Data & Knowledge Engineering

Papers
(The H4-Index of Data & Knowledge Engineering is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-11-01 to 2025-11-01.)
ArticleCitations
Editorial84
A graph theoretic approach to assess quality of data for classification task65
On efficient top-k transaction path query processing in blockchain database47
Convolutional neural network-based high-precision and speed detection system on CIDDS-00141
ROSI: A hybrid solution for omni-channel feature integration in E-commerce40
Providing healthcare shopping advice through knowledge-based virtual agents39
Static and dynamic techniques for iterative test-driven modelling of Dynamic Condition Response Graphs38
How to build data-driven Strategy Maps? A methodological framework proposition36
From base data to knowledge discovery – A life cycle approach – Using multilayer networks35
The power and potentials of Flexible Query Answering Systems: A critical and comprehensive analysis34
Editorial Board32
PROADAPT: Proactive framework for adaptive partitioning for big data warehouses31
Generating multiple conceptual models from behavior-driven development scenarios31
Blockchain-based ontology driven reference framework for security risk management31
Unraveling the foundations and the evolution of conceptual modeling—Intellectual structure, current themes, and trajectories29
Reasoning on responsibilities for optimal process alignment computation26
A design theory for data quality tools in data ecosystems: Findings from three industry cases26
Editorial Board23
Evaluating quality of ontology-driven conceptual models abstractions23
Enhancing the convolution-based knowledge graph embeddings by increasing dimension-wise interactions22
Editorial Board22
SimBio: Adopting Particle Swarm Optimization for ontology-based biomedical term similarity assessment21
A transformer-based neural network framework for full names prediction with abbreviations and contexts21
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