Alternative ways for knowledge collection, indexing and robust language retrieval.
Definitions are provided of the key entities in knowledge representation for Natural Language Processing (NLP). Starting from the words, which are the natural components of any sentence, both the role of expressions and the decomposition of words into their parts are emphasized. This leads to the notion of concepts, which are either primitive or composite depending on the model where they are created. The problem of finding the most adequate degree of granularity for a concept is studied. From this reflection on basic Natural Language Processing components, four categories of linguistic knowledge are recognized, that are considered to be the building blocks of a Medical Linguistic Knowledge Base (MLKB). Following on the tracks of a recent experience in building a natural language-based patient encoding browser, a robust method for conceptual indexing and query of medical texts is presented with particular attention to the scheme of knowledge representation.
Baud
R H
RH
Division of Medical Informatics, Geneva University Hospital, Switzerland. Robert.Baud@dim.hcuge.ch
Lovis
C
C
Rassinoux
A M
AM
Scherrer
J R
JR
D000043:Abstracting and Indexing; D001185:Artificial Intelligence; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D009626:Terminology as Topic; D018875:Vocabulary, Controlled