The knowledge gained from data mining is highly dependent on the experience of an expert
for further analysis to increase effectiveness and wise decision-making. This mined …

Semantic similarity is the process of identifying relevant data semantically. The traditional
way of identifying document similarity is by using synonymous keywords and syntactician. In …

Due to the significant increase of the number of wind-based electricity generation systems, it
is important to have accurate information on their operational characteristics, which are …

Clustering has been intensively studied in machine learning and data mining communities.
Although demonstrating promising performance in various applications, most of the existing …

Density peaks clustering (DPC) is a density-based clustering algorithm with excellent
clustering performance including accuracy, automatically detecting the number of clusters …

Clustering network vertices is an enabler of various applications such as social computing
and Internet of Things. However, challenges arise for clustering when networks increase in …

Spectral clustering is a well-known graph-theoretic clustering algorithm. Although spectral
clustering has several desirable advantages (such as the capability of discovering non …

Different types of outliers have existed in the monitoring data of wind turbines, which are not
conducive to the follow-up data mining. However, the complex inner characteristics of the …

It is crucial to evaluate the quality of clustering results in cluster analysis. Although many
cluster validity indices (CVIs) have been proposed in the literature, they have some …

The purpose of this paper is to explore a method for detecting abnormal comments. With the
growth of e-commerce sites and reviews sites, user reviews of messages begin to affect …