Enhancing skyline query processing on large and incomplete graphs with graph neural networks: a hybrid machine learning approach

Adzman, Hasan Khair and Hassan, Raini and Handayani, Dini Oktarina Dwi (2025) Enhancing skyline query processing on large and incomplete graphs with graph neural networks: a hybrid machine learning approach. International Journal on Perceptive and Cognitive Computing (IJPCC), 11 (2). pp. 162-172. E-ISSN 2462-229X

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Abstract

Skyline query processing is essential in multi-criteria decision making, as it retrieves optimal results without requiring user-defined weights. Traditional skyline methods, however, face significant challenges when applied to large-scale and incomplete datasets. This study proposes a hybrid approach that integrates the ISkyline dominance graph technique with Graph Neural Networks (GNNs) to improve skyline query performance under such conditions. The GNN component is utilized to predict skyline tuples in the presence of missing or incomplete data. Evaluation on both synthetic and real-world datasets demonstrates enhanced accuracy and efficiency when compared to established methods such as ISkyline, SIDS, and OIS. This work demonstrates the potential of creating a more efficient query processing, supporting applications in e-commerce, finance, and smart data systems, while aligning with the 9th Sustainable Development Goal on industry, innovation, and infrastructure.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Skyline query processing, Graph Neural Networks (GNNs), incomplete data, Pareto optimality, ISkyline, multi-criteria decision making, data imputation, machine learning, query optimization, scalability
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 Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Dr. Raini Hassan
Date Deposited:	05 Aug 2025 11:55
Last Modified:	05 Aug 2025 11:55
URI:	http://irep.iium.edu.my/id/eprint/122468

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