HYPE: mining hierarchical sequential patterns

Mining data warehouses is still an open problem as few approaches really take the specificities of this framework into account (e.g. multidimensionality, hierarchies, historized data). Multidimensional sequential patterns have been studied but they do not provide any way to handle hierarchies. In this paper, we propose an original sequential pattern extraction method that takes the hierarchies into account. This method extracts more accurate knowledge and extends our preceding M2 SP approach. We define the concepts related to our problems as well as the associated algorithms. The results of our experiments confirm the relevance of our proposal. Categories and Subject Descriptors I.5 [Pattern Recognition]: Miscellaneous; H. [Information Systems]: General General Terms Algorithms, Design, Theory. Keywords Multidimensional Sequential Patterns, Hierarchies, OLAP.

• Type: Conference
• Year: 2006
• Where: DOLAP
• Authors: Marc Plantevit, Anne Laurent, Maguelonne Teisseire
• Keywords: DOLAP 2006, Information Management, Multidimensional Sequential Patterns, Sequential Pattern Extraction, Sequential Patterns