Cloud is a heterogeneous group of services and one of that is data storage. Generally the data stored in cloud is in very large amount, retrieval of the same requires precision and accuracy. Many methods are being proposed to retrieve data from cloud and strict match algorithm is one of them. In this paper we use of Levenshtein distance to find out the amount of similarity between two different strings. We compare the keyword given by user with our set of words, find out similarity and provide

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... uesses to the user as accurate as possible. 228 Copyright ⓒ 2014 SERSC As we can see in the table above, August has highest similarity with the string entered by the user, i.e., augst and hence it will be provided to the user as prediction. Mechanism Adopted and Tools Used Cloud computing is the leading technology for delivery of reliable, secure, fault-tolerant, sustainable, and scalable computational services. It is not always possible to perform benchmarking experiments in repeatable, dependable, and scalable environments using realworld Cloud environments. A more viable alternative is the use of simulation tools. We make use of NetBeans to simulate our project. We have created the ontology using protégé and integrated the same with NetBeans as .rdf file. Also we have created a web services project in NetBeans which contains a GUI in html file and a backend code in java which searches the keyword entered by user in our database (i.e., RDF file). Results and Discussions Lightweight ontology for the patients, doctors and nurse tables and their relations. Figure 2. lightweight ontology created 7.2 The sample database we created for different patients with their details like blood group, date of birth, diseases they are suffering from and doctors assigned to them.