Efficient mining and recommendation of sparse data through collaborative filtering technique in medical transcriptions

The Recommendation technique plays a major role in today´s real time scenarios. Recent researchers focus on data mining based on the difficulties of recommendation techniques associated with cluster of data. A new methodology for recommendation technique is proposed in this paper. It is related with the information of user´s current selection and previous information of the specific user or group of users. At last, the concluding recommendation is made based on weighing the features of the user´s history. In the proposed system, Medical Record datasets is taken as an input and based on the user´s selection and Disease type, the prediction is done. The operation is implemented using Google App Engine, a cloud platform. The Login module is implemented using Google OAuth.