loading
Documents

Research.Publish.Connect.

Paper

Authors: Mohamad Omar Nachawati ; Alexander Brodsky and Juan Luo

Affiliation: George Mason University, United States

ISBN: 978-989-758-247-9

Keyword(s): Advanced Analytics, Decision Guidance Management Systems, Decision Support Systems, Decision Management Systems, Knowledge Management, Modeling, Simulation, Optimization, Machine Learning.

Related Ontology Subjects/Areas/Topics: Databases and Information Systems Integration ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Non-Relational Databases ; Query Languages and Query Processing ; Tools, Techniques and Methodologies for System Development

Abstract: Enterprises across all industries increasingly depend on decision guidance systems to facilitate decision-making across all lines of business. Despite significant technological advances, current paradigms for developing decision guidance systems lead to a tight-integration of the analytic models, algorithms and underlying tools that comprise these systems, which inhibits both reusability and interoperability. To address these limitations, this paper focuses on the development of the Unity analytics engine, which enables the construction of decision guidance systems from a repository of reusable analytic models that are expressed in JSONiq. Unity extends JSONiq with support for algebraic modeling using a symbolic computation-based technique and compiles reusable analytic models into lower-level, tool-specific representations for analysis. In this paper, we also propose a conceptual architecture for a Decision Guidance Management System, based on Unity, to support the rapid development of decision guidance systems. Finally, we conduct a preliminary experimental study on the overhead introduced by automatically translating reusable analytic models into tool-specific representations for analysis. Initial results indicate that the execution times of optimization models that are automatically generated by Unity from reusable analytic models are within a small constant factor of that of corresponding, manually-crafted optimization models. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.80.4.76

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Nachawati, M.; Brodsky, A. and Luo, J. (2017). Unity Decision Guidance Management System: Analytics Engine and Reusable Model Repository.In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 312-323. DOI: 10.5220/0006338703120323

@conference{iceis17,
author={Mohamad Omar Nachawati. and Alexander Brodsky. and Juan Luo.},
title={Unity Decision Guidance Management System: Analytics Engine and Reusable Model Repository},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={312-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006338703120323},
isbn={978-989-758-247-9},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Unity Decision Guidance Management System: Analytics Engine and Reusable Model Repository
SN - 978-989-758-247-9
AU - Nachawati, M.
AU - Brodsky, A.
AU - Luo, J.
PY - 2017
SP - 312
EP - 323
DO - 10.5220/0006338703120323

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.