Due to the rapid growth of resource sharing, distributed systems are developed, which can
be used to utilize the computations. Data mining (DM) provides powerful techniques for …

This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

High utility itemset mining is a challenging task in frequent pattern mining, which has wide
applications. The state-of-the-art algorithm is HUI-Miner. It adopts a vertical representation …

We present SPMF, an open-source data mining library offering implementations of more
than 55 data mining algorithms. SPMF is a cross-platform library implemented in Java …

Sequential pattern mining algorithms using a vertical representation are the most efficient for
mining sequential patterns in dense or long sequences, and have excellent overall …

Academics and practitioners have a common interest in the continuing development of
methods and computer applications that support or perform knowledge-intensive …

Data Mining in general is the act of extracting interesting patterns and discovering non-trivial
knowledge from a large amount of data. Medical data mining can be used to understand the …

Sequential rule mining is an important data mining problem with multiple applications. An
important limitation of algorithms for mining sequential rules common to multiple sequences …

Sequential rule mining is an important data mining task with wide applications. The current
state-of-the-art algorithm (RuleGrowth) for this task relies on a pattern-growth approach to …

Recommender system suggests a personalized recommendation by filtering the information
based on users interest. Nowadays, users like to purchase the best possible items and …