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检索条件"主题词=distributed data mining"

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Performance analysis of privacy preserving distributed data mining based on cryptographic techniques 7

Performance analysis of privacy preserving distributed data ...

引用

7th International Conference on Electrical Energy Systems (ICEES)

作者： Marimuthu, Venkatesh Kumar Lakshmi, C. SRMIST Dept Comp Sci & Engn Chennai Tamil Nadu India SRMIST Dept Software Engn Chennai Tamil Nadu India

ISBN: (纸本)9781728176123

Privacy Preservation should be maintained while retrieving relevant information from multiple sources without any leakage. In order to make correct decision, data mining plays a crucial role in any business environment. Performing distributed data mining for retrieving or extracting relevant information from multiple parties without any leakage is an important issue which has to be addressed. In order to overcome this problem, privacy preserving distributed data mining methods was used for secure and reliable information sharing from multiple parties. In this paper, different privacy preservation distributed data mining techniques commonly known as cryptographic approaches like Secure Multiparty Computation Homomorphic Encryption and Secret Sharing methods were discussed and methods like homomorphic encryption and secret sharing is implemented on medical and business data. Our experimental result shows that secret sharing method performs better than homomorphic encryption.

关键词： distributed data mining privacy preserving data mining cryptography homomorphic encryption secret sharing secure multiparty computation

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Appraisal of homogeneous techniques in distributed data mining - classifier approach 16

Appraisal of homogeneous techniques in Distributed Data Mini...

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1st International Conference on Informatics and Analytics (ICIA)

作者： Urmela, S. Nandhini, M. Pondicherry Univ Dept Comp Sci Pondicherry India

ISBN: (纸本)9781450347563

In recent years, distributed data mining (DDM) has evolved in large space aiming at minimizing computation cost and memory overhead in processing huge geographically distributed data. There are two approaches of DDM - homogeneous and heterogeneous classifier approach. This paper presents implementation of four homogeneous classifier techniques for DDM with different Electronic Health Records (EHRs) homogeneous datasets namely diabetes, hepatitis, hypothyroid and further analyzing results based on metric evaluation.

关键词： distributed data mining Electronic Health Records computation cost memory overhead homogeneous approach

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A distributed data mining system for a novel ubiquitous healthcare framework

A distributed data mining system for a novel ubiquitous heal...

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7th International Conference on Computational Science (ICCS 2007)

作者： Viswanathan, M. Whangbo, T. K. Lee, K. J. Yang, Y. K. Kyungwon Univ Coll Software Kyonggi Do South Korea

ISBN: (纸本)9783540725879

Recent years have shown impressive growth in the development of ubiquitous healthcare (u-Healthcare) systems which aim for the next generation in e-Health services and associated research. Such systems are primarily being designed to provide emergency and preventive healthcare to citizens anywhere/anytime using wired and wireless mobile technologies. data mining is an indispensable aspect of such systems and represents the process of analyzing databases to extract hidden knowledge and relationships. This paper introduces and studies the development framework of a prototype ubiquitous healthcare system initiated by the South Korean government. Preliminary results with a distributed data mining system are presented in the context of a larger future integration with the ubiquitous healthcare framework.

关键词： distributed data mining ubiquitous healthcare decision supporting system healthcare data data classification

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Mobile Agent Model with Efficient Communication for distributed data mining 1

引用

1st International Conference on Internet Computing and Information Communications (ICICIC)

作者： Kavitha, S. Kumar, K. Senthil Anandam, K. V. Arul SRM Univ Dept Comp Applicat Madras Tamil Nadu India Govt Thirumagai Mills Coll Gudiyattam Tamil Nadu India

ISBN: (纸本)9788132212980;9788132212997

This paper presents the managing of large-scale distributed system with the use of mobile agent concept in distributed environment which is becoming an increasing challenging task. The primary goal is to ensure efficient use of resources, services of computer systems, and networks to provide timely services to the end users using mobile agent with decentralized processing and control in distributed resources so as to minimize the network traffic and speed up management tasks in distributed environment, provide more scalability, and to provide more flexibility in the development and maintenance of the applications. The problem with the traditional techniques is, when the number of visited nodes grows, the mobile agent size also increases and making migration harder. One possible solution to this problem is to visit a fixed number of nodes, return to the agent home or send all data to it (reducing the mobile agent size), and start the task again on the remaining nodes. The initial size of a mobile agent also affects agent performance, since the larger the size, the more difficult the migration.

关键词： Mobile agent distributed data mining Mobile agent model Communication among agents Agent architecture

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A Reliable and Intelligent Protocol for distributed data mining Architecture in Sporadic Wireless Sensor Network

A Reliable and Intelligent Protocol for Distributed Data Min...

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International Symposium on Mathematical Sciences and Computing Research (iSMSC)

作者： Wagan, Asif Ali Jung, Low Tang Univ Teknol PETRONAS Dept Comp & Informat Sci Tronoh 31750 Perak Malaysia

ISBN: (纸本)9781479978946

distributed data mining (DDM) approaches are considered most suitable for managing large datasets. DDM can reduce the communication cost, computational cost, and storage cost. However a key issue for DDM is accuracy of knowledge discovery. To mitigate the accuracy issue, it is necessary to provide reliable network. In practice, it is assumed that the network is available all the time but in reality, it may not available most of the time. In this study, we considered a sporadic wireless sensor network (SWSN), SWSN is a wireless network where most of the time a complete path is not available from a source to a destination, or such a path is highly unreliable. It is also possible in this type of network a communication path is available for a very short time and it may breaks when try to send data over it and limited storage capacity. The objective of this study is to overcome the above mentioned issues by providing a reliable and intelligent protocols for DDM architecture in a SWSN.

关键词： sporadic network distributed data mining reliable protocol intelligent protocol sporadic wireless sensor network

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Communication-Efficient Adam-Type Algorithms for distributed data mining 22

Communication-Efficient Adam-Type Algorithms for Distributed...

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22nd IEEE International Conference on data mining (ICDM)

作者： Xian, Wenhan Huang, Feihu Huang, Heng Univ Pittsburgh Dept Elect & Comp Engn Pittsburgh PA 15260 USA

ISBN: (纸本)9781665450997

distributed data mining is an emerging research topic to effectively and efficiently address hard data mining tasks using big data, which are partitioned and computed on different worker nodes, instead of one centralized server. Nevertheless, distributed learning methods often suffer from the communication bottleneck when the network bandwidth is limited or the size of model is large. To solve this critical issue, many gradient compression methods have been proposed recently to reduce the communication cost for multiple optimization algorithms. However, the current applications of gradient compression to adaptive gradient method, which is widely adopted because of its excellent performance to train DNNs, do not achieve the same ideal compression rate or convergence rate as Sketched-SGD. To address this limitation, in this paper, we propose a class of novel distributed Adam-type algorithms (i.e., SketchedAMSGrad) utilizing sketching, which is a promising compression technique that reduces the communication cost from O(d) to O(log(d)) where d is the parameter dimension. In our theoretical analysis, we prove that our new algorithm achieves a fast convergence rate of O(1/root nT + 1/(k/d)T-2) with the communication cost of O(k log(d)) at each iteration. Compared with single-machine AMSGrad, our algorithm can achieve the linear speedup with respect to the number of workers n. The experimental result of training distributed DNN validates the performance of our algorithms.

关键词： distributed data mining adaptive gradient gradient compression

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Research on distributed data mining Tool Used in Control System

Research on Distributed Data Mining Tool Used in Control Sys...

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International Conference on Advanced Computer Control

作者： Ma, Yuekun Li, Zhigang Yu, Shuh Chen, Lei Hebei Polytech Univ Coll Comp & Automat Control Tangshan 063009 Peoples R China

ISBN: (纸本)9780769535166

In this paper, A distributed data mining tool that suitable for distributed and isomeric database environment of intelligent control system by borrowing ideas from architecture of grid is introduced. It can also perform incremental data mining based on history mining result. This tool makes full use of Metadata of each kind of resources. The resources associated in the data mining are all packed into form of web set-vice, which is give a description by respective attribute document of the XML format. SOAP takes charge of the communication between the separated parts of the whole data mining-process.

关键词： distributed data mining control rule grid architecture web service metadata

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distributed data mining in the grid environment

Distributed data mining in the grid environment

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2011 IEEE International Conference on Intelligent Computing and Intelligent Systems(ICIS 2011)

作者： Wang tingzhong Academy of information technology Luoyang Normal University luoyang,China Fan ganglong Academy of information technology Luoyang Normal University luoyang,China

In many scientific and business areas, it is often necessary to analyze large data sets, maintained over geographically distributed sites, which makes DDM a major research issue on today’ data mining *** a latest member in distributed computing technology family, the grid can play a significant role in providing an effective computational support for knowledge discovery *** mining algorithm and knowledge discovery processes are both compute and data intensive;therefore the grid can offers a computing and data management infrastructure for supporting decentralized and parallel data *** paper describes the grid framework and discusses how grid computing can be used to support the distributed data ***-based data mining uses grids as decentralized platforms where to execute data mining tasks and knowledge discovery algorithms and applications .Finally the paper outlines the promising future for developing grid-based distributed data mining.

关键词： distributed data mining knowledge grid

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distributed data mining for Multiple Sourced Heterogeneous datasets: A Survey

Distributed Data Mining for Multiple Sourced Heterogeneous D...

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2018 3rd International Conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM 2018)

作者： Xing-ying LI Shan-zi LI Yi-xuan WU Ai-jia HE Xiao-ya HUANG Xin ZHAO Beijing Normal University

In the information age of the 21st century, a large amount of information is collected and applied. However, due to the heterogeneity of system environment for data storage and computing, how to mine these distributed data sources has become a valuable research topic that attracted more and more attention. In this paper, we firstly presented the problem scenario and main challenges confronting with the problem of distributed data mining on multiple sourced heterogeneous data sets. Then, we surveyed research works related to the problem and elicited their main features on different technology domains to show current distributed solutions for different data mining algorithm categories. Finally, we reviewed in detail the research works and discussed the challenges remained in the distributed data mining problem for multiple sourced heterogeneous data sets.

关键词： Multiple sourced heterogeneous data sets distributed data mining distributed algorithms

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Study on distributed data mining Model in Wireless Sensor Networks

Study on Distributed Data Mining Model in Wireless Sensor Ne...

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2010 International Conference on Intelligent Computing and Integrated Systems

作者： Hong Yuehua,Xu Shuang,Wu Huajian Yulin Normal University YuLin,P.R.China

Aiming at the severe energy and computing resource constraints of Wireless Sensor Network(WSN),based on rough set theory and ART2 network,a distributed data mining model for WSN is *** model poses a three-layer MLP for data aggregation in the clustered sensor network. And the input layer neuron and the first layer neuron are located in every cluster member,while the second layer neuron and the output layer neuron are located in every cluster head. The features of the training samples were extracted to build up the decision table;the rough set theory was applied to reduce the decision ***,the reduced decision attributes were used to construct ART2 neural network classification data. Constructed data mining algorithm can be integrated in each sensor network *** results prove data dimension is reduced and data redundancy is eliminated after the raw-data is processed by data mining algorithm,and the communication traffic is decreased and the life of WSN is extended.

关键词： wireless sensor network distributed data mining rough set theory ART2 neural network

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