Sentence examples for transaction database from inspiring English sources

Congress has long resisted the idea of a central transaction database.

The first issue is the discovery of generalized fuzzy association rules in the transaction database.

More importantly, algorithm SWF is particularly powerful for efficient incremental mining for an ongoing time-variant transaction database.

This study integrates customer behavioral variables, demographic variables, and transaction database to establish a method of mining changes in customer behavior.

In essence, by partitioning a transaction database into several partitions, algorithm SWF employs a filtering threshold in each partition to deal with the candidate itemset generation.

The second issue is to discover association rules from the web usage data and the large itemsets identified in the transaction database.

Then, we give an application of our declarative framework in data mining, namely, the problem of mining Top-k motifs in the transaction databases and in the sequences.

High-utility itemset mining (HUIM) is a useful set of techniques for discovering patterns in transaction databases, which considers both quantity and profit of items.

This study therefore proposes a new method which incorporates mining algorithms with enterprise transaction databases directly to perform real-time mining.

It includes a novel pre-processing method to construct multiple types of transaction databases from a same original event log using transformations.

High-Utility Itemset Mining (HUIM) is an extension of frequent itemset mining, which discovers itemsets yielding a high profit in transaction databases (HUIs).