Automated tagging for the retrieval of software resources in grid and cloud infrastructures

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
Pages628-635
Number of pages8
DOIs
Publication statusPublished - 16 Jul 2012
Event12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 - Ottawa, ON, Canada
Duration: 13 May 201216 May 2012

Conference

Conference12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
CountryCanada
CityOttawa, ON
Period13/05/1216/05/12

Keywords

  • classification
  • cloud
  • grid
  • information retrieval
  • machine learning
  • mining
  • software
  • tagging

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  • Cite this

    Katakis, I., Pallis, G., Dikaiakos, M. D., & Onoufriou, O. (2012). Automated tagging for the retrieval of software resources in grid and cloud infrastructures. In Proceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 (pp. 628-635). [6217475] https://doi.org/10.1109/CCGrid.2012.66