Predicting the next location of human mobility and its semantic information can support
recommendations for location-based services and trajectory mining, such as human mobility …

Both the current trends in technology such as smart phones, general mobile devices,
stationary sensors, and satellites as we as a new user mentality of using this technology to …

Finding frequent itemsets is computationally the most expensive step in association rules
mining, and most of the research attention has been focused on it. With the observation that …

In the heterogeneous information network (HIN), a motif-clique is a" complete graph" for a
given motif (or a small connected graph) that could capture the desired relationship in the …

Dengan bertumbuhnya e-commerce di Indonesia yang terus meningkat setiap tahunnya,
menjadikan peluang bisnis khususnya di pasar e-commerce. Sebagai platform dengan …

This study describes the formalization of the medical decision-making process under
uncertainty underpinned by conditional preferences, the theory of evidence and the …

To mine frequent itemsets from uncertain data, many existing algorithms rely on expected
support based mining. An alternative approach relies on probabilistic based mining, which …

We study the impact of preprocessing techniques on performance and effectiveness of the
similarity measures for uncertain time series. Some existing work on uncertain time series …

Abstract Frequent Itemset Mining (FIM) includes develo** data mining algorithms to
discover interesting and productive patterns from a variety of databases. There are several …

Abstract The mechanism of Frequent Itemset Mining can be performed by using sequential
algorithms like Apriori on a standalone system, or it can be applied using parallel algorithms …