M. Y. Lin and S. Y. Lee, "Incremental Update on Sequential Patterns in Large Databases," Proceedings of 10th IEEE International Conference on Tools with Artificial Intelligence, Taipei, Taiwan, pp. 24-31, 1998. Home/Search Document Details and Download
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Incremental Mining of Sequential Patterns in Large.. - Masseglia, Poncelet.. (2000) (2 citations) (Correct)
.... there is a need for e cient algorithms to update, maintain and manage the information discovered [5] Several e cient algorithms for maintaining association rules 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 taken into account. In order to illustrate the problem, let us consider an original and an incremental database. Then, to compute the set of sequential patterns ....
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.
Web Usage Mining: How to Effciently Manage New.. - Masseglia, Poncelet, .. (Correct)
....techniques such as data characterization, class comparison, association, prediction, classi cation or time series analysis can be used on the Web log data cube 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 patterns in a database when new transactions and new customers are added to the database. It is based on an increment sequence Lattice consisting of all the frequent ....
....data is combined with the frequent sequences and negative border in order to determine the portions of the original database that need to be re scanned. Even this approach is very e cient, maintaining negative border is very memory consuming and not well adapted for very large databases [13] In [7], the author proposes the FASTUP algorithm, which can update the sequential patterns in a database when new transactions are added to the database. The FASTUP approach fully resumes the FUP algorithm [3] de ned for incremental mining of association rules. The main idea is to store the counts of ....
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.
Interactive Sequence Discovery by Incremental Mining - Ming-Yen Lin And Self-citation (Lin) (Correct)
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M. Y. Lin and S. Y. Lee, "Incremental Update on Sequential Patterns in Large Databases," Proceedings of 10th IEEE International Conference on Tools with Artificial Intelligence, Taipei, Taiwan, pp. 24-31, 1998.
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