An Ontology-based Approach to Support Text Mining and Information Retrieval in the Biological Domain
Khaled Khelif (INRIA Sophia Antipolis, France)
Rose Dieng-Kuntz (INRIA Sophia Antipolis, France)
Pascal Barbry (IPMC, Sophia Antipolis, France)
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: Corese, NLP, life science, ontologies, semantic annotation, semantic web
Categories: H.3.1, H.3.3, M.0, M.7