Paper Info
Title
Text-mining and ontologies: new approaches to knowledge discovery of microbial diversity.
Abstract
Microbiology research has access to a very large amount of public information on the habitats of microorganisms. Many areas of microbiology research uses this information, primarily in biodiversity studies. However the habitat information is expressed in unstructured natural language form, which hinders its exploitation at large-scale. It is very common for similar habitats to be described by different terms, which makes them hard to compare automatically, e.g. intestine and gut. The use of a common reference to standardize these habitat descriptions as claimed by (Ivana et al., 2010) is a necessity. We propose the ontology called OntoBiotope that we have been developing since 2010. The OntoBiotope ontology is in a formal machine-readable representation that enables indexing of information as well as conceptualization and reasoning.
Year
Venue
Field
2018
arXiv: Quantitative Methods
Ontology (information science),Biodiversity,Data science,Ontology,Public information,Search engine indexing,Conceptualization,Natural language,Knowledge extraction,Artificial intelligence,Machine learning,Mathematics
DocType
Volume
ISSN
Journal
abs/1805.04107
Proceedings of the 4th International Microbial Diversity Conference. pp. 221-227, ed. Marco Gobetti. Pub. Simtra. ISBN 978-88-943010-0-7, Bari, October 2017
Citations 
PageRank 
References 
0
0.34
3
Authors
4
Name
Order
Citations
PageRank
Claire Nedellec134179.72
Robert Bossy219915.02
Estelle Chaix301.69
Louise Deleger423420.13