DocumentCode :
186121
Title :
Predicate-Based Cloud Computing
Author :
Hashem, Hadi ; Ranc, Daniel
Author_Institution :
LOR Software-Networks Dept., Inst. Mines-Telecom, Evry, France
fYear :
2014
fDate :
10-12 Sept. 2014
Firstpage :
131
Lastpage :
136
Abstract :
Consumer interaction on Internet is establishing a new digital channel between the brands and their audiences. Exabytes of data are created everyday as information based on data models that keep growing in volume and variety. Predictive consumer scoring models have achieved significant lifts in conversion rates. Using the statistical techniques and other consumer web pioneers, personalized Predicate Models can be built to identify the potential of consumers. The dynamic model to discuss in this paper offers help in the challenge of managing data processing. We will mention the basics of this study, on how to capture and collect data, build connections and identify data types based on sample analysis. Next, we explain in details how to use Expert Systems to improve Cloud Computing. Finally, we expose some use-cases.
Keywords :
cloud computing; consumer behaviour; expert systems; statistical analysis; Internet; brands; consumer interaction; data models; digital channel; expert systems; predicate-based cloud computing; predictive consumer scoring models; statistical techniques; Cloud computing; Computational modeling; Data models; Databases; Engines; Roads; Servers; Cloud Computing; Inference Engine; Predicate-based Reasoning; Statistical Data Modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Next Generation Mobile Apps, Services and Technologies (NGMAST), 2014 Eighth International Conference on
Conference_Location :
Oxford
Print_ISBN :
978-1-4799-5072-0
Type :
conf
DOI :
10.1109/NGMAST.2014.29
Filename :
6982904
Link To Document :
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