Parameter Reputation Model for Cloud Service Recommendation and Ranking Using Opinion Mining

Abstract

Enabling effective cloud service recommendation and ranking model helps cloud users settle on brief choices when they are up against by an enormous number of choices. This helps to improve the cloud users’, as well as the service providers’, satisfaction levels. In this paper, parameter reputation-based algorithms are proposed to boost the service selection and ranking. The proposed work employs prominent the parameters of the Service Measurement Index (SMI) standardized by the Cloud Service Measurement Index Consortium (CSMIC). The parameters are systematically analyzed in order to obtain a user review opinion, such as a positive, negative and neutral view about the parameters. Here, both the positive and negative parameter reputations are addressed. The positive parameter reputation increased the cloud users’ choice of service selection and ranking. The negative parameter reputation helped the service providers to realize where they are stand and give them a chance to improve their service provisioning in future endeavors. The detailed experimental results confirm that the proposed models enhance the choice of service selection and ranking.

Keywords

• Cloud computing
• cloud service selection
• opinion mining
• sentiment analysis
• parameter reputation