Retrieving knowledgeable information from cloud using trapezoid-based multi-keyword query ranking with weighted distributed function

Abstract

Collection of information is available in cloud and growing at an exponential rate and this scope makes the organisation and accessing of data critical for efficient use of knowledgeable information. In order to obtain the desired outcome, users heavily rely upon the cloud information retrieval methods. Many research works have been conducted in the field of knowledge related information retrieval. However, effective ranking of complex query pose significant challenges. In this paper, to efficiently rank the query on cloud services a method called, weighted fuzzy multi-keyword rank query (WFM-KRQ) is introduced. This method is based on associating a query with a fuzzy rule, applying a weighted distribution function and a pruning technique based on a threshold value. The proposed encrypted RepeatKeyRotate algorithm effectively improves the performance rate of cloud data sharing services by reducing the processing time and improving the retrieval rate on handling complex queries when compared to the state-of-the-art works.