Format

Send to

Choose Destination
Int J Big Data. 2015 Oct;2(2):43-56.

Automated Predictive Big Data Analytics Using Ontology Based Semantics.

Author information

1
Department of Computer Science, Statistics University of Georgia, Athens.
2
Department of Statistics University of Georgia, Athens.

Abstract

Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not always be readily available. In this paper, we propose to use semantic technology to assist data analysts and data scientists in selecting appropriate modeling techniques and building specific models as well as the rationale for the techniques and models selected. To formally describe the modeling techniques, models and results, we developed the Analytics Ontology that supports inferencing for semi-automated model selection. The SCALATION framework, which currently supports over thirty modeling techniques for predictive big data analytics is used as a testbed for evaluating the use of semantic technology.

KEYWORDS:

big-data-analytics; model-selection; ontology; semantics

PMID:
29657954
PMCID:
PMC5898823

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center