The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

As the information from diverse disciplines continues to integrate during the whole life cycle
of an Architecture, Engineering, and Construction (AEC) project, the BIM (Building …

The purpose of this study was to gain insights into the variations in antioxidant profiles
between fruits and vegetables using pattern recognition tools; classification was achieved …

This study investigated the variations in antioxidant profiles between spices using pattern
recognition tools; classification was achieved based on the results of global antioxidant …

Categorical data clustering algorithms, in contrast to numerical ones, are still in their infancy
despite some algorithms have been proposed in the literature. It is known that many …

Clustering ensemble selection is an effective technique for improving the quality of
clustering results. However, traditional methods usually measure the quality and diversity …

Clustering categorical data is an integral part of data mining and has attracted much
attention recently. In this paper, we present k-ANMI, a new efficient algorithm for clustering …

Abstract Domain experts are driven by business needs, while data analysts develop and use
various algorithms, methods, and tools, but often without domain knowledge. A major …

Water management is a crucial issue in East Asia and is significantly influenced by climate
change. Because East Asia's precipitation characteristics are varied and complex, it is …

Introduction We aimed to identify clusters of people with type 2 diabetes mellitus (T2DM) and
to assess whether the frequency of these clusters was consistent across selected countries …