• DocumentCode
    2182270
  • Title

    Research on a Kind of High Efficiency Cloud Service Recommendation Algorithm

  • Author

    Ran Jin ; Chunhai Kou ; Ruijuan Liu ; Yefeng Li

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
  • fYear
    2013
  • fDate
    16-19 Dec. 2013
  • Firstpage
    291
  • Lastpage
    296
  • Abstract
    As the third wave of the IT following personal computers, the Internet, cloud computing is not only the revolution of modern information technology, but also more of the innovation of modern business model. From cloud computing to cloud services, "cloud" has led an industrial revolution, and various cloud services emerge endlessly. The cloud computing technology and service innovation in China is in rapid development and areas across the country are advancing corresponding cloud computing and cloud service plans. But with the continued growth of cloud service type and quantity, users are faced with the challenge of how to choose the best cloud services. Based on the analysis of the cloud service, this paper introduces the concept of user community, and combining the collaborative filtering of classical recommendation algorithm and improved K-Means clustering algorithm, it puts forward a new cloud service recommendation algorithm CSRA. A lot of experiments show that under different matrix density and scale of data sets, the mean absolute error of CSRA is smaller than that of UPCC and IPCC, and it has more efficient service to recommend.
  • Keywords
    business data processing; cloud computing; collaborative filtering; recommender systems; China; Internet; business model; cloud computing technology; cloud service type; collaborative filtering; high efficiency cloud service recommendation algorithm; industrial revolution; information technology; k-means clustering algorithm; personal computers; Algorithm design and analysis; Availability; Cloud computing; Clustering algorithms; Collaboration; Communities; Prediction algorithms; Cloud Computing; Cloud Service Recommendation; Clustering Technology; User Community; collaborative filtering recommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
  • Conference_Location
    Fuzhou
  • Print_ISBN
    978-1-4799-2829-3
  • Type

    conf

  • DOI
    10.1109/CLOUDCOM-ASIA.2013.90
  • Filename
    6821006