|Title||Interpretation of Knowledge Discovery System on formulation of Gene Disease Relationship.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Sumathi, P, Prabavathy, K|
|Journal||International Journal of Applied Engineering Research|
The flare up information is owing to high production of biomed corpus. By which, it detonates on increased availability solutions for storing, organizing, and retrieving the outsized text data. In this intend, Knowledge Discovery System (KDS) is designed to unlock the knowledge stored in natural language of biomed corpus to tune researchers. It extracts named entities like Genes and disease from unstructured textual data through the identification and exploration of interesting patterns and its relationship. It compares different documents, and relevance of the documents by incorporating Gene Ontology (GO) and disease annotation to hit upon patterns and trends across multiple documents. Named Entity Recognition (Gene& Disease) by Probabilistic Latent Semantic Indexing and Analysis with BM25 and stimulating Named Entity Relationship (formulation of Gene Disease relationship) by Logistic Model of dictionary construction method. Testing the GDD algorithm indicates that it perk up better identification of Gene Disease relationship result with all previously suggested methods.