SCISOR: extracting information from on-line news
Communications of the ACM
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Proceedings of the third annual conference on Autonomous Agents
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AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Wrapper induction: efficiency and expressiveness
Artificial Intelligence - Special issue on Intelligent internet systems
An integrated, dual learner for grammars and ontologies
Data & Knowledge Engineering
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Machine Learning
ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
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ECML '00 Proceedings of the 11th European Conference on Machine Learning
EKAW '99 Proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management
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ICCS '99 Proceedings of the 7th International Conference on Conceptual Structures: Standards and Practices
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ICCS '01 Proceedings of the 9th International Conference on Conceptual Structures: Broadening the Base
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ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
Text Mining at Detail Level Using Conceptual Graphs
ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
User-Centred Ontology Learning for Knowledge Management
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
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ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Toward semantic understanding: an approach based on information extraction ontologies
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Addressing the Ontology Acquisition Bottleneck Through Reverse Ontological Engineering
Knowledge and Information Systems
Survey of semantic annotation platforms
Proceedings of the 2005 ACM symposium on Applied computing
Unsupervised learning of generalized names
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
University of Sheffield: description of the LaSIE system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
An integrated architecture for shallow and deep processing
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites
Computational Linguistics
Programming with data frames for everyday data items
AFIPS '80 Proceedings of the May 19-22, 1980, national computer conference
CASEE: a hierarchical event representation for the analysis of videos
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Adaptive information extraction from text by rule induction and generalisation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Employing a Domain Specific Ontology to Perform Semantic Search
ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
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The main claim of this paper is that machine learning can help integrate the construction of ontologies and extraction grammars and lead us closer to the Semantic Web vision. The proposed approach is a bootstrapping process that combines ontology and grammar learning, in order to semi-automate the knowledge acquisition process. After providing a survey of the most relevant work towards this goal, recent research of the Software and Knowledge Engineering Laboratory (SKEL) of NCSR “Demokritos” in the areas of Web information integration, information extraction, grammar induction and ontology enrichment is presented. The paper concludes with a number of interesting issues that need to be addressed in order to realize the advocated bootstrapping process.