An Enhanced Keyword Search Using Flexible Ranking Over Differential Query Services in Cloud

Cloud computing has emerged as a major driver for reducing the information technology costs incurred by organizations. In a cost-sensitive environment, an organization is willing tolerate a certain threshold of delay while retrieving information from the cloud. We first review a private -based file retrieval scheme that was EIRQ, users can retrieve the desired percentage of files by assigning ranks to queries. This feature is useful if the user is only interested in a subset of all the matched files. By further reducing the communication cost incurred on the cloud, the existing EIRQ schemes make the private searching technique more applicable to a cost-efficient cloud environment. The main drawback is, we simply determine the rank of each file by the highest rank of queries it matches. Since this ranking is not flexible. In this paper we present a more sophisticated ranking system by providing variable weights to the relevance attributes of each file. A flexible ranked search sorts the matches by relevance. This ranking allows the user to find the most (or least) relevant information quickly, rather than sorting through every match in the content collection. This approach improves the user friendly environment as well as it tries to focus on the reduction of communication cost