Fast Discovery of Sequential Patterns Using Materialized Data Mining Views

Most data mining techniques consist in discovery of frequently occurring patterns in large data sets. From a user’s point of view, data mining can be seen as advanced querying, where each data mining query specifies the source data set and the requested class of patterns. Unfortunately, current data mining systems consume minutes or hours to answer simple queries, which makes them unsuitable for interactive use. In this paper we present the concept of materialized data mining views and their application to fast discovery of sequential patterns. We show how materialized data mining views can be used to optimize processing of sequential pattern queries.

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