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This book is an outcome of our research in the field of clustering techniques used in spatial data analysis. Finding meaningful patterns and useful trends in large datasets has attracted considerable interest recently, and one of the most widely studied problems in this area is the identification and formation of clusters, or densely populated regions in a dataset. Prior work does not adequately address the problem of large datasets and minimization of Input/output costs. The objective of this book is to present a survey on Data Mining Clustering techniques, especially Density Based Clustering…mehr

Produktbeschreibung
This book is an outcome of our research in the field of clustering techniques used in spatial data analysis. Finding meaningful patterns and useful trends in large datasets has attracted considerable interest recently, and one of the most widely studied problems in this area is the identification and formation of clusters, or densely populated regions in a dataset. Prior work does not adequately address the problem of large datasets and minimization of Input/output costs. The objective of this book is to present a survey on Data Mining Clustering techniques, especially Density Based Clustering and finally to show case a new Triangle-density based clustering technique, which we have named as TDCT, for efficient clustering of spatial data. Much emphasis has been given to make the book clearly understandable to the readers and provide the readers with general clustering concepts.
Autorenporträt
Hrishav Bakul Barua is currently working with Tata Consultancy Services (TCS) as an Assistant System Engineer tagged with a role of developer and DBA. He has published 3 research papers in reputed International Journals. He is a professional member of Association for Computing Machinary (ACM). His research interests include Data mining and AI.