Efficient storage and querying of sequential patterns in database systems? ?
The number of patterns discovered by data mining can become tremendous, in some cases exceeding the size of the original database. Therefore, there is a requirement for querying previously generated mining results or for querying the database against discovered patters. In this paper, we focus on developing methods for the storage and querying of large collections of sequential patterns. We describe a family of algorithms, which address the problem of considering the ordering among elements, that is crucial when dealing with sequential patterns. Moreover, we take into account the fact that the distribution of elements within sequential patterns is highly skewed, to propose a novel approach for the effective encoding of patterns. Experimental results, which examine a variety of factors, illustrate the efficiency of the proposed method.
sequential patterns pattern post-processing persistency signatures