With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then autonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to incorporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process. With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then autonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to incorporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.