The present manuscript is intended to be a textbook that could serve both undergraduate
and graduate students when studying Fuzzy Set Theory and Applications. It is also intended …

Determining the quality of the results obtained by clustering techniques is a key issue in
unsupervised machine learning. Many authors have discussed the desirable features of …

Clustering is a widely studied data mining problem in the text domains. The problem finds
numerous applications in customer segmentation, classification, collaborative filtering …

Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

This paper presents algorithms for hierarchical, agglomerative clustering which perform
most efficiently in the general-purpose setup that is given in modern standard software …

Clustering validation has long been recognized as one of the vital issues essential to the
success of clustering applications. In general, clustering validation can be categorized into …

Clustering is a powerful technique in data-mining, which involves identifing homogeneous
groups of objects based on the values of attributes. Meta-heuristic algorithms such as …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

This study aims to investigate the travellers' choice behaviour towards green hotels through
existing online travel reviews on TripAdvisor. Accordingly, a method combining …

Organizing data into sensible groupings is one of the most fundamental modes of
understanding and learning. As an example, a common scheme of scientific classification …