Ontological Framework for Integrating Predictive Analytics, AI, and Big Data in Decision-Making Systems Using Knowledge Graph

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022577" target="_blank" >RIV/62690094:18450/25:50022577 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.5220/0013514400003970" target="_blank" >http://dx.doi.org/10.5220/0013514400003970</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0013514400003970" target="_blank" >10.5220/0013514400003970</a>

Result language

angličtina

Original language name

Ontological Framework for Integrating Predictive Analytics, AI, and Big Data in Decision-Making Systems Using Knowledge Graph

Original language description

The rapid development of AI, big data and DSS is changing decision-making processes by enabling the efficient processing of huge volumes of data for strategic and operational decisions. The increasing complexity of data-driven decision making requires the integration of predictive analytics, machine learning and knowledge-based systems. This paper presents an ontological framework that uses a knowledge graph to systematically depict the interrelationships between these technologies and supports transparent, efficient and ethical decision making in the areas of business intelligence, healthcare, public policy and crisis management. It also addresses challenges such as algorithmic bias, ethical considerations and explain ability and highlights the need for responsible AI deployment. © 2025 by Paper published under CC license (CC BY-NC-ND 4.0).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the International Conference on Simulation and Modeling Methodologies, Technologies and Applications

ISBN

978-989-758-759-7

ISSN

2184-2841

e-ISSN

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Number of pages

8

Pages from-to

287-294

Publisher name

Science and Technology Publications, Lda

Place of publication

Setúbal

Event location

Bilbao

Event date

Jun 11, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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