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Journal Photo for ISCSITR - International Journal of Data Science
Peer reviewed only Open Access

ISCSITR - International Journal of Data Science (ISCSITR-IJDS)

Publisher : ISCSITR
Data Science
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e-ISSN 3067-7408
Issue Frequency Half-Yearly
Est. Year 2020
Mobile 1234567809
DOI YES
Language English
APC YES
Impact Factor Assignee Google Scholar
Email editor@iscsitr.com, iscsitr@gmail.com

Journal Descriptions

ISCSITR - International Journal of Data Science (ISCSITR-IJDS) is a leading open-access, peer-reviewed journal sponsored by the International Society for Computer Science and Information Technology Research (ISCSITR). This journal is dedicated to the field of data science, offering a comprehensive forum for researchers, data scientists, and industry professionals to present their latest research findings, innovative methodologies, and technological advancements. The ISCSITR-IJDS covers a wide array of topics within data science, including but not limited to big data analytics, statistical methods, data mining, machine learning, predictive modeling, data visualization, data infrastructure, data privacy and security, and the application of data science techniques in various industries like healthcare, business, finance, and telecommunications. The journal aims to foster a deeper understanding of the vast potentials and challenges in the field of data science, promoting the development of more efficient, effective, and innovative data-driven methodologies and technologies. By maintaining an open-access model, the ISCSITR-IJDS ensures that all content is freely available, facilitating greater dissemination of information and collaboration among data science professionals worldwide. This makes it an invaluable resource for anyone involved in or interested in the latest developments in the field of data science.

ISCSITR - International Journal of Data Science (ISCSITR-IJDS) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Data Science , Online , Half-Yearly Journal

  • UGC Approved, ISSN Approved: P-ISSN E-ISSN: 3067-7408, Established: 2020,
  • Provides Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Publications of ISCSITR-IJDS

Formal Verification of Multi-Party Privacy Protocols Using Probabilistic Automata and Symbolic Abstraction in High-Stakes Data Environments
Lena Hoffmann April, 2021
Ensuring data privacy in high-stakes, multi-party computation (MPC) environments demands formally verified protocols that accommodate uncertainty and adversarial behavior. This paper present...
Multidimensional Data Modeling and Intelligent Query Processing for Enhanced Decision Support in Enterprise Data Warehouses
Carlos Ordonez September, 2023
Enterprise Data Warehouses (EDWs) have become pivotal in organizational decision-making, demanding not only robust data integration but also intelligent, efficient query handling. This paper...
Optimizing Enterprise Decision-making under Data Uncertainty Using Hybrid Predictive and Prescriptive Analytics Frameworks
Mateo González April, 2022
Uncertainty in enterprise data—stemming from market volatility, sensor errors, or incomplete records—poses significant challenges to optimal decision-making. This paper proposes a hybrid...
Multiscale Topological Characterization of Dynamic Interaction Patterns in Large-Scale Complex Networks Under Temporal Evolution Constraints
Tomas Novak April, 2020
The structural evolution of large-scale complex networks over time reveals critical insights into their dynamic behavior and underlying interaction patterns. This study proposes a multiscale...
Dynamic Knowledge Distillation Strategies for Continual Learning in Lifelong Autonomous Systems Without Catastrophic Forgetting
Yoshua Bengio March, 2025
Lifelong learning in autonomous systems demands the ability to acquire new knowledge over time without compromising previously learned information—a challenge known as catastrophic forgett...
AI-Powered Feature Engineering in Data Science Pipelines Using Automated Feature Selection and Embedding Techniques
Noah Spears June, 2024
Feature engineering is a crucial component in data science pipelines, enhancing the performance of machine learning models by transforming raw data into meaningful representations. Tradition...
Cross-Domain Comparative Analysis of Decision-Making Algorithms in Autonomous and Semi-Autonomous System Architectures
Sami Haddadin June, 2023
This study presents a comparative analysis of decision-making algorithms employed across autonomous and semi-autonomous system architectures within the fields of transportation, robotics, an...