अमूर्त

Information retrieval for biomedicine applications through linked open data based optimization model

Senthilselvan N, Subramaniyaswamy V, Sekar KR

In biomedical, objective of the semantic web is a pillar to connect plenty number of related data for information. Human and machine readable is the main theme behind web of science. Open linked data is the guideline for merging concepts, location and persons. Existing work is employed on Resource Description Framework (RDF) for machine learning purpose, GRDLL, POWDER, R2RML and SHACL are the existing work available in the market. The limitations of RDF for manipulating the data is not providing intellectual information retrieval, SPARQL is the query language playing a vital role. RDF is a lightweight and not possible for creating negative ontology. It is not holds good for negative expressions, cardinal values and metadata. The proposed methodology consisting of try model: (i) Backward chaining methodology in artificial intelligence; (ii) OWL-RDF is an intellectual query retrieval and (iii) Open linked data is used for obtain information’s from heterogeneous sources. It concludes Web Ontology Language (OWL) is the logic based language with a fine interoperability in web contents and always expresses the clear meaning. Using different biomedical datasets HCUP, data.gov, healthdata.gov, HMD, SEER, MHOS, DRUGBASE, and so on, open linked data consume information through the technique called OWL choreography.