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Meta-path reasoning of knowledge graph for commonsense question answering
Commonsense question answering (CQA) requires understanding and reasoning over QA context and related commonsense knowledge, such as a structured...
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Reason more like human: Incorporating meta information into hierarchical reinforcement learning for knowledge graph reasoning
Nowadays, reasoning over knowledge graphs (KGs) has been widely adapted to empower retrieval systems, recommender systems, and question answering...
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Meta-Path Based Social Relation Reasoning in a Deep and Robust Way
Social relation reasoning in heterogeneous social networks (HSNs) should not only infer whether people are connected, but also why they know each...
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Meta-reasoning in Assembly Robots
As robots become increasingly pervasive in human society, there is a need for develo** theoretical frameworks for “human–machine shared contexts.”...
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Using Hybrid Knowledge Bases for Meta-reasoning over OWL 2 QL
Metamodeling refers to scenarios in ontologies in which class-es and roles can be members of classes or occur in roles. This is a desirable modelling...
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An Evaluation of Meta-reasoning over OWL 2 QL
There has been increasing interest in enriching ontologies with meta-modeling and meta-querying for the past few years. Unfortunately, the Direct...
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Algorithm selection using edge ML and case-based reasoning
In practical data mining, a wide range of classification algorithms is employed for prediction tasks. However, selecting the best algorithm poses a...
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Report on “Axiomatizing Conditional Normative Reasoning”
This is a report on the project “Axiomatizing Conditional Normative Reasoning” (ANCoR, M 3240-N) funded by the Austrian Science Fund (FWF). The...
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Formal Meta Engineering Event-B: Extension and Reasoning The \( EB4EB \) Framework
State-based Formal methods have been used to design and verify the development of complex software systems for a long time. Such methods are...
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Abductive subconcept learning
Bridging neural network learning and symbolic reasoning is crucial for strong AI. Few pioneering studies have made some progress on logical reasoning...
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Classifying Design Science Research in Terms of Types of Reasoning from an Epistemological Perspective
Design science research (DSR) is now an established branch of the artificial sciences. However, the nature of the logical reasoning and the...
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Document-Level Relation Extraction with Relational Reasoning and Heterogeneous Graph Neural Networks
Document-level relation extraction aims to identify the relations between the entities in an unstructured text and represents them in a structured...
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Thinking Fast and Slow in AI: The Role of Metacognition
Artificial intelligence (AI) still lacks human capabilities, like adaptability, generalizability, self-control, consistency, common sense, and causal...
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Category Theory in Isabelle/HOL as a Basis for Meta-logical Investigation
This paper presents meta-logical investigations based on category theory using the proof assistant Isabelle/HOL. We demonstrate the potential of a...
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Efficient Abductive Learning of Microbial Interactions Using Meta Inverse Entailment
Abductive reasoning plays an essential part in day-to-day problem-solving. It has been considered a powerful mechanism for hypothetical reasoning in...
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A Recommendation Algorithm Based on Automatic Meta-path Generation and Relationship Aggregation
Knowledge Graph (KG) contains rich semantic information and supports knowledge reasoning. In recent years, introducing KG as auxiliary information...
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Computational knowledge vision: paradigmatic knowledge based prescriptive learning and reasoning for perception and vision
This paper outlines a novel advanced framework that combines structurized knowledge and visual models—Computational Knowledge Vision. In advanced...
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Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework
In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement learning framework. The Detect component is composed of a...
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Cross-Relational Reasoning for Neural Tensor Networks
Neural tensor networks are knowledge graph embedding models which infer relationships between two given entities. Although demonstrated to be...
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Path-Aware Cross-Attention Network for Question Answering
Reasoning is an essential ability in QA systems, and the integration of this ability into QA systems has been the subject of considerable research. A...