Djiroun, R., Guesssoum, M.A., Boukhalfa, K. and BENKHELIFA, Elhadj (2018) A novel cloud services recommendation system based on automatic learning techniques. Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2017-O. pp. 598-605. ISSN 2161-5330
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Abstract or description
The Cloud Computing technology is evolving constantly but essence remains the same that is to offer distinct cost saving opportunities by consolidating and restructuring information technology as a service. With the continuously increasing cloud provisions, cloud consumers start to have difficulties to find the best relevant services that suit their requirements. Therefore, selecting best services by cloud users is becoming a greater challenge. In this paper, we present a framework of services' recommendation system in a Cloud environment, using automatic learning techniques. The system aims at finding the services that suit the interests and preferences of cloud consumers by combining content based and behaviour based recommendations. In this paper, we present, USTHBCLOUD, a cloud services recommendation prototype evaluated with an experimental study. © 2017 IEEE.
Item Type: | Article |
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Additional Information: | Presented at The Conference of 14th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2017 ; Conference Date: 30 October 2017 - 3 November 2017; Conference Code:135250 |
Faculty: | School of Computing and Digital Technologies > Computing |
Depositing User: | Library STORE team |
Date Deposited: | 13 Jun 2018 15:36 |
Last Modified: | 24 Feb 2023 13:51 |
URI: | https://eprints.staffs.ac.uk/id/eprint/4421 |