Data mining is an analytical approach that contributes to achieving a solution to many
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …

Clustering refers to the task of identifying groups or clusters in a data set. In density‐based
clustering, a cluster is a set of data objects spread in the data space over a contiguous …

Travelers can enjoy a wide range of choices with the assistance of online review websites
such as TripAdvisor. Online reviews provided by customers are an important portion of …

One of the most challenging aspects of clustering is validation, which is the objective and
quantitative assessment of clustering results. A number of different relative validity criteria …

Gene expression data hide vital information required to understand the biological process
that takes place in a particular organism in relation to its environment. Deciphering the …

The use of artificial neural networks (ANNs) in problems related to water resources has
received steadily increasing interest over the last decade or so. The related method of the …

Groundwater contamination at the site has become a very serious problem. A clear
understanding of the hydrogeochemical characteristics of groundwater is indispensable for …

This paper presents a novel emotion recognition model using the system identification
approach. A comprehensive data driven model using an extended Kohonen self-organizing …

To make an overall assessment of the groundwater quality in Seoul city, we used the self-
organizing map (SOM) technique in combination with fuzzy c-means (FCM) clustering. SOM …

The clustering ensemble technique aims to combine multiple clusterings into a probably
better and more robust clustering and has been receiving an increasing attention in recent …