Clustering is the unsupervised classification of patterns (observations, data items, or feature
vectors) into groups (clusters). The clustering problem has been addressed in many contexts …

A successful International Conference and Workshop on recent advances in medical
toxicology & legal medicine was organised from 2-7th Nov. 1998 at AIIMS, New Delhi. The …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal
partition of a given data into a specified number of clusters. GA's used earlier in clustering …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

The grou** genetic algorithm (GGA) is a genetic algorithm heavily modified to suit the
structure of grou** problems. Those are the problems where the aim is to find a good …

Most textbooks on modern heuristics provide the reader with detailed descriptions of the
functionality of single examples like genetic algorithms, genetic programming, tabu search …

Most optimization problems have constraints. The solution or set of solutions which are
obtained as the final result of an evolutionary search must necessarily be feasible, that is …

Database outsourcing is an emerging data management paradigm which has the potential
to transform the IT operations of corporations. In this paper we address privacy threats in …

From basic data mining concepts to state-of-the-art advances, this book covers the theory of
the subject as well as its application in a variety of fields. It discusses the incorporation of …