期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：10
页码：2847-2860
出版社：Journal of Theoretical and Applied
摘要：Lately, there is a rapid increase in the demand of CC-Cloud Computing. Companies offering cloud services have are now endowed with new enhancement in their list of services which includes: WB-Web Mining and DM-Data Mining taking into consideration variety of available computing resources. Recently, the RS-Recommender systems are offering improvised services to the users by minimizing the user�s cost time so as to quickly achieve the required outcome. The approach of Cloud computing is the need of the hour and has turned out to be the computing infrastructure for the present generation computing. There exist numerous cloud vendors offering varied sort of cloud services as mentioned in the SLC - Service Level Catalogue. Selecting the best suitable cloud service for particular applications tends to be a difficult task. Among various challenges and issues faced by the CSP (cloud service provider), disappointment among the users related to the CSP stands the prime most. The reason being that there exists numerous cloud services having same functionalities but different non-functional attributes. In order to identify the most appropriate CSP the most suitable cloud service attributes and selected quality along with the feedback of the users is taken into consideration. In this research work proposed to achieve to Rating based service selection techniques for best cloud services selection processing and Multi-step matching algorithm for predict the best cloud service to be recommended personalized users. The main objective of this work is to recommend a methodology for choosing the most appropriate cloud service for the users from the environment of cloud computing. The mechanism updates the cloud service provider dynamically in order to deliver services. The constructed structure and related workflow involves following stages: first-cloud service filtering, second - selection, third - prediction, lastly, Ranking and recommendations. The CSS (cloud services selection) then handles the system by employing Rating Based Selecting Techniques, further, selecting quality and most appropriate cloud services is predicted by adopting MSM- Multi-Step Matching Algorithm and eventually, RBSR - Requirement Based Similarity Ranking Techniques (RBSR) is incorporated for suggesting the top most cloud service to be ranked to the personalized user. The scope of this research is to recommend best cloud service for personalized user. It�s observed and analyzed that the personalized Cloud services recommendation system is yielding better performance compared to the present proposed techniques.
关键词：Cloud services; Multi-Step Matching Algorithm; Requirement Based Similarity Ranking Technique; Service Level Catalogue; Cloud Service Selection; web mining; and recommendation system
