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Details for article 5 of 10 found articles
| Title: |
Incremental mining of sequential patterns: Progress and challenges |
| Author: |
Mallick, Bhawna Garg, Deepak Grover, P.S. |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 17 (2013) nr. 3 pages 507-530 |
| Year: |
2013-05-21 |
| Contents: |
Sequential pattern mining is a vital problem with broad applications. However, it is also challenging, as combinatorial high number of intermediate subsequences are generated that have to be critically examined. Most of the basic solutions are based on the assumption that the mining is performed on static database. But modern day databases are being continuously updated and are dynamic in nature. So, incremental mining of sequential patterns has become the norm. This article investigates the need for incremental mining of sequential patterns. An analytical study, focusing on the characteristics, has been made for more than twenty incremental mining algorithms. Further, we have discussed the issues associated with each of them. We infer that the better approach is incremental mining on the progressive database. The three more relevant algorithms, based on this approach, are also studied in depth along with the other work done in this area. This would give scope for future research direction. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 5 of 10 found articles
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