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                                       Details for article 11 of 12 found articles
 
 
  Mining of closed frequent subtrees from frequently updated databases
 
 
Title: Mining of closed frequent subtrees from frequently updated databases
Author: Anh Nguyen, Viet
Yamamoto, Akihiro
Appeared in: Intelligent data analysis
Paging: Volume 16 (2012) nr. 6 pages 953-967
Year: 2012-11-19
Contents: We study the problem of mining closed frequent subtrees from tree databases that are updated regularly over time. Closed frequent subtrees provide condensed and complete information for all frequent subtrees in the database. Although mining closed frequent subtrees is in general faster than mining all frequent subtrees, this is still a very time consuming process, and thus it is undesirable to mine from scratch when the change to the database is small. The set of previous mined closed subtrees should be reused as much as possible to compute new emerging subtrees. We propose, in this paper, a novel and efficient incremental mining algorithm for closed frequent labeled ordered trees. We adopt a divide-and-conquer strategy and apply different mining techniques in different parts of the mining process. The proposed algorithm requires no additional scan of the whole database while its memory usage is reasonable. Our experimental study on both synthetic and real-life datasets demonstrates the efficiency and scalability of our algorithm.
Publisher: IOS Press
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 11 of 12 found articles
 
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