Efficient Multi Keyword Searching Using Hierarchically Reliable and Ceaseless Minimization Clustering and Improved Learning and Intelligent Optimization Solver Clustering Techniques
【摘 要】 In the contemporary period massive amount of health care information\'s such as Electrical Medical Records (EMR), Health Information Services (HIS), Electronic Health Records (EHR), Personal Health Records (PHR), Tele medicines and so on, are stored ... 更多 >> In the contemporary period massive amount of health care information\'s such as Electrical Medical Records (EMR), Health Information Services (HIS), Electronic Health Records (EHR), Personal Health Records (PHR), Tele medicines and so on, are stored in the database. This health care information\'s are accessed by emergency situation by using keyword searching. The main challenges in the healthcare information is, it gives the irrelevant information which increases the searching time, waiting time and reduces the efficiency of the system. So this paper presents multiple keyword searching based on Clustering formation, which increase the performance of the system and reduces the cost of searching the health care information. The cluster formation of the peers is achieved by using the Hierarchically Reliable and Ceaseless Minimization Clustering (HRCM) algorithm. Then the keywords search by using the Improved Learning and Intelligent Optimization Solver (ILIOS) algorithm. The searching algorithm is based on the reactive research optimization, so, it is capable learning from previous actions and human feedback which produces the efficient results. The combination of these algorithms ensures that the efficient multiple keyword search on health care information systems and reduces the traffic cost. << 收起
