From Ontology to Knowledge Graph Trend: Ontology as Foundation Layer for Knowledge Graph

AL-Aswadi, Fatima N.; Chan, Huah Yong; Gan, Keng Hoon

doi:10.1007/978-3-031-21422-6_25

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Dang et al (2019) adopted an acknowledged educational ontology to model online learning resource knowledge and constructed a MOOC-related knowledge graph to improve the utilization of online learning resources. Al-Aswadi et al (2022) explained how an ontology serves as a foundation layer for a knowledge graph. A knowledge graph is an extension of an ontology and can be considered a network knowledge base formed by entities with attributes linked by relations.…”

Section: Related Research Ontology and Knowledge Graph: Foundations A...mentioning

confidence: 99%

Constructing a Knowledge Graph for the Chinese Subject Based on Collective Intelligence

Ding,

Yi,

Feng

2023

International Journal on Semantic Web and Information Systems

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Knowledge graphs are a valuable tool for intelligent tutoring systems and are typically constructed with a focus on objectivity and accuracy. However, they may not effectively capture the subjectivity and complex relationships often present in the humanities. To address this issue, a dynamic visualization of subject matter knowledge graph was developed using a collective intelligence approach that integrates the individual intelligence of learners and considers cognitive diversity to construct and evolve the knowledge graph. The approach resulted in the construction of 722 knowledge associations and the evolution of 584 triples. A survey assessed the effectiveness and user-friendliness, revealing that this approach is effective, easy to use, and can improve subject matter knowledge ontology. In conclusion, combining individual and collective intelligence is a promising approach for building effective knowledge graphs in subject areas with subjectivity and complexity.

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Section: Related Research Ontology and Knowledge Graph: Foundations A...mentioning

confidence: 99%

Constructing a Knowledge Graph for the Chinese Subject Based on Collective Intelligence

Ding,

Yi,

Feng

2023

International Journal on Semantic Web and Information Systems

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Modification and completion of geological structure knowledge graph based on pattern matching

Lu,

Xu,

Zhang

2024

Sci Rep

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As a knowledge representation method, knowledge graph is widely used in intelligent question answering systems and recommendation systems. At present, the research on knowledge graph mainly focuses on information query and retrieval based on knowledge graph. In some domain knowledge graphs, specific subgraph structures (patterns) have specific physical meanings. Aiming at this problem, this paper proposes a method and framework of knowledge graph pattern mining based on gat. Firstly, the patterns with specific physical meaning were transformed into subgraph structures containing topological structures and entity attributes. Secondly, the subgraph structure of the pattern is regarded as the query graph, and the knowledge graph is regarded as the data graph, so that the problem is transformed into an approximate subgraph matching problem. Then, the improved relational graph attention network is used to fuse the adaptive edge deletion mechanism to realize the approximate subgraph matching of subgraph structure and attribute, so as to obtain the best matching subgraph. The proposed method is trained in an end-to-end manner. The approximate subgraph matching is realized on the existing data set, and the research work of key pattern mining of complex geological structure knowledge graph is carried out.

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From Ontology to Knowledge Graph Trend: Ontology as Foundation Layer for Knowledge Graph

Cited by 2 publications

References 30 publications

Constructing a Knowledge Graph for the Chinese Subject Based on Collective Intelligence

Constructing a Knowledge Graph for the Chinese Subject Based on Collective Intelligence

Modification and completion of geological structure knowledge graph based on pattern matching

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