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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.