Reference health
Artificial intelligence and machine learning
2 of 77 checkable references need attention · checked 2026-08-10
At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.
23 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
References needing attention
does not resolve to a known work10.1609/aimag.v27i4.1904
does not resolve to a known work10.1093/2Fmind/2FLIX.236.433
The 75 checked references that resolve
resolves10.1007/s12525-021-00459-2
Machine learning in information systems - a bibliographic review and open research issues
resolves10.1111/j.1365-2575.2006.00208.x
Cognitive biases and decision support systems development: a design science approach
resolves10.5445/IR/1000085769
How to Cope with Change? Preserving Validity of Predictive Services over Time
resolves10.1109/ICETET.2008.239
Usage of Nearest Neighborhood, Decision Tree and Bayesian Classification Techniques in Development of Weight Management Counseling System
resolves10.1002/9781444324044
The Handbook of Computational Linguistics and Natural Language Processing
resolves10.1016/j.ijinfomgt.2021.102383
Artificial intelligence in information systems research: A systematic literature review and research agenda
resolves10.1007/s12525-018-0309-2
Design principles for a hybrid intelligence decision support system for business model validation
resolves10.1016/j.eap.2017.12.006
Trends and priority shifts in artificial intelligence technology invention: A global patent analysis
resolves10.1016/j.eswa.2007.11.059
Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering
resolves10.1007/s12599-019-00583-6
A Reinforcement Learning Based Model for Adaptive Service Quality Management in E-Commerce Websites
resolves10.1016/j.eswa.2003.10.007
Using a hybrid rule-based approach in developing an intelligent tutoring system with knowledge acquisition and update capabilities
resolves10.1007/s12525-019-00337-y
Value co-creation practices in business-to-business platform ecosystems
resolves10.1007/s12525-019-00336-z
Cognitive computing for customer profiling: meta classification for gender prediction
resolves10.1007/s12525-021-00506-y
Creating customer value from data: foundations and archetypes of analytics-based services
resolves10.1145/2628194.2628239
A study of machine learning methods for detecting user interest during web sessions
resolves10.1057/s41303-017-0044-3
Design and evaluation of a model-driven decision support system for repurposing electric vehicle batteries
resolves10.1007/978-94-009-0279-4_9
Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming
resolves10.17705/1CAIS.04845
How to Conduct Rigorous Supervised Machine Learning in Information Systems Research: The Supervised Machine Learning Report Card
resolves10.1007/s12525-019-00351-0
Supporting customer-oriented marketing with artificial intelligence: automatically quantifying customer needs from social media
resolves10.1016/j.cogsys.2017.08.003
The role of cognitive architectures in general artificial intelligence
resolves10.1057/ejis.2016.2
Utilizing big data analytics for information systems research: challenges, promises and guidelines
resolves10.1016/j.acra.2017.12.027
Artificial Intelligence and Radiology: Have Rumors of the Radiologist's Demise Been Greatly Exaggerated?
resolves10.1126/science.198.4319.816
Cognitive Psychology:
<i>Cognition and Reality</i>
. Principles and Implications of Cognitive Psychology. Ulric Neisser. Freeman, San Francisco, 1976. xvi, 230 pp. Cloth, $12.50; paper, $4.95.
resolves10.1007/s12525-015-0182-1
Smart technologies for personalized experiences: a case study in the hospitality domain
resolves10.1007/s12525-020-00433-4
The impact of artificial intelligence on event experiences: a scenario technique approach
resolves10.1080/12460125.2019.1646509
Cognitive bias, decision styles, and risk attitudes in decision making and DSS
resolves10.1080/12460125.2019.1623534
Analytics, bias, and evidence: the quest for rational decision making
resolves10.1016/0191-2607(90)90068-H
A knowledge-based decision support architecture for advanced traffic management
resolves10.48550/arXiv.1709.05412
Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition
resolves10.3390/en8088300
Learning Agent for a Heat-Pump Thermostat with a Set-Back Strategy Using Model-Free Reinforcement Learning
resolves10.1017/S0269888900007724
Artificial intelligence—a modern approach by Stuart Russell and Peter Norvig, Prentice Hall. Series in Artificial Intelligence, Englewood Cliffs, NJ.
resolves10.1080/07421222.2017.1394049
Exploring Emerging Hacker Assets and Key Hackers for Proactive Cyber Threat Intelligence
resolves10.17705/1jais.00608
"Research Perspectives: The Rise of Human Machines: How Cognitive Computing Systems Challenge Assumptions of User-System Interaction "
resolves10.1109/TSMCC.2004.841910
Agent-Based Evolutionary Approach for Interpretable Rule-Based Knowledge Extraction
resolves10.18653/v1/N16-2013
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
resolves10.18653/v1/W17-5524
VOILA: An Optimised Dialogue System for Interactively Learning
Visually-Grounded Word Meanings (Demonstration System)
resolves10.1016/j.compag.2020.105256
Decision support systems for agriculture 4.0: Survey and challenges
resolves10.1016/j.eswa.2008.09.032
Online updating belief rule based system for pipeline leak detection under expert intervention
The 23 references without a DOI — listed, not checked
no DOI — not checkedAbasolo, J. M., & Gomez, M. (2000). MELISA: An ontology-based agent for information retrieval in medicine. Proceedings of the 1st international workshop on the semantic web (SemWeb2000), 73–82.
no DOI — not checkedBellman, R. (1978). In Boyd & Fraser. (Ed.), An introduction to artificial intelligence: Can computers think?
no DOI — not checkedBrynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review, 1–20.
no DOI — not checkedCamerer, C. F. (2017). Artificial intelligence and behavioral economics. In Economics of Artificial Intelligence. University of Chicago Press.
no DOI — not checkedChuang, T.-T., & Yadav, S. B. (1997). An agent-based architecture of an adaptive decision support system. Americas Conference on Information Systems, Indianapolis, IN.
no DOI — not checkedCopeland, M. (2016). What’s the difference between artificial intelligence. Machine learning, and deep learning, 29. https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/. Accessed 3 May 2022.
no DOI — not checkedDejoux, C., & Léon, E. (2018). Métamorphose des managers à l’ère du numérique et de l’intelligence artificielle. Pearson.
no DOI — not checkedGuizzo, E. (2014). How Aldebaran robotics built its friendly humanoid robot, pepper. IEEE Spectrum. https://www.spectrum.ieee.org/how-aldebaran-robotics-built-its-friendly-humanoid-robot-pepper
no DOI — not checkedHastie, T., Tibshirani, R., & Friedman, J. (2017). The elements of statistical learning: Data mining, inference and prediction (Vol. 9). Springer.
no DOI — not checkedHegazy, I. M., Faheem, H. M., Al-Arif, T., & Ahmed, T. (2005). Performance evaluation of agent-based IDS. Proceedings of the 2nd international conference on intelligent computing and information systems (ICICIS 2005) (pp. 314–319).
no DOI — not checkedHemmer, P., Schemmer, M., Vössing, M., & Kühl, N. (2021). Human-AI complementarity in hybrid intelligence systems: A structured literature review. PACIS 2021 Proceedings.
no DOI — not checkedICO. (2017). Big data, artificial intelligence, machine learning and data protection. https://www.ico.org.uk/media/for-organisations/documents/2013559/big-data-ai-ml-and-data-protection.pdf
no DOI — not checkedJames, H., & Paul, R. (2018). Collaborative intelligence: Humans and AI are joining forces (pp. 114–123). Harvard Business Review.
no DOI — not checkedLiebman, E., Saar-Tsechansky, M., & Stone, P. (2015). Dj-mc: A reinforcement-learning agent for music playlist recommendation. Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 591–599.
no DOI — not checkedMcDermott, D., & Charniak, E. (1985). Introduction to artificial intelligence. International Journal of Adaptive Control and Signal Processing, 2(2), 148–149.
no DOI — not checkedNewell, A., & Simon, H. A. (1961). GPS, a program that simulates human thought. (Report of the Defense Technical Information Center). https://www.apps.dtic.mil/sti/citations/AD0294731
no DOI — not checkedOroszi, F., & Ruhland, J. (2010). An early warning system for hospital acquired. 18th European Conference on Information Systems (ECIS). https://www.aisel.aisnet.org/ecis2010/93
no DOI — not checkedPoole, D. L., Mackworth, A., & Goebel, R. G. (1998). Computational intelligence and knowledge. Computational Intelligence: A Logical Approach, Ci, 1–22.
no DOI — not checkedRai, A., Constantinides, P., & Sarker, S. (2019). Next generation digital platforms: Toward human-AI hybrids. MIS Quarterly, 43(1), iii–ix.
no DOI — not checkedRich, E., & Knight, K. (1991). Artificial intelligence. McGraw-Hill.
no DOI — not checkedThe Washington Post. (2018, April 10). Transcript of Mark Zuckerberg’s senate hearing. https://www.washingtonpost.com/news/the-switch/wp/2018/04/10/transcript-of-mark-zuckerbergs-senate-hearing/
no DOI — not checkedZheng, Z., Zheng, L., & Yang, Y. (2017). Pedestrian alignment network for large-scale person re-identification. ArXiv Preprint ArXiv:1707.00408.
no DOI — not checkedZhu, X. J. (2005). Semi-supervised learning literature survey. University of Wisconsin-Madison, Department of Computer Sciences. https://www.digital.library.wisc.edu/1793/60444
What this badge says. CiteStamped means the CHECKABLE references of this
work were clean at the dated check: each resolved to a known work in a public registry, and none
carried a retraction notice at that time. It says nothing about the quality, findings,
or importance of the work itself, and nothing about references deposited without a DOI.
checked 2026-08-10 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record
Embed this badge
Both snippets point at the live badge image and link back to this page. The badge re-renders from the daily check, so an embed never goes stale by more than a day of visits.
<a href="https://citestamp.com/citestamped/10.1007/s12525-022-00598-0"><img src="https://citestamp.com/citestamped/10.1007/s12525-022-00598-0/badge.svg" alt="CiteStamped reference-health badge" width="460" height="64"></a>
[](https://citestamp.com/citestamped/10.1007/s12525-022-00598-0)