This paper presents the top 10 data mining algorithms identified by the IEEE International
Conference on Data Mining (ICDM) in December 2006: C4. 5, k-Means, SVM, Apriori, EM …

Big data for health care is one of the potential solutions to deal with the numerous
challenges of health care, such as rising cost, aging population, precision medicine …

Advancement in the fields of electronic communication, data processing, and internet
technologies enable easy access to and interaction with a variety of physical devices …

A motion object extraction algorithm based on the active contour model is proposed. Firstly,
moving areas involving shadows are segmented with the classical background difference …

Clustering, the unsupervised classification of patterns into groups, is one of the most
important tasks in exploratory data analysis. Primary goals of clustering include gaining …

The study of collective behavior is to understand how individuals behave in a social network
environment. Oceans of data generated by social media like Facebook, Twitter, Flickr and …

The k-means algorithm is known to have a time complexity of O (n 2), where n is the input
data size. This quadratic complexity debars the algorithm from being effectively used in large …

While periodic checkpointing has been an important mechanism for tolerating faults in high-
performance computing (HPC) systems, it is cost-prohibitive as the HPC system approaches …

With increased reliance on solar-based energy generation in modern power systems, the
problem of managing uncertainty in power system operation becomes crucial. However, in …

In recent years, k-means has been fitted into the MapReduce framework and hence it has
become a very effective solution for clustering very large datasets. However, k-means is not …