Journal Navigation
Published: Nov 7, 2023
DOI: 10.4018/JDM.333471
Volume 35
Pasi Raatikainen, Samuli Pekkola, Maria Mäkelä
People see the world and convey their perception of it with narratives. In an information system context, stories are told and collected when the systems are developed. Requirements elicitation is... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Raatikainen, Pasi, et al. "Narrativization in Information Systems Development." JDM vol.35, no.1 2024: pp.1-30. http://doi.org/10.4018/JDM.333471

APA

Raatikainen, P., Pekkola, S., & Mäkelä, M. (2024). Narrativization in Information Systems Development. Journal of Database Management (JDM), 35(1), 1-30. http://doi.org/10.4018/JDM.333471

Chicago

Raatikainen, Pasi, Samuli Pekkola, and Maria Mäkelä. "Narrativization in Information Systems Development," Journal of Database Management (JDM) 35, no.1: 1-30. http://doi.org/10.4018/JDM.333471

Export Reference

Mendeley
Published: Nov 9, 2023
DOI: 10.4018/JDM.333519
Volume 35
Zhongliang Li, Yaofeng Tu, Zongmin Ma
Based on the relationship between client load and overall system performance, the authors propose a sample-aware deep deterministic policy gradient model. Specifically, they improve sample quality... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Li, Zhongliang, et al. "A Sample-Aware Database Tuning System With Deep Reinforcement Learning." JDM vol.35, no.1 2024: pp.1-25. http://doi.org/10.4018/JDM.333519

APA

Li, Z., Tu, Y., & Ma, Z. (2024). A Sample-Aware Database Tuning System With Deep Reinforcement Learning. Journal of Database Management (JDM), 35(1), 1-25. http://doi.org/10.4018/JDM.333519

Chicago

Li, Zhongliang, Yaofeng Tu, and Zongmin Ma. "A Sample-Aware Database Tuning System With Deep Reinforcement Learning," Journal of Database Management (JDM) 35, no.1: 1-25. http://doi.org/10.4018/JDM.333519

Export Reference

Mendeley
Published: Dec 11, 2023
DOI: 10.4018/JDM.334710
Volume 35
Zongmin Ma, Daiyi Li, Jiawen Lu, Ruizhe Ma, Li Yan
The Resource Description Framework (RDF) and RDF Schema (RDFS) recommended by World Wide Web Consortium (W3C) provide a flexible model for semantically representing data on the web. With the... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Ma, Zongmin, et al. "RDF(S) Store in Object-Relational Databases." JDM vol.35, no.1 2024: pp.1-32. http://doi.org/10.4018/JDM.334710

APA

Ma, Z., Li, D., Lu, J., Ma, R., & Yan, L. (2024). RDF(S) Store in Object-Relational Databases. Journal of Database Management (JDM), 35(1), 1-32. http://doi.org/10.4018/JDM.334710

Chicago

Ma, Zongmin, et al. "RDF(S) Store in Object-Relational Databases," Journal of Database Management (JDM) 35, no.1: 1-32. http://doi.org/10.4018/JDM.334710

Export Reference

Mendeley
Published: Jan 7, 2024
DOI: 10.4018/JDM.335888
Volume 35
Lavlin Agrawal, Pavankumar Mulgund, Raj Sharman
The adoption of empirical methods for secondary data analysis has witnessed a significant surge in IS research. However, the secondary data is often incomplete, skewed, and imbalanced at best.... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Agrawal, Lavlin, et al. "Handling Imbalanced Data With Weighted Logistic Regression and Propensity Score Matching methods: The Case of P2P Money Transfers." JDM vol.35, no.1 2024: pp.1-37. http://doi.org/10.4018/JDM.335888

APA

Agrawal, L., Mulgund, P., & Sharman, R. (2024). Handling Imbalanced Data With Weighted Logistic Regression and Propensity Score Matching methods: The Case of P2P Money Transfers. Journal of Database Management (JDM), 35(1), 1-37. http://doi.org/10.4018/JDM.335888

Chicago

Agrawal, Lavlin, Pavankumar Mulgund, and Raj Sharman. "Handling Imbalanced Data With Weighted Logistic Regression and Propensity Score Matching methods: The Case of P2P Money Transfers," Journal of Database Management (JDM) 35, no.1: 1-37. http://doi.org/10.4018/JDM.335888

Export Reference

Mendeley
Published: Feb 13, 2024
DOI: 10.4018/JDM.337971
Volume 35
Jizi Li, Xiaodie Wang, Justin Z. Zhang, Longyu Li
The acquisition and sharing of reviews have significant ramifications for the selection of crowdsourcing designs before mass production. This article studies the optimal decision of a brand... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Li, Jizi, et al. "Optimal Information Acquisition and Sharing Decisions: Joint Reviews on Crowdsourcing Product Design." JDM vol.35, no.1 2024: pp.1-34. http://doi.org/10.4018/JDM.337971

APA

Li, J., Wang, X., Zhang, J. Z., & Li, L. (2024). Optimal Information Acquisition and Sharing Decisions: Joint Reviews on Crowdsourcing Product Design. Journal of Database Management (JDM), 35(1), 1-34. http://doi.org/10.4018/JDM.337971

Chicago

Li, Jizi, et al. "Optimal Information Acquisition and Sharing Decisions: Joint Reviews on Crowdsourcing Product Design," Journal of Database Management (JDM) 35, no.1: 1-34. http://doi.org/10.4018/JDM.337971

Export Reference

Mendeley
Published: Feb 14, 2024
DOI: 10.4018/JDM.338276
Volume 35
Amit Singh, Jay Prakash, Gaurav Kumar, Praphula Kumar Jain, Loknath Sai Ambati
The use of encrypted data, the diversity of new protocols, and the surge in the number of malicious activities worldwide have posed new challenges for intrusion detection systems (IDS). In this... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Singh, Amit, et al. "Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS." JDM vol.35, no.1 2024: pp.1-25. http://doi.org/10.4018/JDM.338276

APA

Singh, A., Prakash, J., Kumar, G., Jain, P. K., & Ambati, L. S. (2024). Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS. Journal of Database Management (JDM), 35(1), 1-25. http://doi.org/10.4018/JDM.338276

Chicago

Singh, Amit, et al. "Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS," Journal of Database Management (JDM) 35, no.1: 1-25. http://doi.org/10.4018/JDM.338276

Export Reference

Mendeley
Published: Mar 8, 2024
DOI: 10.4018/JDM.339915
Volume 35
Ruizhe Ma, Weiwei Zhou, Zongmin Ma
In IoT (internet of things), most data from the connected devices change with time and have sampling intervals, which are called time-series data. It is challenging to design a time series storage... Show More
Download (PDF): Article
Add to Your Personal Library: Article
Cite Article

MLA

Ma, Ruizhe, et al. "An Efficient NoSQL-Based Storage Schema for Large-Scale Time Series Data." JDM vol.35, no.1 2024: pp.1-21. http://doi.org/10.4018/JDM.339915

APA

Ma, R., Zhou, W., & Ma, Z. (2024). An Efficient NoSQL-Based Storage Schema for Large-Scale Time Series Data. Journal of Database Management (JDM), 35(1), 1-21. http://doi.org/10.4018/JDM.339915

Chicago

Ma, Ruizhe, Weiwei Zhou, and Zongmin Ma. "An Efficient NoSQL-Based Storage Schema for Large-Scale Time Series Data," Journal of Database Management (JDM) 35, no.1: 1-21. http://doi.org/10.4018/JDM.339915

Export Reference

Mendeley
IGI Global Open Access Collection

IGI Global Open Access Collection provides all of IGI Global’s open access content in one convenient location and user-friendly interface that can easily searched or integrated into library discovery systems. Browse IGI Global Open
Access Collection

Contact
Submission-Related Inquiries
Professor Keng Siau, PhD
Head of the Department of Information Systems
Chair Professor of Information Systems
City University of Hong Kong
E-mail: isjofdm@cityu.edu.hk

Author Services Inquiries
For inquiries involving pre-submission concerns, please contact the Journal Development Division:
journaleditor@igi-global.com

Open Access Inquiries
For inquiries involving publishing costs, APCs, etc., please contact the Open Access Division:
openaccessadmin@igi-global.com

Production-Related Inquiries
For inquiries involving accepted manuscripts currently in production or post-production, please contact the Journal Production Division:
journalproofing@igi-global.com

Rights and Permissions Inquiries
For inquiries involving permissions, rights, and reuse, please contact the Intellectual Property & Contracts Division:
contracts@igi-global.com

Publication-Related Inquiries
For inquiries involving journal publishing, please contact the Acquisitions Division:
acquisition@igi-global.com

Discoverability Inquiries
For inquiries involving sharing, promoting, and indexing of manuscripts, please contact the Citation Metrics & Indexing Division:
indexing@igi-global.com

Editorial Office
701 E. Chocolate Ave.
Hershey, PA 17033, USA
717-533-8845 x100