Sentence examples for mining of association from inspiring English sources

Recently, several important database applications have called for the design of efficient techniques for incremental mining of association rules.

In response to this need, we explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules.

The proposed method uses efficient mining of association rules.

A serious problem encountered during the mining of association rules is the exponential growth of their cardinality.

The present paper focuses on the mining of association rules based on maximum single constraints on both rule sides, which is stated as follows.

Two serious problems encountered during the mining of association rules with maximum single constraints are that (1) their cardinality grows exponentially, and the known algorithms for mining them typically generate numerous redundancies and duplicates and (2) their constraints are frequently modified.

In this analysis, we extended the established data mining technique of association rules borrowed from market basket analysis to transcriptome analysis.

A method is designed to transform mining of fuzzy association rules to the binary counterpart.

Additionally, mining of cyclic association rules is not able to discover two or more periodic patterns whose cycles overlap on the same period of time due to the same application processed with different frequencies by two or more users.

Data mining is mainly composed of association rules mining, sequent pattern mining, classification and clustering.

Our knowledge discovery tool applies emerging pattern (EP) mining [2]: a form of association rule mining [3] that is well known to computer science, but is relatively new to chemistry [4].