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 language | English |
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Title of host publication | Proceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 |
Pages | 628-635 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 16 Jul 2012 |
Event | 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 - Ottawa, ON, Canada Duration: 13 May 2012 → 16 May 2012 |
Conference
Conference | 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 |
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Country/Territory | Canada |
City | Ottawa, ON |
Period | 13/05/12 → 16/05/12 |
Keywords
- classification
- cloud
- grid
- information retrieval
- machine learning
- mining
- software
- tagging