Expert System for Healthseekers by Using Local Mining and Global Learning
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 4
Abstract
In this new era on the popularity of internet has made the people to examine their health status before they knock the door of the doctors. This motivated us to propose a system, which helps the healthcare seekers by bridging the vocabulary gap between health seekers and providers. We proposed a novel scheme for retrieving the answers forthwith by the system using following tactics namely Local Mining, Global Learning .In local mining the posted query undergoes Natural language processing which entail of three processes Noun phrase extractor, stop word remover and Spell checker. As corollary a key word is extracted then it is normalized into medical terminology as the result of local mining , a corpus aware terminology generated automatically normalized medical terms are indexed using Invert indexing to ensure the immediate retrieval of result. The approach of global learning is used to enhance the local mining through identifying the missing medical terms from resource PDF using lexical similarities and analysis it to derive the conclusion In case of lacking exact information in our system then the query is forward to experts thus making our system knowledge to answered all the queries posted by health seekers, which overcome delayed cross system operability and the inter usability.
Authors and Affiliations
Mrs. S. Suganya Devi, Kavitha. U, Krithika. K, Leelapriskila. R
Keywords
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- EP ID EP21868
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