JUCS - Journal of Universal Computer Science 13(12): 1881-1907, doi: 10.3217/jucs-013-12-1881
An Ontology-based Approach to Support Text Mining and Information Retrieval in the Biological Domain
expand article infoKhaled Khelif‡, Rose Dieng-Kuntz‡, Pascal Barbry§
‡ INRIA Sophia Antipolis, France§ IPMC, Sophia Antipolis, France

Corresponding author: Khaled Khelif ( khaled.khelif@sophia.inria.fr )

© Khaled Khelif, Rose Dieng-Kuntz, Pascal Barbry.
This article is freely available under the J.UCS Open Content License.
Citation: Khelif K, Dieng-Kuntz R, Barbry P (2007) An Ontology-based Approach to Support Text Mining and Information Retrieval in the Biological Domain. JUCS - Journal of Universal Computer Science 13(12): 1881-1907. https://doi.org/10.3217/jucs-013-12-1881
Open Access
Abstract
This paper describes an ontology-based approach aiming at helping biologists to annotate their documents and at facilitating their information retrieval task. Our approach, based on semantic web technologies, relies on formalised ontologies, semantic annotations of scientific articles and knowledge extraction from texts. We propose a method/system for the generation of ontology-based semantic annotations (MeatAnnot) and a system allowing biologists to draw advanced inferences on these annotations (MeatSearch). This approach was proposed to support biologists working on DNA microarray experiments in the validation and the interpretation of their results, but it can probably be extended to other massive analyses of biological events (as provided by proteomics, metabolomics...).
Keywords
semantic web, ontologies, semantic annotation, life science, NLP, Corese