OntoMiner: bootstrapping ontologies from overlapping domain specific web sites
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
The state of the art in ontology learning: a framework for comparison
The Knowledge Engineering Review
Learning domain ontologies for Web service descriptions: an experiment in bioinformatics
WWW '05 Proceedings of the 14th international conference on World Wide Web
OntoMiner: Bootstrapping and Populating Ontologies from Domain-Specific Web Sites
IEEE Intelligent Systems
Ontology based annotation of text segments
Proceedings of the 2007 ACM symposium on Applied computing
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
On how to perform a gold standard based evaluation of ontology learning
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
An accuracy-enhanced light stemmer for arabic text
ACM Transactions on Speech and Language Processing (TSLP)
ArabOnto: experimenting a new distributional approach for building Arabic ontological resources
International Journal of Metadata, Semantics and Ontologies
Toward a taxonomy of concepts using web documents structure
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
Ontology-based sentiment analysis of twitter posts
Expert Systems with Applications: An International Journal
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Ontologies play a vital role in many web- and internet-related applications. This work presents a system for accelerating the ontology building process via semi-automatically learning a hierarchal ontology given a set of domain-specific web documents and a set of seed concepts. The methods are tested with web documents in the domain of agriculture. The ontology is constructed through the use of two complementary approaches. The presented system has been used to build an ontology in the agricultural domain using a set of Arabic extension documents and evaluated against a modified version of the AGROVOC ontology.