Text Mining and Its Applications

As nowadays data centers are processing more jobs and collecting more data, the system status monitoring and analyzing functionality ensuring the availability, scalability and efficiency becomes more and more important. In order to build an automated status monitoring and alerting system, we need to group jobs performed at a data center upon jobs' characteristics. Since the job names are generated by system users at will, it is very hard to group them in order to monitor the job status efficiently. Thus we need to find some methods to sort out the system log, and help to group jobs that are beneficial for improving the accuracy and efficiency of the system analysis. This paper proposes a text mining algorithm and its application in grouping jobs for log analysis.