Data mining for association rules and sequential patterns: sequential and parallel algorithms
Data mining for association rules and sequential patterns: sequential and parallel algorithms
A tree projection algorithm for generation of frequent item sets
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
An iterative strategy for pattern discovery in high-dimensional data sets
Proceedings of the eleventh international conference on Information and knowledge management
Mining Sequential Patterns Using Graph Search Techniques
COMPSAC '03 Proceedings of the 27th Annual International Conference on Computer Software and Applications
Efficient dynamic mining of constrained frequent sets
ACM Transactions on Database Systems (TODS)
FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs
Proceedings of the 6th annual ACM international workshop on Web information and data management
Finding frequent itemsets by transaction mapping
Proceedings of the 2005 ACM symposium on Applied computing
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In this article we present the online pattern discovery algorithm. The algorithm is capable to discover frequent patterns in the records of online sensors and similar devices. Each record is processed only once and only the processed record is available at the time. The algorithm operates on the records of discrete valued attributes and is capable to operate on the infinite sets of records as well as the infinite sets of their attributes values. Neither the number of records nor the number of attributes and their values needs to be known in advance.