Paper Info
Title
Intelligent Big Data Analysis Architecture Based on Automatic Service Composition
Abstract
Big Data contains massive information, which are generating from heterogeneous, autonomous sources with distributed and anonymous platforms. Since, it raises extreme challenge to organizations to store and process these data. Conventional pathway of store and process is happening as collection of manual steps and it is consuming various resources. An automated real-time and online analytical process is the most cognitive solution. Therefore it needs state of the art approach to overcome barriers and concerns currently facing by the Big Data industry. In this paper we proposed a novel architecture to automate data analytics process using Nested Automatic Service Composition (NASC) and CRoss Industry Standard Platform for Data Mining (CRISP-DM) as main based technologies of the solution. NASC is well defined scalable technology to automate multi-disciplined problems domains. Since CRISP-DM also a well-known data science process which can be used as innovative accumulator of multi-dimensional data sets. CRISP-DM will be mapped with Big Data analytical process and NASC will automate the CRISP-DM process in an intelligent and innovative way.
Year
DOI
Venue
2015
10.1109/BigDataCongress.2015.46
2015 IEEE International Congress on Big Data
Keywords
Field
DocType
Big data analytics,Nested Automatic Service composition,Data mining,Architecture,CRSIP-DM
Data science,Data mining,Data architecture,Architecture,Data set,Data analysis,Unified Modeling Language,Computer science,Service composition,Big data,Database,Scalability
Conference
ISSN
Citations 
PageRank 
2379-7703
6
0.62
References 
Authors
5
4
Name
Order
Citations
PageRank
T. H. A. S. Siriweera1191.91
Incheon Paik224138.80
Banage T. G. S. Kumara3629.65
K. R. C. Koswatta460.62