Research on distributed data stream mining algorithms based on matrix weighted association rules

2020 ◽  
Vol 18 (2) ◽  
pp. 133-143
Author(s):  
Dong Xu
Keyword(s):  
Association Rules ◽  
Data Stream ◽  
Data Stream Mining ◽  
Distributed Data ◽  
Stream Mining ◽  
Weighted Association Rules ◽  
Mining Algorithms

Research on the Mining Technology of Multimedia Communication Data Flow Based on Computer Network

2013 ◽  
Vol 380-384 ◽  
pp. 3570-3574
Author(s):  
Yong Hong Cheng ◽  
Li Hua Ouyang ◽  
Xin Yan Liu
Keyword(s):  
Data Stream ◽  
High Speed ◽  
Data Flow ◽  
Computer Network ◽  
Multimedia Communication ◽  
Data Stream Mining ◽  
Stream Mining ◽  
Mining Technology ◽  
Daily Work ◽  
Mining Algorithms

computer network multimedia communication has spread all over daily work and life fields, people also have put forward higher requirements for computer multimedia communication network. Based on current network multimedia communication, there are a large amount of data transmission, high-speed and dynamic characteristics, the mining technology of its communication data flow is carried out related to research. In this paper, the frequent item sets of data stream mining technology is carried out related to research, and the classical HCOUNT algorithm is carried out relevant analysis, according to the relevant analysis, the classical HCOUNT algorithm is improved, in order to alleviate possible error problem in data mining. Finally, the data stream mining algorithms are carried out relevant analysis of actual experimental data. Study on the technical aspects of the data flow mining in computer network multimedia communication, it is an important role in the development of the computer network multimedia communication. Study on the improvement of the current algorithm, it provides reference in the similar field of algorithm research

VEDAS: A Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring

2004 ◽  
Author(s):  
Hillol Kargupta ◽  
Ruchita Bhargava ◽  
Kun Liu ◽  
Michael Powers ◽  
Patrick Blair ◽  
...  
Keyword(s):  
Real Time ◽  
Data Stream ◽  
Data Stream Mining ◽  
Distributed Data ◽  
Stream Mining ◽  
Mining System ◽  
Vehicle Monitoring

Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms

2016 ◽  
Vol 20 (3) ◽  
pp. 147 ◽  
Author(s):  
Hang Yang ◽  
Simon Fong ◽  
Kyungeun Cho ◽  
Junbo Wang
Keyword(s):  
Pattern Recognition ◽  
Sensor Network ◽  
Human Activities ◽  
Data Stream ◽  
Data Stream Mining ◽  
Stream Mining ◽  
Using Data ◽  
Mining Algorithms

Algorithms for Distributed Data Stream Mining

2007 ◽  
pp. 309-331 ◽  
Author(s):  
Kanishka Bhaduri ◽  
Kamalika Das ◽  
Krishnamoorthy Sivakumar ◽  
Hillol Kargupta ◽  
Ran Wolff ◽  
...  
Keyword(s):  
Data Stream ◽  
Data Stream Mining ◽  
Distributed Data ◽  
Stream Mining

scholarly journals Research on wireless distributed financial risk data stream mining based on dual privacy protection

2020 ◽  
Author(s):  
Yuhao Zhao
Keyword(s):  
Data Mining ◽  
Data Streams ◽  
Privacy Protection ◽  
Data Stream ◽  
Financial Risk ◽  
Data Stream Mining ◽  
Distributed Data ◽  
Stream Mining ◽  
Mining Technology ◽  
Distributed Data Streams

Abstract With the advancement of network technology and large-scale computing, distributed data streams have been widely used in the application of financial risk analysis. However, while data mining reveals financial models, it also increasingly poses a threat to privacy. Therefore, how to prevent privacy leakage during the efficient mining process poses new challenges to the data mining technology. This article is mainly aimed at the current privacy data leakage in financial data mining, combined with existing data mining technology to study data mining and privacy protection. First, a data mining model for dual privacy protection is defined, which can better meet the characteristics of distributed data streams while achieving privacy protection effects. Secondly, a privacy-oriented data stream mining algorithm is proposed, which uses random interference technology to effectively protect the original sensitive data. Finally, the analysis and discussion of the algorithm in this paper through simulation experiments show that the algorithm is feasible and effective, and can better adapt to the distributed data flow distribution and dynamic characteristics, while achieving better privacy protection effects, effectively Reduced communication load.

scholarly journals Research on Distributed Data Stream Mining of Financial Risk Based on Double Privacy Protection

2020 ◽  
Author(s):  
Yuhao Zhao
Keyword(s):  
Data Mining ◽  
Data Streams ◽  
Privacy Protection ◽  
Data Stream ◽  
Financial Risk ◽  
Data Stream Mining ◽  
Distributed Data ◽  
Stream Mining ◽  
Mining Technology ◽  
Distributed Data Streams

Abstract With the advancement of network technology and large-scale computing, distributed data streams have been widely used in the application of financial risk analysis. However, while data mining reveals financial models, it also increasingly poses a threat to privacy. Therefore, how to prevent privacy leakage during the efficient mining process poses new challenges to the data mining technology. This article is mainly aimed at the current privacy data leakage in financial data mining, combined with existing data mining technology to study data mining and privacy protection. First, a data mining model for dual privacy protection is defined, which can better meet the characteristics of distributed data streams while achieving privacy protection effects. Secondly, a privacy-oriented data stream mining algorithm is proposed, which uses random interference technology to effectively protect the original sensitive data. Finally, the analysis and discussion of the algorithm in this paper through simulation experiments show that the algorithm is feasible and effective, and can better adapt to the distributed data flow distribution and dynamic characteristics, while achieving better privacy protection effects, effectively Reduced communication load.

scholarly journals Data Stream Mining Algorithms for Building Decision Models in a Computer Role-Playing Game Simulation

2010 ◽  
Author(s):  
Rosane Maria Maffei Vallim ◽  
André Carlos Ponce de Leon Ferreira de Carvalho ◽  
João Gama
Keyword(s):  
Data Stream ◽  
Role Playing ◽  
Decision Models ◽  
Data Stream Mining ◽  
Stream Mining ◽  
Role Playing Game ◽  
Game Simulation ◽  
Mining Algorithms
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