TDML: A Data Mining Language for Transaction Databases

A desired feature of data mining systems is the ability to support ad hoc and interactive data mining in order to facilitate flexible and effective knowledge discovery. Data mining query languages can be designed to support such a feature. There are data mining query languages like DMQLfor mining relational databases. In this paper, we have proposed a new data mining language for mining transaction databases called TDML. This proposed language mines association rule mining and sequential pattern mining. It uses a new bit map processing approach with buffered storage of results. Various types of data mining approaches that are supported like generalized mining, multilevel mining, multidimensional mining, distributed mining, partition mining, incremental mining, online mining, merge mining, transaction reduction, stream mining and targeted itemset mining.