Graph-based reasoning
WebThe target of the multi-hop knowledge base question-answering task is to find answers of some factoid questions by reasoning across multiple knowledge triples in the knowledge base. Most of the existing methods for multi-hop knowledge base question answering based on a general knowledge graph ignore the semantic relationship between each hop. …
Graph-based reasoning
Did you know?
WebJun 20, 2024 · Graph-Based Global Reasoning Networks. Abstract: Globally modeling and reasoning over relations between regions can be beneficial for many computer vision tasks on both images and videos. Convolutional Neural Networks (CNNs) excel at modeling local relations by convolution operations, but they are typically inefficient at capturing … WebApr 21, 2024 · Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning. Knowledge Graph (KG) reasoning that predicts missing facts …
WebJan 1, 2024 · 2024. TLDR. This survey provides a comprehensive overview of RL and graph mining methods and generalize these methods to Graph Reinforcement Learning (GRL) as a unified formulation and creates an online open-source for both interested scholars who want to enter this rapidly developing domain and experts who would like to … WebSRGCN: Graph-based multi-hop reasoning on knowledge graphs: NC: Transductive: Link-2024: TRAR: Target relational attention-oriented knowledge graph reasoning: NC: …
WebNov 1, 2024 · The graph-based reasoning layers regard the feature map from the last convolution layer as a graph and construct the structural relations. Then the graph-based attention layer enhances the key information guided by the relations. Besides, a front-end curriculum design is introduced to split the training dataset from simple to complex and … WebMar 7, 2024 · Knowledge acquisition and reasoning are essential in intelligent welding decisions. However, the challenges of unstructured knowledge acquisition and weak knowledge linkage across phases limit the development of welding intelligence, especially in the integration of domain information engineering. This paper proposes a cognitive …
WebNov 16, 2024 · Abstract. Human beings are fundamentally sociable—that we generally organize our social lives in terms of relations with other people. Understanding …
WebKnowledge graph (KG) technology is a newly emerged knowledge representation method in the field of artificial intelligence. Knowledge graphs can form logical mappings from cluttered data and establish triadic relationships between entities. Accurate derivation and reasoning of knowledge graphs play an important role in guiding power equipment operation and … how do you pronounce yaeWebGraphDB performs reasoning based on forward chaining of entailment rules defined using RDF triple patterns with variables. GraphDB’s reasoning strategy is one of Total … how do you pronounce xuxaWebJul 15, 2024 · Graph-Based Social Relation Reasoning. Wanhua Li, Yueqi Duan, Jiwen Lu, Jianjiang Feng, Jie Zhou. Human beings are fundamentally sociable -- that we generally organize our social lives in terms of relations with other people. Understanding social relations from an image has great potential for intelligent systems such as social … how do you pronounce y in germanWebOct 10, 2024 · 2.3. Graph-Based Reasoning. Graph-based reasoning provides an efficient idea of global context reasoning. Random walk and conditional random field (CRF) networks have been proposed based on graph for efficient image segmentation and classification. Recently, graph convolutional networks (GCNs) have been proposed for … how do you pronounce yahelWebFeb 27, 2024 · There is a technology called GraphScale that empowers Neo4j with scalable OWL reasoning. The approach is based on an abstraction refinement technique that … phone number for dwp pipWebNov 1, 2024 · The graph-based reasoning layers regard the feature map from the last convolution layer as a graph and construct the structural relations. Then the graph … how do you pronounce yachatsWeb2 days ago · In this work, to answer such questions involving temporal and causal relations, we generate event graphs from text based on dependencies, and rank answers by aligning event graphs. In particular, … how do you pronounce yahushua