KAGO: an approximate adaptive grid-based outlier detection approach using kernel density estimate

Pattern Analysis and Applications - Outlier detection approaches show their efficacy while extracting unforeseen knowledge in domains such as intrusion detection, e-commerce, and fraudulent...     

A survey of density based clustering algorithms

Density based clustering algorithms(DBCLAs)rely on the notion of density to identify clusters of arbitrary shapes,sizes with varying densities.Existing surveys on DB-CLAs cover only a selected set of algorithms.These surveys fail to provide an extensive information about a variety of DBCLAs proposed till date including a taxonomy of the algorithms.In this paper we present a comprehensive survey of various DB-CLAS over last two decades along with their classification.We group the DBCLAs in each of the four categories:density definition,parameter sensitivity,execution mode and nature of*data and further divide them into various classes under each of these categories.In addition,we compare the DBCLAs through their common features and variations in citation and conceptual dependencies.We identify various application areas of DBCLAS in domains such as astronomy,earth sciences,molecular biology,geography,multimedia.Our survey also identifies probable future directions of DBCLAs where involvement of density based methods may lead to favorable results.     

BISDBx: towards batch-incremental clustering for dynamic datasets using SNN-DBSCAN

Pattern Analysis and Applications - Many important applications such as recommender systems, e-commerce sites, web crawlers involve dynamic datasets. Dynamic datasets undergo frequent changes in...