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Abstract: Mining of sequential patterns in a transactional database is time-consuming due to its complexity. While maintaining present patterns is a non-trivial task after database update, since appended data sequences may invalidate old patterns and create new ones. In contrast to re-mining, the incremental update algorithm proposed which effectively utilizes discovered knowledge is the key to improve mining performance. By counting over appended data sequences instead of entire updated database in... (Update)
Context of citations to this paper: More
...and Web log database. To the best of our knowledge, not much e ort has been spent on maintaining sequential patterns in the general way [13, 7]. The rst approach proposes an incremental mining algorithm, based on the SPADE approach [17] which can update the sequential...
.... have been developed [5, 6, 14] However to the best of our knowledge, not much e ort has been spent on maintaining sequential patterns [9]. This problem is much more complicated than maintaining association rules, since transaction cutting and sequence permutation has to be...
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BibTeX entry: (Update)
M.Y Lin and S.Y. Lee. Incremental Update on Sequential Patterns in Large Databases. In Proceedings of the Tools for Arti cial Intelligence Conference (TAI'98), pages 2431, May 1998. http://citeseer.ist.psu.edu/lin98incremental.html More
@misc{ lin98incremental,
author = "M. Lin and S. Lee",
title = "Incremental Update on Sequential Patterns in Large Databases",
text = "M.Y Lin and S.Y. Lee. Incremental Update on Sequential Patterns in Large
Databases. In Proceedings of the Tools for Arti cial Intelligence Conference
(TAI'98), pages 2431, May 1998.",
year = "1998",
url = "citeseer.ist.psu.edu/lin98incremental.html" }
Citations (may not include all citations):340 Mining Sequential Patterns - Agrawal, Srikant - 1995
242 Dynamic Itemset Counting and Implication Rule for Market Bas.. - Brin, Motwani et al. - 1997
189 Discovering Frequent Episodes in Sequences (context) - Mannila, Toivonen et al. - 1995
157 Mining Sequential Patterns: Generalizations and Performance .. - Srikant, Agrawal - 1995
117 IEEE Transactions on Knowledge and Data Engineering (context) - Agrawal, afer et al. - 1996
106 Maintenance of Discovered Association Rules in Large Databas.. - Cheung, Han et al. - 1996
85 Discovering Generalized Episodes using Minimal Occurrences - Mannila, Toivonen - 1996
36 Advances in Knowledge Discovery and Data Mining (context) - Agrawal, Mannila et al. - 1996
33 A General Incremental Technique For Maintaining Discovered A.. - Lee, Cheung et al. - 1997
22 Using a Hash-Based Method with Transaction Trimming for Mini.. - Park, Chen et al. - 1997
21 Fast Mining of Sequential Patterns in Very Large Databases - Zaki - 1997
20 Discovery of Frequent Patterns in Large Data Collections - Toivonen - 1996
6 Discovery of Multi-Level Association Rules from Large Databa.. (context) - Han, Fu - 1995
Documents on the same site (http://www.csie.nctu.edu.tw/~mylin/./index.htm):
Interactive Sequence Discovery by Incremental Mining - Ming-Yen Lin And (Correct)
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