Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
نویسندگان
چکیده
منابع مشابه
Maintenance of Discovered Knowledge: A Case in Multi-Level Association Rules
Many knowledge discovery (kdd) systems need to spend substantial amount of eeort to search for rules and patterns within large amount of data. After some natural evolutions, as a consequence of updates applied to their databases, these systems must update their previously discovered knowledge to reeect the current state of their databases. The straight forward approach of re-running the discove...
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E cient discovery of association rules in large databases is a well studied problem and several approaches have been proposed. However, it is non trivial to maintain the association rules current when the database is updated since, such updates could invalidate existing rules or introduce new rules. In this paper, we propose an incremental updating technique based on negative borders, for the m...
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EEcient discovery of association rules in large databases is a well studied problem and several approaches have been proposed. However, it is non trivial to maintain the association rules current when the database is updated since, such updates could invalidate existing rules or introduce new rules. In this paper, we propose an incremental updating technique based on negative borders, for the m...
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Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these databases has to be maintained, and an incremental updating technique needs to be developed for maintaining the discovered association rules from these databases. The concept of Temporal Association Rules has been in...
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