Preface to Incremental Clustering, Concept Drift and Novelty Detection

Abstract

The development of dynamic information analysis methods, like incremental clustering, concept drift management and novelty detection techniques, is becoming a central concern in a bunch of applications whose main goal is to deal with information which is varying over time. These applications relate themselves to very various and highly strategic domains, including web mining, social network analysis, adaptive information retrieval, anomaly or intrusion detection, process control and management, recommender systems, technological and scientific survey, and even genomic information analysis, in bioinformatics. The term "incremental" is often associated to the terms dynamics, adaptive, interactive, on-line, or batch. The majority of the learning methods were initially defined in a non-incremental way.