Ontology Mapping of Indian Medicinal Plants with Standardized Medical Terms

Abstract

Problem statement: World Wide Web (WWW) consisting large volume of information related with medicinal plants. However health care recommendation with Indian Medicinal Plants becomes complicated because valuable Information about medicinal resources as plants is scattered, in text form and unstructured. Search engines are not quite efficient and require excessive manual processing. Therefore search becomes difficult for the ordinary users to find the medicinal uses of herbal plants from the web. And another problem is that the domain experts could not able to map the medicinal uses of herbal plants with the existing standardized medical terms. Mapping the existing ontology introduces the problem of finding the similarity between the terms and relationships. Finding the solution to perform automatic mapping is another major challenge to be solved. Approach: To address these issues we developed a Knowledge framework for the Indian Medicinal Plants (KIMP). Knowledge framework includes the ontology creation, user interface for querying the system. Jena is used to build semantic web applications with the ontology representation of Resource Description Framework (RDF) and Web Ontology Language (OWL). SPARQL Protocol and RDF Query Language (SPARQL) is used to retrieve various query patterns. Automated mapping is achieved by considering lexical and edge based relatedness. Results: The user interface is demonstrated for five thousand concepts, which gives the related information from Wikipedia web page in three languages. Mapping recommendation by the lexical similarity Jaccard algorithm gives 27% and Jaro Winkler algorithm gives 60%. Edge based relationship using WuPalmer algorithm gives 93% mapping recommendation. These are analyzed and compared with our algorithm based on WuPalmer gives more specific mapping results than WuPalmer with 71%. Conclusion: Thus it possible to find the specific resultant web page based on the user requirement in three different languages. The mapping with standardized ontology gives more improvement in analyzing the performance of the medicinal plants and their uses.