Corpus-based thematic analysis
Text-based intelligent systems
Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Learning ontologies from natural language texts
International Journal of Human-Computer Studies
A step towards the detection of semantic variants of terms in technical documents
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Exogeneous and endogeneous approaches to semantic categorization of unknown technical terms
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
The state of the art in ontology learning: a framework for comparison
The Knowledge Engineering Review
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We describe the early stage of our methodology of knowledge acquisition from technical texts. First, a partial morpho-syntactic analysis is performed to extract "candidate terms". Then, the knowledge engineer, assisted by an automatic clustering tool, builds the "conceptual fields" of the domain. We focus on this conceptual analysis stage, describe the data prepared from the results of the morpho-syntactic analysis and show the results of the clustering module and their interpretation. We found that syntactic links represent good descriptors for candidate terms clustering since the clusters are often easily interpreted as "conceptual fields".