Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …

Most clustering strategies have not changed considerably since their initial definition. The
common improvements are either related to the distance measure used to assess …

This paper presents a comprehensive survey of the meta-heuristic optimization algorithms
on the text clustering applications and highlights its main procedures. These Artificial …

Time series clustering has been shown effective in providing useful information in various
domains. There seems to be an increased interest in time series clustering as part of the …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

Clustering is a powerful vehicle to reveal and visualize structure of data. When dealing with
time series, selecting a suitable measure to evaluate the similarities/dissimilarities within the …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

While fuzzy c-means is a popular soft-clustering method, its effectiveness is largely limited to
spherical clusters. By applying kernel tricks, the kernel fuzzy c-means algorithm attempts to …

Web personalization is the process of customizing a Web site to the needs of specific users,
taking advantage of the knowledge acquired from the analysis of the user's navigational …