Paper Info
Title
Automating Big Data Analysis Based on Deep Learning Generation by Automatic Service Composition
Abstract
Automation of Big Data Analysis (BDA) procedure gives us a great profit in the era of Big Data and Artificial Intelligence. BDA procedure can be efficiently automated by the automatic service composition concept efficiently. Our previous work for Auto-BDA shows a great future prospect in reducing turnaround time for data analysis. Moreover, it requires consideration of the automation with a well-geared combination of the data preparation and the optimal model (deep learning) generation. This paper shows the construction of automating BDA and model generation (here deep learning) together with data preparation and parameter optimization.
Year
DOI
Venue
2019
10.1109/DSAA.2019.00081
2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)
Keywords
Field
DocType
Big-Data-Analysis,automation,automatic-service-composition,CRISP-DM,deep-learning-generation
Software engineering,Computer science,Automation,Service composition,Turnaround time,Artificial intelligence,Deep learning,Big data,Data preparation
Conference
ISSN
ISBN
Citations 
2472-1573
978-1-7281-4494-8
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Incheon Paik124138.80
T. H. Akila S. Siriweera232.10