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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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Otmane Azeroual, Renaud Fabre, Uta Störl and Ruidong Qi
The use of Elastic Stack (ELK) solutions and Knowledge Graphs (KGs) has attracted a lot of attention lately, with promises of vastly improving business performance based on new business insights and better decisions. This allows organizations not only to...
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Chao Liu, Buhong Wang, Zhen Wang, Jiwei Tian, Peng Luo and Yong Yang
With the development of the air traffic management system (ATM), the cyber threat for ATM is becoming more and more serious. The recognition of ATM cyber threat entities is an important task, which can help ATM security experts quickly and accurately rec...
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Hasan Abu-Rasheed, Christian Weber, Johannes Zenkert, Mareike Dornhöfer and Madjid Fathi
In modern industrial systems, collected textual data accumulates over time, offering an important source of information for enhancing present and future industrial practices. Although many AI-based solutions have been developed in the literature for a do...
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Hongmei Tang, Wenzhong Tang, Ruichen Li, Yanyang Wang, Shuai Wang and Lihong Wang
Knowledge graph (KG) reasoning improves the perception ability of graph structure features, improving model accuracy and enhancing model learning and reasoning capabilities. This paper proposes a new GraphDIVA model based on the variational reasoning div...
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Wu Hao, Jiao Menglin, Tian Guohui, Ma Qing and Liu Guoliang
Aiming to solve the problem of environmental information being difficult to characterize when an intelligent service is used, knowledge graphs are used to express environmental information when performing intelligent services. Here, we specially design a...
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Yu Wang, Yining Sun, Zuchang Ma, Lisheng Gao and Yang Xu
Named Entity Recognition (NER) is the fundamental task for Natural Language Processing (NLP) and the initial step in building a Knowledge Graph (KG). Recently, BERT (Bidirectional Encoder Representations from Transformers), which is a pre-training model,...
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Jindou Zhang and Jing Li
Combining first order logic rules with a Knowledge Graph (KG) embedding model has recently gained increasing attention, as rules introduce rich background information. Among such studies, models equipped with soft rules, which are extracted with certain ...
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