Add to ORKGAbstract: Distributed clustering is an effect method for solving the problem of clustering data located at different sites. Considering the circumstance that data is horizontally distributed, algorithm LDBDC (local density based distributed clustering) is presented based on the existeding algorithm DBDC (density based distributed clustering), which can easily fit datasets of high dimension and abnormal distribution by adopting ideas such as local density-based clustering and density attractor. Theoretical analysis and experimental results show that algorithm LDBDC outperforms DBDC and SDBDC (scalable density-based distributed clustering) in both clustering quality and efficiency. Key words: distributed clustering; local density based clus...
In recent years, clustering methods have attracted more attention in analysing and monitoring data s...
In this paper, we propose a clustering algorithm to find clusters of different sizes, shapes and den...
The various-density problem has become one of the focuses in density based clustering research. A no...
Abstract. Clustering has become an increasingly important task in modern application domains such as...
1 Introduction Clustering is the process of allocating points in a given dataset into disjoint and m...
bzhana~hpl.hp.com Data clustering is one of the fundamental techniques in scientific data analysis a...
One of the main categories in Data Clustering is density based clustering. Density based clustering ...
The analysis of big data requires powerful, scalable, and accurate data analytics techniques that th...
Finding clusters in data is a challenging problem especially when the clusters are being of widely v...
The paper proposes a new density-based distributed clustering algorithm - the PPDBDC (Privacy Preser...
Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in appl...
Abstract- Clustering high dimensional data is an emerging research field. Most clustering technique ...
The clustering by fast search and find of density peaks (DPC) has the advantages of no iteration and...
Clustering methods in data mining are widely used to detect hotspots in many domains. They play an i...
Aiming at the problems of unreasonable division of data gridding, low accuracy of clustering results...
In recent years, clustering methods have attracted more attention in analysing and monitoring data s...
In this paper, we propose a clustering algorithm to find clusters of different sizes, shapes and den...
The various-density problem has become one of the focuses in density based clustering research. A no...
Abstract. Clustering has become an increasingly important task in modern application domains such as...
1 Introduction Clustering is the process of allocating points in a given dataset into disjoint and m...
bzhana~hpl.hp.com Data clustering is one of the fundamental techniques in scientific data analysis a...
One of the main categories in Data Clustering is density based clustering. Density based clustering ...
The analysis of big data requires powerful, scalable, and accurate data analytics techniques that th...
Finding clusters in data is a challenging problem especially when the clusters are being of widely v...
The paper proposes a new density-based distributed clustering algorithm - the PPDBDC (Privacy Preser...
Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in appl...
Abstract- Clustering high dimensional data is an emerging research field. Most clustering technique ...
The clustering by fast search and find of density peaks (DPC) has the advantages of no iteration and...
Clustering methods in data mining are widely used to detect hotspots in many domains. They play an i...
Aiming at the problems of unreasonable division of data gridding, low accuracy of clustering results...
In recent years, clustering methods have attracted more attention in analysing and monitoring data s...
In this paper, we propose a clustering algorithm to find clusters of different sizes, shapes and den...
The various-density problem has become one of the focuses in density based clustering research. A no...