Ontology based Concept Extraction and Classification of Ayurvedic Documents

India is rich with its culture and heritage. It is known for its traditional medicinal system and it is mentioned even in the ancient Vedas and other scriptures also. In India, Traditional Medical system includes Ayurveda, yoga, siddha, Unani, and homeopathy. Biomedical Text Mining (BioTM) is aiming at the extraction of novel, non-trivial information from the large amounts of biomedical related documents. This unstructured bio medical document holds greater knowledge about medical diagnostics, treatment, and prevention. Ontology plays a vital role in deep understanding of information. It is the building block of the Semantic Web and considers it’s important on the semantic clarity of concepts and entities. The main objective is to search the most relevant content from this huge set of text by understanding the meaning of conceptual terms. We proposed Ontology based Concept Extraction and Classification in which the domain ontology and semantic document description was used to improve classification accuracy. The results show that the classification accuracy of proposed algorithm outperforms than the other existing supervised machine learning algorithm. To further prove the efficiency of the model, experiments were conducted by giving different queries and the results are compared with other existing methods. The results show that the content retrieved by the proposed model was most relevant when compared with existing system.