Abstract
One of the most determining factors for mining the sequences in terms of service mining in cloud services is time sequence. However, this factor is found to be often ignored and recommendation of services in cloud system is done based on the item mining approach. The problem that we discussed in this paper is addressed by applying the concept of time weight factor in the collection of sequence from which we achieved better result of recommendation from relational sequences. In this paper, we describe a recommendation method of service to user based on his service usage pattern in the system. The recommendation algorithm is based on the mining result of TWSMA algorithm which adopts an innovative approach based on sequences of service usage pattern and then characterizes each set of sequences using multidimensional properties based on user id, time series, and usage frequencies. We take advantage of implementing recommendation in Jyaguchi cloud system in which the user are recommended the services according to the log of service used by the users.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, R., Srikant, R.: Mining Sequential Patterns. In: Proc. of the Eleventh International Conference on Data Engineering, pp. 3–14 (1995)
Shrestha, S.K., Kudo, Y., Gautam, B.P., Shrestha, D.: Multidimensional Service Weight Sequence Mining based on Cloud Service Utilization in Jyaguchi. In: Proc. of the International Multi Conference of Engineers and Computer Scientists, IMECS 2013, vol. I, pp. 301–306 (2013)
Gautam, B.P.: An Architectural Model for Time Based Resource Utilization and Optimized Resource Allocation in a Jini Based Service Cloud. Master Thesis, Shinshu University, Nagano, Japan (2009)
Gautam, B.P., Shrestha, D.: A Model for the Development of Universal Browser for Proper Utilization of Computer Resources Available in Service Cloud over Secured Environment. In: Proc. of the International Multi Conference of Engineers and Computer Scientists, IMECS 2010, vol. I (2010)
Gautam, B.P., Shrestha, S.K., Paudel, D.R.: Utilization of Jyaguchi Architecture for development of Jini Based Service Cloud. Wakkanai Hokusei Gakuen University Journal (11), 7–21 (2011)
Pinto, H., Han, J., Pei, J., Wang, K., Chen, Q., Dayal, U.: Multidimensional Sequential Pattern Mining. In: Proc. of the Tenth International Conference on Information and Knowledge Management (CIKM 2001), pp. 81–88 (2001)
Pei, J., Han, J., Mortazavi-Asl, B., Wang, J., Pinto, H., Chen, Q., Dayal, U., Hsu, M.C.: Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach. IEEE Transactions on Knowledge and Data Engineering 16(10), 1424–1440 (2004)
Oku, K., Tung, T.S., Hattori, F.: Collaborative Filtering for Predicting Users Potential Preferences. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds.) KES 2011, Part IV. LNCS (LNAI), vol. 6884, pp. 44–52. Springer, Heidelberg (2011)
Pazzani, M.J., Billsus, D.: Content-Based Recommendation Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)
Burke, R.: Hybrid Web Recommender Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 377–408. Springer, Heidelberg (2007)
Zhou, B., Hui, S.C., Fong, A.C.M.: Efficient Sequential Access Pattern Mining for Web Recommendations. International Journal of Knowledge-based and Intelligent Engineering Systems 10(2), 155–168 (2006)
Han, M., Wang, Z., Yuan, J.: Mining Constraint Based Sequential Patterns and Rules on Restaurant Recommendation System. Journal of Computational Information Systems 9(10), 3901–3908 (2013)
Zhou, B., Hui, S.C., Chang, K.: An intelligent recommender system using sequential web access patterns. In: Proc. of the 2004 IEEE Conference on Cybernetics and Intelligent Systems, vol. 1, pp. 393–398 (2004)
Khonsha, S., Sadreddini, M.H.: New hybrid web personalization framework. In: Proc. of IEEE 3rd International Conference on Communication Software and Networks, ICCSN, pp. 86–92 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Shrestha, S.K., Kudo, Y., Gautam, B.P., Shrestha, D. (2014). Recommendation of a Cloud Service Item Based on Service Utilization Patterns in Jyaguchi. In: Huynh, V., Denoeux, T., Tran, D., Le, A., Pham, S. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 245. Springer, Cham. https://doi.org/10.1007/978-3-319-02821-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-02821-7_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02820-0
Online ISBN: 978-3-319-02821-7
eBook Packages: EngineeringEngineering (R0)