Efficient skyline query processing in incomplete graph databases using machine learning techniques

Noor, Ubair and Hassan, Raini and Dwi Handayani, Dini Oktarina (2025) Efficient skyline query processing in incomplete graph databases using machine learning techniques. International Journal on Perceptive and Cognitive Computing, 11 (2). pp. 146-161. E-ISSN 2462-229X

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Abstract

Skyline queries play a critical role in multi-criteria decision-making systems by retrieving non-dominated data points from large datasets. In recent years, the rapid growth of graph-structured data across various domains has introduced challenges in efficiently processing skyline queries over incomplete and large-scale graph databases. Processing skyline queries in such massive, incomplete graphs is computationally intensive due to missing values and high-dimensional data. Traditional techniques often fail to scale or effectively handle data imperfections. There is a pressing need for a scalable, intelligent framework that can manage missing data, reduce computational overhead, and improve skyline query efficiency. This study adopts the Design Science Research Methodology (DSRM) to design and implement an optimisation framework that integrates machine learning techniques, including domination score ranking, dimension-based filtering, K-Means clustering and quicksort. These methods collectively reduce the search space and redundant comparisons. Experimental evaluation on real graph datasets demonstrates significant improvements in skyline computation time and accuracy, with clear reductions in pairwise comparisons and improved processing efficiency on large-scale graphs. By leveraging machine learning techniques for sorting, filtering and clustering, the approach reduces computational complexity and enhances scalability. These results show promising directions for applying intelligent query optimization in big data environments

Item Type:	Article (Journal)
Uncontrolled Keywords:	Skyline queries, Incomplete graph database, Machine learning, Graph database
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. Raini Hassan
Date Deposited:	05 Aug 2025 11:05
Last Modified:	05 Aug 2025 11:05
URI:	http://irep.iium.edu.my/id/eprint/122467

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