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Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
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Hanme Jang, Kiyun Yu and Jiyoung Kim
With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While we ...
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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge...
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Zilin Zhao, Zhi Cai, Mengmeng Chang and Zhiming Ding
Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large...
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Fangling Leng, Fan Li, Yubin Bao, Tiancheng Zhang and Ge Yu
As graph models become increasingly prevalent in the processing of scientific data, the exploration of effective methods for the mining of meaningful patterns from large-scale graphs has garnered significant research attention. This paper delves into the...
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Jinhui Guo, Xiaoli Zhang, Kun Liang and Guoqiang Zhang
In recent years, the emergence of large-scale language models, such as ChatGPT, has presented significant challenges to research on knowledge graphs and knowledge-based reasoning. As a result, the direction of research on knowledge reasoning has shifted....
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Rogério Luiz Cardoso Silva Filho, Kellyton Brito and Paulo Jorge Leitão Adeodato
This study presents an approach to investigating the main interventions related to gains on performance using a combination of educational data mining (EDM) techniques and traditional theory-driven models. The goal is to overcome the limitation of previo...
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Xu Chen, Shaohua Wang, Huilai Li, Fangzheng Lyu, Haojian Liang, Xueyan Zhang and Yang Zhong
The ability to quickly calculate or query the shortest path distance between nodes on a road network is essential for many real-world applications. However, the traditional graph traversal shortest path algorithm methods, such as Dijkstra and Floyd?Warsh...
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Vetle Ryen, Ahmet Soylu and Dumitru Roman
Knowledge graphs have, for the past decade, been a hot topic both in public and private domains, typically used for large-scale integration and analysis of data using graph-based data models. One of the central concepts in this area is the Semantic Web, ...
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