检索结果-内蒙古大学图书馆

Multidimensional grid-based clustering with local differential privacy

INFORMATION SCIENCES 2023年第1期623卷 402-420页

作者： Fu, Nan Ni, Weiwei Hu, Haibo Zhang, Sen Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Peoples R China Hong Kong Polytech Univ Dept Elect & Informat Engn Hong Kong Peoples R China

Privacy-preserving clustering has received increasing research attention in recent years. Local differential privacy (LDP) is a privacy model without relying on trusted third parties. It plays a crucial role in distributed privacy-preserving clustering. Most previous methods focus on partition-based clustering (e.g., k-means), which necessitates many iterative interactions. Massive iterations cause a division of the privacy budget and increase the amount of individual noise, affecting the clustering utility. To address this issue, we turn to grid-based clustering and design the GC-LDP algorithm to balance the privacy and clus-tering utility with only three rounds of interactions. In GC-LDP, our core contribution is to develop a non-uniform grid division method via the coefficient of variation (CV), which can generate a grid structure approximating the global data distribution within two rounds of interactions. Besides, we designed a new perturbation mechanism to reduce the amount of individual noise injection. Further, a cell aggregation method is developed by exploring the relative density difference among grids to achieve multi-density clustering. Theoretical analysis and experiments on real-world datasets show that GC-LDP can obtain high-quality clustering results while satisfying local differential privacy. (c) 2022 Elsevier Inc. All rights reserved.

关键词： Local differential privacy grid-based clustering Iteration rounds

来源：评论

学校读者我要写书评

暂无评论

A Systematic Review of Density grid-based clustering for Data Streams

引用

IEEE ACCESS 2022年 10卷 579-596页

作者： Tareq, Mustafa Sundararajan, Elankovan A. Harwood, Aaron Abu Bakar, Azuraliza Al Hikma Univ Coll Dept Comp Technol Engn Baghdad 10015 Iraq Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ctr Software Technol & Management Bangi 43600 Selangor Malaysia Univ Melbourne Sch Comp & Informat Sci Melbourne Vic 3010 Australia Univ Kebangsaan Malaysia Ctr Articial Intelligence & Technol Fac Informat Sci & Technol Bangi 43600 Selangor Malaysia

Various applications, such as electronic business, satellite remote sensing, intrusion discovery, and network traffic monitoring, generate large unbounded data stream sequences at a rapid pace. The clustering of data streams has attracted considerable interest due to the increasing usage of evolving data streams. In particular, evolving data streams affect clustering because they introduce numerous challenges, such as time and memory limits and one-pass clustering. Furthermore, researchers need to be able to determine arbitrarily shaped clusters present in evolving data streams from applications. Due to these characteristics, conventional density grid-based clustering techniques cannot be used. Moreover, the existing density grid-based clustering algorithms have low cluster quality for clustering evolving data streams. This study conducted a systematic literature review (SLR) and noted numerous research-related issues encountered in solving the aforementioned problems. We summarized numerous grid-based clustering algorithms that have been used and determined their distinctive and limited features. We also observed how these algorithms address the challenges affecting the clustering of evolving data streams and studied their advantages and disadvantages. SLR was based on 104 articles published between 2010 and 2021. Numerous challenges remain for grid-based clustering algorithms, particularly in terms of time-limited and high-dimensional data handling. Last, our findings indicated a variety of active studies on density grid-based clustering.

关键词： clustering algorithms Data mining Systematics Protocols Databases Real-time systems Licenses clustering data stream grid-based clustering data stream clustering density-based clustering

来源：评论

学校读者我要写书评

暂无评论

A spatio-temporal binary grid-based clustering model for seismicity analysis

引用

PATTERN ANALYSIS AND APPLICATIONS 2024年第1期27卷 14-14页

作者： Vijay, Rahul Kumar Nanda, Satyasai Jagannath Sharma, Ashish Banasthali Vidyapith Dept Comp Sci Tonk 304022 Rajasthan India Malaviya Natl Inst Technol Dept Elect & Commun Engn Jaipur 302017 Rajasthan India Jaipur Engn Coll & Res Ctr Dept Elect & Commun Engn Jaipur 302022 Rajasthan India

This paper presents a spatio-temporal binary grid-based clustering model for determining complex earthquake clusters with different shapes and heterogeneous densities present in a catalog. The 3D occurrence of earthquakes is mapped into a 2D-low memory sparse matrix through a grid mechanism in the binary domain with consideration of spatio-temporal attributes. Then, image-transformation of a non-empty sets binary feature matrix, a clustering strategy is implemented with logical AND operator as similarity measure among the binary vectors. This approach is applied to solve the problem of seismicity declustering which separates the clustering and non-clustering patterns of seismicity for real-world earthquake catalogs of Japan (1972-2020) and Eastern Mediterranean (1966-2020). Results demonstrate that the proposed method has a significant reduction in both computation and memory footprint with few tuning parameters. Background earthquakes have an impression on the homogeneous Poisson process with fair memory-less characteristics in the time domain as evident from graphical and statistical analysis. Overall seismicity and observed background activity both have similar multi-fractal behavior with a deviation of +/- 0.04\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm 0.04$$\end{document}. The comparative analysis is carried out with benchmark declustering models: Gardner-Knopoff, Uhrhammer, Gruenthal window-based method, and Reasenberg's approach, and superior performance of the proposed method is found in most cases.

关键词： grid-based clustering Seismicity Earthquake catalogs Homogeneous Poisson process Morisita index Memory coefficient

来源：评论

学校读者我要写书评

暂无评论

Improving the grid-based clustering by Identifying Cluster Center Nodes and Boundary Nodes Adaptively 10th

Improving the Grid-based Clustering by Identifying Cluster C...

引用

10th International Conference on Pattern Recognition Applications and Methods (ICPRAM)

作者： Li, Yaru Xi, Yue Lu, Yonggang Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China

ISBN: (纸本)9789897584862

clustering analysis is a data analysis technology, which divides data objects into different clusters according to the similarity between them. The density-based clustering methods can identify clusters with arbitrary shapes, but its time complexity can be very high with the increasing of the number and the dimension of the data points. The grid-based clustering methods are usually used to deal with the problem. However, the performance of these grid-based methods is often affected by the identification of the cluster center and boundary based on global thresholds. Therefore, in this paper, an adaptive grid-based clustering method is proposed, in which the definition of cluster center nodes and boundary nodes is based on relative density values between data points, without using a global threshold. First, the new definitions of the cluster center nodes and boundary nodes are given, and then the clustering results are obtained by an initial clustering process and a merging process of the ordered grid nodes according to the density values. Experiments on several synthetic and real-world datasets show the superiority of the proposed method.

关键词： grid-based clustering Density Estimation Boundary Nodes clustering Analysis

来源：评论

学校读者我要写书评

暂无评论

Division of crustal units in China using grid-based clustering and a zircon U-Pb geochronology database

引用

COMPUTERS & GEOSCIENCES 2020年 145卷 104570-104570页

作者： Fang, Xianjun Wu, Yujing Liao, Sisi Xue, Lizhi Chen, Zhe Yang, Jiangnan Lu, Yamin Ling, Kun Hu, Shengyi Kong, Shuyuan Xiong, Yiwei Li, Huacheng Shang, Xiuqi Ji, Rui Lu, Xueyun Song, Biao Zhang, Lei Ji, Jianqing Peking Univ Sch Earth & Space Sci Key Lab Orogen Belts & Crustal Evolut MOE Beijing 100871 Peoples R China Chinese Acad Geol Sci Beijing SHRIMP Ctr Inst Geol Beijing 100037 Peoples R China Chinese Acad Geol Sci Inst Geol Beijing 100037 Peoples R China

Zircon U-Pb dating is one of the most effective and widely used methods due to the widespread existence of zircon as an accessory mineral in rocks and its high closure temperature. Throughout history, each region of the earth has experienced its own crustal evolution. Using zircon U-Pb geochronology data, researchers can reveal the crustal growth history and regional discrimination. In this study, a large spatial analysis was performed across China, involving more than 120,000 data records taken from the zircon U-Pb geochronology database. By applying the Gaussian multipeak fitting method, nine age peaks corresponding to crustal growth events on the continent of China were identified, which centered at 45, 132, 249, 441, 815, 1236, 1908, 2505, and 2933 Ma. Using a grid-based clustering algorithm, grids with similar crustal growth event combinations were gathered and their features extracted. based on the time series of the crustal growth events, the gathered grid clusters were further integrated into larger crustal units. We used various grid sizes in our algorithm, including 0.325 degrees x 0.325 degrees, 0.4 degrees x 0.4 degrees, 0.6 degrees x 0.6 degrees, 0.8 degrees x 0.8 degrees, 1.0 degrees x 1.0 degrees, 1.2 degrees x 1.2 degrees, and 1.4 degrees x 1.4 degrees. Although the shape and number of the crustal units varied depending on grid size, six large entities were clearly identified and were best visualized using the 0.8 degrees x 0.8 degrees, 1.0 degrees x 1.0 degrees, 1.2 degrees x 1.2 degrees, and 1.4 degrees x 1.4 degrees grids. These six entities include the Tibet-Sichuan-Yunnan, North Xinjiang, Northeast, Gansu-Qinghai, North China, and South China units. Furthermore, while there were some variations, the crustal unit results found herein were in agreement with tectonic unit research, displaying a new potential avenue of research.

关键词： Zircon U-Pb geochronology Database grid-based clustering Crustal units

来源：评论

学校读者我要写书评

暂无评论

A Fast Density-grid based clustering Method 9

A Fast Density-Grid Based Clustering Method

引用

9th IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Brown, Daniel Japa, Arialdis Shi, Yong Kennesaw State Univ Dept Comp Sci Kennesaw GA 30144 USA

ISBN: (纸本)9781728105543

clustering algorithms are a large area of focus in the world of data analytics, especially in the current age of big data sets that are large, multidimensional, and grow quickly. We also live in an age where parallel and distributed computing are at the forefront of any form of data analysis. Because of these two ideas, this paper discusses an algorithm that was designed to scale well with big data sets for fast run time, while also being highly scalable for a potential parallel version. This algorithm, the Fast Density-grid clustering Algorithm, works by dividing the data space into a grid structure and then assigning a density measurement to each grid cell. These spaces are then merged based on their densest neighbor in order to cluster the entire space. The experimental results for the serial version demonstrate that the algorithm is generally comparable to DBSCAN in accuracy, while also having a lower run time.

关键词： clustering DBSCAN density grid density grid density-based clustering grid-based clustering parallel computing distributed computing data analysis

来源：评论

学校读者我要写书评

暂无评论

grid-based dynamic clustering with grid proximity measure

引用

INTELLIGENT DATA ANALYSIS 2016年第4期20卷 853-875页

作者： Lee, Gun Ho Soongsil Univ Dept Ind & Informat Syst Engn 369 Sangdoro Seoul 156743 South Korea

This study discusses and compares grid proximity measures that use representative data points in grid cells and the average distance between the data points in grid cells. Basic theorems for the grid distance measure are formulated and proved. The grid distance measure is applied to the grid-based clustering problem where the number of clusters is dynamically determined by using a threshold value and by maximizing intra-similarity in a cluster and inter-dissimilarity between the clusters. In this study, the grid-based clustering problem is illustrated and formulated using a 0-1 integer programming approach. We perform numerical experiments on randomly generated problems and also for a clustering problem concerning microarray data of human fibroblasts in varying serum concentrations, with the latter data having been taken from a prior study. The theorems are applicable to the grid-based clustering of any data set.

关键词： grid proximity measure grid-based clustering Dynamic clustering Cluster validity index

来源：评论

学校读者我要写书评

暂无评论

Fast grid-based clustering Method for Automatic Calculation of Optimal Parameters of Skin Color Classifier for Head Tracking 2

Fast Grid-Based Clustering Method for Automatic Calculation ...

引用

IEEE 2nd International Conference on Cybernetics (CYBCONF)

作者： Szkudlarek, Michal Pietruszka, Maria Lodz Univ Technol Inst Informat Technol Lodz Poland

ISBN: (纸本)9781479983223

One of the fast method for extracting head position from the camera image is the selection of face pixels with a skin color classifier. Regardless of the chosen model of such a classifier, the problem is to automatically calculate its optimal parameters and to obtain a short computation time. In this article a new grid-based method for clustering RGB space is proposed. It allows a significant reduction in large data set size with an accurate representation and a short calculation time. The clustering method is multipurpose as it does not require any input parameters, and can operate on the large data sets and makes no assumptions about clustered data set.

关键词： data mining grid-based clustering head tracking fuzzy sets image processing

来源：评论

学校读者我要写书评

暂无评论

Density grid-based clustering for Wireless Sensors Networks

Density Grid-Based Clustering for Wireless Sensors Networks

引用

International Conference on Communications, Management, and Information Technology (ICCMIT)

作者： Abdullah, Manal Eldin, Hend Nour Al-Moshadak, Tahani Alshaik, Rawan Al-Anesi, Inas King Abdulaziz Univ Fac Comp & Informat Technol Jeddah 21413 Saudi Arabia

Wireless Sensor Networks WSNs are special networks consist of devices (sensor nodes) in large numbers and spatial distribution. They have various sensing capability and cooperate to accomplish common task. clustering is one of the most effective techniques used to solve the problem of energy consumption in WSNs. grid based clustering has proven its efficiency specially for high dynamic networks. The girds' strategy used in this research is implemented on dense network and divides the network area into multiple grid cells with different densities (High, Low, and empty). Then grids are combined to form clusters as normal and advanced clusters. Cluster head is elected for each cluster based on high energy. This new suggested strategy is implemented and tested using MATLAB. The results show that this suggested strategy works well at 150 node WSN and grid size between 510 units where the network life time is 633 seconds approximately. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： grid-based clustering Density-based clustering clustering Algorithms Wireless Sensor Network Cluster head Election

来源：评论

学校读者我要写书评

暂无评论

Density grid-based clustering for Wireless Sensors Networks

引用

Procedia Computer Science 2015年 65卷 35-47页

作者： Manal Abdullah Hend Nour Eldin Tahani Al-Moshadak Rawan Alshaik Inas Al-Anesi Faculty of Computing and Information Technology FCIT King Abdulaziz University KAU Jeddah SA

Wireless Sensor Networks WSNs are special networks consist of devices (sensor nodes) in large numbers and spatial distribution. They have various sensing capability and cooperate to accomplish common task. clustering is one of the most effective techniques used to solve the problem of energy consumption in WSNs. grid based clustering has proven its efficiency specially for high dynamic networks. The girds’ strategy used in this research is implemented on dense network and divides the network area into multiple grid cells with different densities (High, Low, and empty). Then grids are combined to form clusters as normal and advanced clusters. Cluster head is elected for each cluster based on high energy. This new suggested strategy is implemented and tested using MATLAB. The results show that this suggested strategy works well at 150 node WSN and grid size between 5-10 units where the network life time is 633 seconds approximately.

关键词： grid-based clustering Density-based clustering clustering Algorithms Wireless Sensor Network Cluster head Election

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：