Abstract: Communication dispatch system is the guarantee for the normal operation of the smart grid. In order to en- sure the correct operation of the system, man on duty need to record the operational status, emergencies, the accident fault as well as the corresponding treatment program of the communication dispatch system of smart grid To help rr}}nr gers to keep up with the working status of system, for finding the potential security risks, the logs need to be labeled for certain types,to facilitate managers to query and retricve,so the communication dispatch system needs to be able to au- tomatically classify recorded logs according to various demands of management. However, the automatic classification for logs recorded by attendants in terms of their own understanding and habits, needs to learn from a large number of la- bcled logs data provided by information scheduling experts. Since manually reading to label is a timcconsuming and la- bor-intensive process,only a small amount of labels are often provided in practical applications, thus affecting the per- formance of the automatic classification. In terms of this limitation, this paper proposed an automated classification method based on active semi-supervised learning. hhis method, on one hand, acquires the labels of logs that can improve the classifier most through active learning,on the other hand,further enhance learning performance by the use of larges number of unlabeled logs. The results of application on logs of communication dispatch system of national smart grid show that the method based on active semi-supervised learning can achieve better performance than existing methods.

Key words: Data mining, Machine learning, Active semi supervised learning, Log classification, Smart grid