On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine

2019 ◽  
pp. 347-354 ◽  
Author(s):  
Maciej Jaworski ◽  
Piotr Duda ◽  
Danuta Rutkowska ◽  
Leszek Rutkowski
Keyword(s):  
Data Stream ◽  
Missing Values ◽  
Restricted Boltzmann Machine ◽  
Data Stream Mining ◽  
Boltzmann Machine ◽  
Stream Mining ◽  
Mining Algorithms

Resource-Aware Data Stream Mining Using the Restricted Boltzmann Machine

2019 ◽  
pp. 384-396 ◽  
Author(s):  
Maciej Jaworski ◽  
Leszek Rutkowski ◽  
Piotr Duda ◽  
Andrzej Cader
Keyword(s):  
Data Stream ◽  
Restricted Boltzmann Machine ◽  
Data Stream Mining ◽  
Boltzmann Machine ◽  
Stream Mining ◽  
Resource Aware

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

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

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

Measuring Different Tasks for Unstructured Data and High Speed Data in Data Stream Mining

2019 ◽  
Vol 7 (5) ◽  
pp. 582-589
Author(s):  
K. Rajasekhar ◽  
P. Venkata Maheswara
Keyword(s):  
Data Stream ◽  
High Speed ◽  
Unstructured Data ◽  
Data Stream Mining ◽  
Stream Mining ◽  
High Speed Data

Kennard-Stone Balance Algorithm for Time-series Big Data Stream Mining

2020 ◽  
Author(s):  
Tengyue Li ◽  
Simon Fong ◽  
Yaoyang Wu ◽  
Antonio J. Tallon-Ballesteros
Keyword(s):  
Time Series ◽  
Big Data ◽  
Data Stream ◽  
Data Stream Mining ◽  
Stream Mining
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