Methods for Batch Processing of Data Mining Queries

Data mining is a useful decision support technique, which can be used to find trends and regularities in warehouses of corporate data. A serious problem of its practical applications is long processing time required by data mining algorithms. Current systems consume minutes or hours to answer single requests, while typically batches of the requests are delivered the systems. In this paper we present the problem of batch processing of data mining requests. We introduce methods that analyze similarities between separate requests to reduce the processing cost. We also perform a comparative performance analysis of the proposed methods.