concepts in the ontology. The other kind of information is the header labels corresponding to the concepts. We design a method for generating the domain ontology by measuring the similarity between the concepts in different Web sites. We have conducted extensive experiments to demonstrate the effectiveness of our approach.