Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Mining generalized association rules
Future Generation Computer Systems - Special double issue on data mining
Using text processing techniques to automatically enrich a domain ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Theoretical Aspects of Schema Merging
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Centroid-Based Document Classification: Analysis and Experimental Results
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Automatic Acquisition of Hyponyms
Automatic Acquisition of Hyponyms
Building and maintaining ontologies: a set of algorithms
Data & Knowledge Engineering - NLDB2002
Natural Language Engineering
Web Semantics: Science, Services and Agents on the World Wide Web
Text2Onto: a framework for ontology learning and data-driven change discovery
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Proposed approach for evaluating the quality of topic map,,
MEDI'11 Proceedings of the First international conference on Model and data engineering
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This paper proposes the CITOM approach for an incremental construction of multilingual Topic Maps. Our main goal is to facilitate the user's navigation across documents available in different languages. Our approach takes into account three types of information sources: (a) a set of multilingual documents, (b) a domain thesaurus and (c) all the possible questioning sources such as FAQ and user's or expert's requests about documents. We have been validating our approach with a real corpus from the sustainable construction domain.