CSRecommender: A Cloud Service Searching and Recommendation System


Cloud Computing and in particular cloud services have become widely used in both the technology and business industries. Despite this significant use, very little research or commercial solutions exist that focus on the discovery of cloud services. This paper introduces CSRecommender—a search engine and recommender system specifically designed for the discovery of these services. To engineer the system to scale, we also describe the implementation of a Cloud Service Identifier which enables the system to crawl the Internet without human involvement. Finally, we examine the effectiveness and usefulness of the system using real-world use cases and users.

Share and Cite:

Wheal, J. and Yang, Y. (2015) CSRecommender: A Cloud Service Searching and Recommendation System. Journal of Computer and Communications, 3, 65-73. doi: 10.4236/jcc.2015.36007.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Buyya, R., Broberg, J. and Goscinski, A. (2011) Cloud Computing Principles and Paradigms. John Wiley & Sons, Inc., Hoboken.
[2] Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J. and Brandic, I. (2009) Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Future Generation Computer Systems, 25, 599-619.
[3] Mohamed, A. (2009) A History of Cloud Computing. Computer Weekly.
[4] Armbrust, M., Fox, A., Griffith, R. and Joseph, A.D. (2010) A View of Cloud Computing. Communications of the ACM, 53, 50-58.
[5] Staten, J. (2015) Is the IaaS/PaaS Line Beginning to Blue? Forrester Research.
[6] Cusumano, M. (2010) Cloud Computing and SaaS as New Computing Platforms. Communications of the ACM, 53, 27-29.
[7] Gartner Inc. (2015) Gartner Says Worldwide SaaS Revenue within the Enterprise Application Software Market to Surpass $8.5 Billion in 2010. Gartnner.
[8] Capterra (2015) Capterra. http://www.capterra.com/
[9] Nubera eBusiness SL. (2015) GetApp. http://www.getapp.com/
[10] Kang, J. and Sim, K.M. (2010) Cloudle: A Multi-Criteria Cloud Service Search Engine. Asia-Pacific Services Computing Conference, Hangzhou, 6-10 December 2010.
[11] Garg, S.K., Versteeg, S. and Buyya, R. (2013) A Framework for Ranking of Cloud Computing Services. Future Generation Computer Systems, 29, 1012-1023.
[12] Adomavicius, G. and Tuzhilin, A. (2005) Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering, 17, 734-749.
[13] Porter, M. (1980) An Algorithm for Suffix Stripping. Program, 14, 130-137.
[14] Manning, C.D., Raghaven, P. and Schutze, H. (2008) Introduction to Information Retrieval. Cambridge University Press, Cambridge.
[15] Sarwar, B., Karypis, G., Konstan, J. and Riedl, J. (2001) Item-Based Collaborative Filtering Recommendation. Proceedings of the 10th International Conference on World Wide Web, Hong Kong, 1-5 May 2001, 285-295.
[16] Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D. and Sartin, M. (1999) Combining Content-Based and Collaborative Filters in an Online. Worcester Polytechnic Institute, Worcester.
[17] Pham, M.C., Cao, Y., Klamma, R. and Jarke, M. (2011) A Clustering Approach for Collaborative Filtering Recommendation Using Social Network Analysis. Universal Computer Science, 17, 583-604.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.