Handbook of Knowledge Engineering / by Broadway, Kaylah, author 639655, Shay, Marisa, author 643759

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Artificial intelligence for long-term robot autonomy: A survey by Kunze, L, Hawes, N, Duckett, T, Hanheide, M, Krajnik, T

“…Some of these have been investigated by sub-disciplines of Artificial Intelligence (AI) including navigation & mapping, perception, knowledge representation & reasoning, planning, interaction, and learning. …”

Temporal datalog with existential quantification by Lanzinger, M, Nissl, M, Sallinger, E, Walega, PA

“…Existential rules, also known as tuple-generating dependencies (TGDs) or Datalog± rules, are heavily studied in the communities of Knowledge Representation and Reasoning, Semantic Web, and Databases, due to their rich modelling capabilities. …”

Reconciling description logics and rules. by Motik, B, Rosati, R

“…Developing a formalism that integrates DLs and rules would be a natural outcome of a large body of research in knowledge representation and reasoning of the last two decades; however, achieving this goal is very challenging and the approaches proposed thus far have not fully reached it. …”

Bridging max graph neural networks and datalog with negation by Tena Cucala, D, Cuenca Grau, B

Knowledge Graph Inference Method Combined with Decision Implication by ZHAI Yanhui, HE Xu, LI Deyu, ZHANG Chao

“…Decision implication is a tool of decision knowledge representation and reasoning in formal concept analysis. …”
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Conclusions from the Commodity Expert Project by Stansfield, James L.

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Relational graph convolutional networks do not learn sound rules by Morris, M, Tena Cucala, DJ, Cuenca Grau, B, Horrocks, I

Ontological, fully probabilistic knowledge model for human activity recognition by Foudeh, Pouya, Salim, Naomie

“…The knowledge model is in the form of ontology, the state-of-the-art in knowledge representation and reasoning. The ontology starts with probabilistic information about subjects’ low-level activities and location and then is populated with the assertion axioms learned from data or defined by the user. …”
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Ontologia regionale pedagogica: una riflessione by Roberto Melchiori

“…Tali applicazioni costituiscono le tecnologie abilitanti le strategie e i prodotti di knowledge representation and reasoning che implementano un’ontologia pedagogica. …”
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On the expressivity of recurrent neural cascades with identity by Knorozova, NA, Ronca, A

Ontology reasoning with deep neural networks by Hohenecker, P, Lukasiewicz, T

“…Traditionally, logic-based symbolic methods from the field of knowledge representation and reasoning have been used to equip agents with capabilities that resemble human logical reasoning qualities. …”

A Systematic Review on the Application of Ontologies to Improve Career Guidance by Dickson Kalungi, Annabella Habinka Ejiri, Fred Kaggwa, Simon Kawuma

“…The review highlights the unique advantages of using ontologies for career guidance (CG), such as formal representation, interoperability, and knowledge representation and reasoning. The review also points out the loopholes in the few studies that attempted to use ontologies in CG. …”
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Learning and reasoning with graph data by Manfred Jaeger

“…Graphs are also the underlying structures of interest in a wide range of more traditional fields ranging from logic-oriented knowledge representation and reasoning to graph kernels and statistical relational learning. …”
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Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework by Niklas Umland, Kora Winkler, David Inkermann

“…The review of the existing approaches is based on twelve criteria that characterize the design automation task in general, such as knowledge representation or reasoning methods used, as well as criteria specific to electric motor design, such as domains considered and their coupling. …”
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A review of knowledge graph embedding methods of TransE, TransH and TransR for missing links by Salwana, Mohamad, Noor Azida, Sahabudin, Nor Syahidatul Nadiah, Ismail, Ily Amalina, Ahmad Sabri

“…Knowledge representation and reasoning require knowledge graph embedding as it is crucial in the area. …”
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Research of Inference Rules on Decision Implication and Variable Decision Implication by XUE Dongqian, ZHAI Yanhui, ZHANG Shaoxia, LI Deyu, XU Weihua

“…Besides, this paper further discusses the differences between the two decision types in knowledge representation and reasoning from the semantic perspective, and summarizes the characteristics of restricted variable decision implication relative to decision implication from the semantic and syntactic perspectives. …”
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An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework by Haiyuan Wang, Zhisheng Huang, Ning Zhong, Jiajin Huang, Yuzhong Han, Feng Zhang

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Using Ontologies for the Formalization and Recognition of Criticality for Automated Driving by Lukas Westhofen, Christian Neurohr, Martin Butz, Maike Scholtes, Michael Schuldes

“…Knowledge representation and reasoning has a long history of examining how knowledge can be formalized, interpreted, and semantically analyzed by machines. …”
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An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring by Marjan Alirezaie, Andrey Kiselev, Martin Längkvist, Franziska Klügl, Amy Loutfi

“…This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. …”
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