Abstract
Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous research is mainly focused on investigating scalable algorithms for mining sequential patterns while less on its theoretical foundations. However, the latter is also important because it can help to use existing theories and methods to support more effective mining tasks. In this chapter, we onduct a systematic study on models and algorithms in sequential pattern analysis, especially discuss the existing algorithms' advantages and limitations. Then, we build the relation between the closed sequential patterns and fixed point, which can serve as a theoretical foundation of sequential patterns. Finally, we discuss
its applications and outline the future research work.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Data Mining - Techniques and Applications |
| Place of Publication | Heidelberg |
| Publisher | Springer |
| Pages | 103-122 |
| Volume | 1 |
| Edition | 1 |
| ISBN (Print) | 978-3-540-26256-5 |
| State | Published - Aug 2005 |