• DocumentCode
    2321588
  • Title

    Automated Tagging for the Retrieval of Software Resources in Grid and Cloud Infrastructures

  • Author

    Katakis, Ioannis ; Pallis, George ; Dikaiakos, Marios D. ; Onoufriou, Onisiforos

  • fYear
    2012
  • fDate
    13-16 May 2012
  • Firstpage
    628
  • Lastpage
    635
  • Abstract
    A key challenge for Grid and Cloud infrastructures is to make their services easily accessible and attractive to end-users. In this paper we introduce tagging capabilities to the Miner soft system, a powerful tool for software search and discovery in order to help end-users locate application software suitable to their needs. Miner soft is now able to predict and automatically assign tags to software resources it indexes. In order to achieve this, we model the problem of tag prediction as a multi-label classification problem. Using data extracted from production-quality Grid and Cloud computing infrastructures, we evaluate an important number of multi-label classifiers and discuss which one and with what settings is the most appropriate for use in the particular problem.
  • Keywords
    cloud computing; grid computing; identification technology; Miner soft system; application software; automated tagging; cloud computing infrastructures; multilabel classification problem; multilabel classifiers; production quality grid computing infrastructures; software resource retrieval; software resources; software search; tag prediction; tagging capability; Cloud computing; Indexes; Libraries; Machine learning; Tagging; Training; classification; cloud; grid; information retrieval; machine learning; mining; software; tagging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4673-1395-7
  • Type

    conf

  • DOI
    10.1109/CCGrid.2012.66
  • Filename
    6217475