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Online service systems have been increasingly popular and important nowadays. Reducing the MTTR (Mean Time to Restore) of a service remains one of the most important steps to assure the user-perceived availability of the service. To reduce the MTTR, a common practice is to restore the service by identifying and applying an appropriate healing action. In this paper, we present an automated mining-based approach for suggesting an appropriate healing action for a given new issue. Our approachdoi:10.1109/dsn.2014.39 dblp:conf/dsn/DingFLLZX14 fatcat:mwoqzei27rff3o7u5eacnrkv2q