SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Activity monitoring: noticing interesting changes in behavior
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A fast string searching algorithm
Communications of the ACM
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Unified View to String Matching Algorithms
SOFSEM '96 Proceedings of the 23rd Seminar on Current Trends in Theory and Practice of Informatics: Theory and Practice of Informatics
DEMON: Mining and Monitoring Evolving Data
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Online Data Mining for Co-Evolving Time Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
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Mining data streams is an emerging area of research given the potentially large number of business applications. A significant challenge in analyzing/mining data streams is the high data rate of the stream. In this paper, we explain a Programmable Pipelined Queue to cope with the high data rate of incoming data streams. It can be added easily to general computer system. And we apply the Programmable Pipelined Queue to online string matching.