scholarly journals Effective Visual Big Data Processing with Machine Learning Methodologies

2019 ◽  
Vol 8 (12S) ◽  
pp. 1148-1152
Keyword(s):  
Machine Learning ◽  
Experimental Study ◽  
Big Data ◽  
Query Processing ◽  
Processing Technique ◽  
Time Data ◽  
Distributed Query Processing ◽  
Distributed Query ◽  
Real Time Data ◽  
Online Business

Development of high web utilization made business procedures in a difficult manner. In request to dissect the online business un-organized and gigantic measure of information is unimaginable with the Traditional frameworks. Recent innovations propel the strategies for examination are made to break down a lot of the information utilizing the Big Data Techniques, and to improve the adaptability and the precision of investigating the business methodologies, it has actualized on Hadoop with parallel preparing. This paper presents the experimental study on IBM real time data of one lakh records for demonstrating the efficiency of proposed Hadoop based distributed query processing technique.

scholarly journals Technical challenges and perspectives in batch and stream big data machine learning

2017 ◽  
Vol 7 (1.3) ◽  
pp. 48 ◽  
Author(s):  
KVSN Rama Rao ◽  
Sivakannan S ◽  
M.A. Prasad ◽  
R. Agilesh Saravanan
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Internet Of Things ◽  
Social Networking ◽  
Paradigm Shift ◽  
Machine Learning Algorithms ◽  
Smart Phones ◽  
Time Data ◽  
Predominant Role ◽  
Real Time Data

Machine Learning is playing a predominant role across various domains. However traditional Machine Learning algorithms are becoming unsuitable for majority of applications as the data is acquiring new characteristics. Sensors, devices, servers, Internet, Social Networking, Smart phones and Internet of Things are contributing the major sources of data. Hence there is a paradigm shift in the Machine learning with the advent of Big Data. Research works are in evolution to deal with Big Data Batch and stream real time data. In this paper, we highlighted several research works that contributed towards Big Data Machine Learning.

Using machine learning and big data approaches to predict travel time based on historical and real-time data from Taiwan electronic toll collection

2017 ◽  
Vol 22 (17) ◽  
pp. 5707-5718 ◽  
Author(s):  
Shu-Kai S. Fan ◽  
Chuan-Jun Su ◽  
Han-Tang Nien ◽  
Pei-Fang Tsai ◽  
Chen-Yang Cheng
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Travel Time ◽  
Real Time ◽  
Time Data ◽  
Electronic Toll Collection ◽  
Real Time Data ◽  
Toll Collection

QoS-based Distributed Query Processing

2004 ◽  
Vol 9 (5-6) ◽  
pp. 205-234 ◽  
Author(s):  
Haiwei Ye ◽  
Brigitte Kerhervé ◽  
Gregor V Bochmann
Keyword(s):  
Query Processing ◽  
Distributed Query Processing ◽  
Distributed Query

Machine Learning for Real-time Data Reduction in Cloud of Things

2020 ◽  
Author(s):  
Atheer Alahmed ◽  
Amal Alrasheedi ◽  
Maha Alharbi ◽  
Norah Alrebdi ◽  
Marwan Aleasa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Data Reduction ◽  
Time Data ◽  
Real Time Data
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