Basket analysis is a prevailing technique to help retailers uncover patterns and associations
of sold products in customer shopping transactions. However, as the size of transaction …

MapReduce is a popular paradigm in distributed computing, but it is not efficient when
executing iterative algorithms over a distributed big dataset due to its heavy data …

Frequent itemset mining (FIM) is a major component in association rule mining, significantly
influencing its performance. FIM is a computationally intensive nondeterministic polynomial …

Frequent itemset mining (FIM) is a highly resource-demanding data-mining task
fundamental to numerous data-mining applications. Support calculation is a frequently …

Traditional approaches to data mining are generally designed for small, centralized, and
static datasets. However, when a dataset grows at an enormous rate, the algorithms become …

Mining high‐utility pattern (HUP) on transactional datasets has been widely discussed, and
various algorithms have been introduced to settle this problem. However, the time‐space …

Sažetak The fuel consumption rate of a diesel engine is closely related to its operating
speed. In order to minimize the fuel consumption rate of the diesel engine, this paper studies …

High-utility itemset mining is to mine high profit itemsets from transaction databases. But if
there are some itemsets with negative utility values in the transaction database, the high …

Spark reduces the I/O costs by introducing an in-memory data abstraction RDD.
Nevertheless, the performance of Spark is still limited by the memory size. Moreover, since …