A Trust Aware Product Recommending Scheme for Multiple Cloud using HADOOP Services

Authors

  • A. Owaise Ahmed  Computer Science and Engineering, Anna University, SKP Engineering College, Tiruvannamalai, Tamil Nadu, India
  • K. Abirami  Computer Science and Engineering, Anna University, SKP Engineering College, Tiruvannamalai, Tamil Nadu, India
  • S. Chandrika  Computer Science and Engineering, Anna University, SKP Engineering College, Tiruvannamalai, Tamil Nadu, India
  • M. Janani  Computer Science and Engineering, Anna University, SKP Engineering College, Tiruvannamalai, Tamil Nadu, India

Keywords:

T-broker, cloud, keyword search, content based search, ranking using hadoop

Abstract

Service recommender systems have been shown as irreplaceable tools for yielding worthy recommendations to client. In the recent years, the range of client, services and online information exchange has grown rapidly, producing the big data analysis issue for service recommender systems. Accordingly, the conventional recommender systems frequently suffer from scalability and problems related to efficieny most of existing recommender systems presents the same grades and rankings to various users without considering multiple users' preferences, which fails to meet users' individualize requirements. In this work, to mention the above challenges and presenting a personalized recommendation list for products and recommending the most relevant products to the users effectively. Particularly, keywords are used to point out users' preferences, and hadoop framework is used for storing and processing the data of the client and will generate appropriate recommendations.

References

  1. Shunmei Meng, Wanchun Dou, Xuyun Zhang, Jinjun Chen," KASR: A Keyword-Aware Service Recommendation Method based on Map Reduce for Big Data Applications" IEEE Transactions On Parallel And Distributed Systems, TPDS-2013-12-1141.
  2. X. Yang, Y. Guo, Y. Liu, "Bayesian-inference based recommendation in social networks," IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 4, pp. 642-651, 2013.
  3. G. Kang, J. Liu, M. Tang, X. Liu and B. cao, "AWSR: Active Web Service Recommendation Based on the Usage History," 2012 IEEE 19th International Conference on Web Services (ICWS), pp. 186-193, 2012.
  4. Yan-Ying Chen, An-Jung Cheng, "Travel Recommendation by Mining People Attributes and Travel Group Types from Community- Contributed Photos" IEEE Transactions on Multimedia, Vol. 15, No. 6, October 2013.
  5. M. Alduan, F. Alvarez, J. Menendez, and O. Baez, "Recommender System for Sport Videos Based on the User Audiovisual Consumption," IEEE Transactions on Multimedia, Vol. 14, No.6, pp. 1546-1557, 2013.
  6. Zibin Zheng, Xinmiao Wu, Yilei Zhang, Michael R. Lyu, Fellow ,and Jianmin Wang," QoS Ranking Prediction for Cloud Services" IEEE Transactions On Parallel And Distributed Systems, Vol. 24, No. 6, June 2013.
  7. G.Linden, B. Smith, and J. York, "Amazon.com Recommendations: Item to Item Collaborative Filtering," IEEE Internet Computing, Vol. 7, No.1, pp.76-80, 2003.
  8. Fuzhi Zhang, Huilin Liu, Jinbo Chao, "A Two-stage Recommendation Algorithm Based on K-means Clustering In Mobile E-commerce", Journal of Computational Information Systems, Vol. 6, Issue 10, pp. 3327-3334, 2010.
  9. Brian Mc Fee, Luke Barrington and Gert Lanckrieo, "Learning Content Similarity for Music Recommendation" IEEE Transactions on Audio, Speech, and Language Processing, Vol. 20, No. 8, 2012.
  10. Z. D. Zhao, and M. S. Shang, "User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop," In the third International Workshop on Knowledge Discovery and Data Mining, pp. 478-481, 2010.
  11. D. Agrawal, S. Das, and A. El Abbadi, "Big Data and Cloud Computing: New Wine or Just New Bottles?" Proc. VLDB Endowment, vol. 3, no. 1, pp. 1647-1648, 2010
  12. J. Dean and S. Ghemawat, "Map Reduce: Simplified Data Processing on Large Clusters," Comm. ACM vol. 51, no. 1, pp. 107-113, 2005.
  13. S. Ghemawat, H. Gobioff, and S. T. Leung, "The Google File System," Proc. 19th ACM Symp. Operating Systems Principles , pp. 29- 43, 2003
  14. Z. Luo, Y. Li, and J. Yin, "Location: A Feature for Service Selection in the Era of Big Data," Proc. IEEE 20th Int’l Conf. Web Service, pp515.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-04-30

Issue

Volume 3, Issue 2, March-April-2017

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
A. Owaise Ahmed, K. Abirami, S. Chandrika, M. Janani, " A Trust Aware Product Recommending Scheme for Multiple Cloud using HADOOP Services , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 2, pp.254-260, March-April-2017.