Clustering Algorithms

Dear Colleagues,

The last decade has witnessed an upsurge of new clustering algorithms based on innovative technical approaches beyond those traditionally addressed in the data mining community. While the principles and fundamentals of distance and similarity prevail underneath these new schemes, their pattern search procedures are radically different from previous approaches: among them, evolutionary (and in general, bio-inspired) meta-heuristics have emerged as computationally efficient search engines that can be exploited, so as to find similarity patterns among massive datasets.

This Special Issue invites prospective researchers and practitioners in this field to submit their latest developments and/or surveys of the state of the art concerning the following topics:

- Evolutionary computing for clustering
- Meta-heuristically empowered pattern discovery
- Applications of clustering when hybridized with meta-heuristics
- Other combinations of meta-heuristics and machine learning (e.g., predictive analytics)

Proposals on other related topics will also be considered via a previous query.

Sincerely,

Javier (Javi) Del Ser Lorente
Guest Editor