Extracting the names of genes and gene products with a hidden Markov model
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Hierarchical clustering of words
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Introduction: named entity recognition in biomedicine
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
Term identification in the biomedical literature
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
Enhancing automatic term recognition through recognition of variation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
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In this article we present an integrated knowledge-mining system for the domain of biomedicine, in which automatic term recognition, term clustering, information retrieval, and visualization are combined. The primary objective of this system is to facilitate knowledge acquisition from documents and aid knowledge discovery through terminology-based similarity calculation and visualization of automatically structured knowledge. This system also supports the integration of different types of databases and simultaneous retrieval of different types of knowledge. In order to accelerate knowledge discovery, we also propose a visualization method for generating similarity-based knowledge maps. The method is based on real-time terminology-based knowledge clustering and categorization and allows users to observe real-time generated knowledge maps, graphically. Lastly, we discuss experiments using the GENIA corpus to assess the practicality and applicability of the system.