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Analysis on Data Mining Model Objected to Internet of Things

Chunguang Zhang, Guangping Zeng, Hongbo Wang, Xuyan Tu
2012 International Journal of Advancements in Computing Technology  
Three data mining models suitable to data processing have been proposed according to some technical challenges on the characteristics data for Internet of Things.  ...  The third model is grid-based data mining model, which could utilize the potentially unlimited amount of data by using grid.  ...  regard intelligent object as a grid computing resources, using grid data mining service to realize mining operation of Internet of Things data.  ... 
doi:10.4156/ijact.vol4.issue21.73 fatcat:e4fkof4tizdctcegjqiieocwry

Data Mining Meets Grid Computing: Time to Dance? [chapter]

Alberto Sánchez, Jesús Montes, Werner Dubitzky, Julio J. Valdés, María S. Pérez, Pedro de Miguel
2009 Data Mining Techniques in Grid Computing Environments  
be mined for patterns that may help to optimize the effectiveness and efficiency of the grid computing infrastructure.  ...  Data Mining Techniques in Grid Computing Environments Edited by Werner Dubitzky  ...  job could be anything that needs a grid resource, e.g. a request for bandwidth or disk space, an application or a set of application programs. .4 DATA MINING GRID -MINING GRID DATA  ... 
doi:10.1002/9780470699904.ch1 fatcat:3ax6ir5gjnhvxbnqcq5skp7a5a

Research on Data Mining Algorithm for Mobile Internet based on Business Cloud Platform

Miao Yue, Wu Huai Guang
2016 International Journal of Grid and Distributed Computing  
Mobile Internet is a mainstream access and communication technology, due to access to Internet anytime and anywhere, the business will varied, and bring mass data, but the data processing has different  ...  Therefore, it is necessary to apply to different data mining methods in the cloud platform, so as to adapt to different business applications, this paper proposes an improved Apriori algorithm, theory  ...  and working way of grid composition, Cloud computing is the product of the integration of traditional computer technology such as grid computing, distributed computing, parallel computing, utility computing  ... 
doi:10.14257/ijgdc.2016.9.5.01 fatcat:in2ozdjeuzbvrfdzk4hvqxrety

Techniques, Models and Challenges of Data Mining in Internet of Things (IOT)

2019 International journal of recent technology and engineering  
Thus, data mining is a process which extracts high business data from huge amount of data easily.  ...  In this paper, a systematic review has been carried out on various data mining techniques and models that have been applied in IoT.  ...  Also, Grid data mining of IoT uses the hardware like RFID, WSAN, WSN, Sensor nodes etc. Grid computing has the capability of efficient computing property over diverse environment.  ... 
doi:10.35940/ijrte.d5238.118419 fatcat:arzckqaskbcvfettnfbqr7bm3e

A Review of Big Data Resource Management: Using Smart Grid Systems as a Case Study

Muhammad Fawad Khan, Muhammad Azam, Muhammad Asghar Khan, Fahad Algarni, Mujaddad Ashfaq, Ibtihaj Ahmad, Insaf Ullah
2021 Wireless Communications and Mobile Computing  
Large data sets created by smart grids or other data-generating sources may be handled using such tools and approaches.  ...  Therefore, in this article, we aim to cover the topic of resource management for big data in detail. We addressed resource management from the perspective of smart grids for a better understanding.  ...  However, there is no sorting process for the multitudes of data mined from the internet.  ... 
doi:10.1155/2021/3740476 doaj:1a7f146c800c4917b0ba0a2ba51169d5 fatcat:6u4s6fypknefxoguxqwsf33sly

Parallel data intensive computing in scientific and commercial applications

Mario Cannataro, Domenico Talia, Pradip K Srimani
2002 Parallel Computing  
The integration of parallel and distributed computational environments will produce major improvements in performance for both computing intensive and data intensive applications in the future.  ...  Large scale data intensive computing plays an increasingly important role in many scientific activities and commercial applications, whether it involves data mining of commercial transactions, experimental  ...  Gerhard Joubert for many helpful suggestions that improved the contents and the presentation of this paper.  ... 
doi:10.1016/s0167-8191(02)00091-1 fatcat:qetjnt73xrbf3eil5p6suwx4ua

Mining Association Rules in Various Computing Environments: A Survey [article]

Sudhakar Singh, Pankaj Singh, Rakhi Garg, P. K. Mishra
2019 arXiv   pre-print
Association Rule Mining (ARM) is one of the well know and most researched technique of data mining. There are so many ARM algorithms have been designed that their counting is a large number.  ...  for adopting new machinery.  ...  Research in data mining on grid computing environment can be categorized into two directions, grid based data mining applications and grid based data mining algorithms.  ... 
arXiv:1908.07918v1 fatcat:uzt4vtybcnh67fdy476qjbdhxy

Guest Editors' Introduction: Internet Access to Scientific Data

D. Korsemeyer, C.W. Thompson
2005 IEEE Internet Computing  
Simulations, queries, and data mining can generate very large derived data sets.  ...  services, and data mining services.  ... 
doi:10.1109/mic.2005.15 fatcat:6mcb62wvjvcvjodj6ap4b2hwua

Analysis of Massive Unstructured Data Model Based on Clustering Algorithm

2018 Academic Journal of Computing & Information Science  
With the rapid development of the Internet and the Internet of Things, the degree of informatization of various industries has rapidly increased, and modern computers can easily collect large amounts of  ...  data.  ...  For the clustering algorithm, the number of grids is required to be limited. Therefore, the setting of the grid size also needs to be compromised.  ... 
doi:10.25236/ajcis.010004 fatcat:l4m7mpdgtngj3lubdc5jlujncy

PARALLEL AND DISTRIBUTED KNOWLEDGE DISCOVERY ON THE GRID: A REFERENCE ARCHITECTURE

M. CANNATARO, D. TALIA
2000 Algorithms and Architectures for Parallel Processing  
In an increasing number of scientific and commercial areas, tools and systems for the analysis of large data sets are emerging as important resources.  ...  In this paper we introduce a reference software architecture for PDKD systems that is built on top of computational grids that provide dependable, consistent, and pervasive access to high-end computational  ...  Those systems operate on clusters of computers or over the Internet, but, none of those we know make use of the computational grid infrastructure for the implementation of the basic services of authentication  ... 
doi:10.1142/9789812792037_0063 fatcat:mxc7r6ppurd5hpsf3q4dxjc5ym

Discovery net

V. Ćurčin, M. Ghanem, Y. Guo, M. Köhler, A. Rowe, J. Syed, P. Wendel
2002 Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '02  
This paper provides a blueprint for constructing collaborative and distributed knowledge discovery systems within Grid-based computing environments.  ...  We show how this architecture will behave during a typical KDD process design and deployment, how it enables the execution of complex and distributed data mining tasks with high performance and how it  ...  ACKNOWLEDGEMENTS We would like to thank the EPSRC, the DTI, the UK e-Science core programme and InforSense for supporting this work.  ... 
doi:10.1145/775047.775145 dblp:conf/kdd/CurcinGGKRSW02 fatcat:ysl6vsxbrbhc5fujc57f46sds4

Research on Data Mining Algorithm based on Business Cloud Platform for Mobile Internet

Fenghua Liu
2016 International Journal of u- and e- Service, Science and Technology  
Cloud computing often confusedwith the traditional grid computing(distributed computing, a virtual super computer that consisting with a group of loosely coupled computer sets, is used to perform a large  ...  Data mining technology is developing rapidly due to currently in the possession of the world's great amount of data and social of these data resources transformation for the huge demand of information  ...  This shows that the data mining of the cloud environment for the company operations or research has practical significance.  ... 
doi:10.14257/ijunesst.2016.9.2.33 fatcat:adbcpley6zanzk4nq34zufg6si

KNOWLEDGE GRID: High Performance Knowledge Discovery Services on the Grid [chapter]

Mario Cannataro, Domenico Talia, Paolo Trunfio
2001 Lecture Notes in Computer Science  
Section 2 discusses the requirements of parallel and distributed data mining on grids and what basic services the grid offers as basic support for PDKD.  ...  computing resources for data-mining petabyte-scale applications that both address high-performance and wide area operations.  ...  Grid applications often involve large amounts of data and/or computing, and are not easily handled by today's Internet and Web infrastructures.  ... 
doi:10.1007/3-540-45644-9_5 fatcat:zdm5pz45lnd5bf2vkrxvrjo7ai

Multi-source data processing and fusion method for power distribution internet of things based on edge intelligence [article]

Quande Yuan, Yuzhen Pi, Lei Kou, Fangfang Zhang, Yang Li, Zhenming Zhang
2022 arXiv   pre-print
By introducing the Box-Cox transform to improve the data offset problem in the Zscore normalization process, a multi-source heterogeneous data processing method for distribution networks based on the Box-Cox  ...  With the rapid advancement of the Energy Internet strategy, the number of sensors within the Power Distribution Internet of Things (PD-IoT) has increased dramatically.  ...  In addition, the model lays the foundation for intelligent computing and advanced applications at the edge of the distribution grid.  ... 
arXiv:2203.17230v1 fatcat:fwrb46t775anvnh76b7wssvixe

NFDDC: Novel Neuro-Fuzzy Logic based Methodology for Distributed Data Classification

2019 International journal of recent technology and engineering  
With the growing culture of Internet applications and their usage lead to challenging task for storing a massive volume of high-velocity data from different fields.  ...  Therefore, a big data mining technique is introducing by modifying traditional data mining scheme using a novel of Neuro-Fuzzy Logic based approach, i.e. named as NFDDC.  ...  outlier detection method for distributed data sets.  ... 
doi:10.35940/ijrte.d7576.118419 fatcat:egnszq4jknaavgetlnatx43kuy
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