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The joint knowledge reasoning model based on knowledge representation learning for aviation assembly domain
Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent performance. For fine-grained...
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Biological knowledge capture and representation inspired by Zachman Framework principles
The biological knowledge capture and its representation in bioinspired design are challenging as knowledge is widely scattered, bulky and complicated...
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Enriched entity representation of knowledge graph for text generation
Text generation is a key tool in natural language applications. Generating texts which could express rich ideas through several sentences needs a...
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A knowledge graph–based structured representation of assembly process planning combined with deep learning
The assembly process is a significant foundation for reference in the procedure of product assembly. Aiming at the problem that assembly process...
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A new relational reflection graph convolutional network for the knowledge representation
The goal of the knowledge representation is to embed entities and relationships in the facts into consecutive low-dimensional dense vectors. Although...
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Interactive optimization of relation extraction via knowledge graph representation learning
Relation extraction is a vital task in constructing large-scale knowledge graphs, aiming to identify factual relations between entities from plain...
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Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Knowledge Graph (KG) has attracted more and more companies’ attention for its ability to connect different types of data in meaningful ways and...
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Integrating knowledge representation into traffic prediction: a spatial–temporal graph neural network with adaptive fusion features
Various external factors that interfere with traffic flow, such as weather conditions, traffic accidents, incidents, and Points of Interest (POIs),...
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Knowledge Graph Completion with Triple Structure and Text Representation
Knowledge Graphs (KGs) describe objective facts in the form of RDF triples, each triple contains sufficient semantic information and triple structure...
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Knowledge capture and its representation using concept map in bioinspired design
Biological knowledge can be represented using different models textually and diagrammatically. One of the least explored diagrammatic methods for...
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Decision Implication-Based Knowledge Representation and Reasoning Within Incomplete Fuzzy Formal Context
Formal Concept Analysis (FCA) is an order theory-based methodology employed for concept analysis and construction. Incomplete fuzzy formal context is...
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New Linguistic Z-Number Petri Nets for Knowledge Acquisition and Representation Under Large Group Environment
In this paper, we develop a new model named linguistic Z-number Petri nets for knowledge acquisition and representation in the large group...
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An associative knowledge network model for interpretable semantic representation of noun context
Uninterpretability has become the biggest obstacle to the wider application of deep neural network, especially in most human–machine interaction...
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Document-level relation extraction based on sememe knowledge-enhanced abstract meaning representation and reasoning
Document-level relation extraction is a challenging task in information extraction, as it involves identifying semantic relations between entities...
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Application of Binary Petri Nets to Knowledge Representation and Inference
In this paper, we present a binary Petri net model designed for knowledge representation and inference in rule-based systems. We assume that...
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A Data-Based Approach for Computer Domain Knowledge Representation
Representation learning is a method to compute the corresponding vectorized representations of entities or relationships. It is one of the most basic...
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Grey Reasoning Petri Nets for Knowledge Representation and Acquisition
FPNs have been widely used for knowledge representation and reasoning in various areas.
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Picture Fuzzy Petri Nets for Knowledge Representation and Acquisition
FPNs have been applied in many fields as a potential modeling tool for knowledge representation and reasoning.
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Spherical Linguistic Petri Nets for Knowledge Representation and Acquisition
FPNs are a promising modeling tool for knowledge representation and reasoning of rule-based expert systems.
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R-Numbers Petri Nets for Knowledge Representation and Acquisition
As a vital modeling technique, FPNs have been widely used in various areas for knowledge representation and reasoning.