Results 41 to 50 of about 221,324 (264)
ACM SIGMOD Record, 2023 Knowledge graphs (KGs) such as DBpedia, Freebase, YAGO, Wikidata, and NELL were constructed to store large-scale, real-world facts as (subject, predicate, object) triples - that can also be modeled as a graph, where a node (a subject or an object) represents an entity with attributes, and a directed edge (a predicate) is a relationship between two ...
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Collective knowledge graph: meta knowledge transfer and federated graph reasoning
智能科学与技术学报, 2022 Collective knowledge graphs refer to knowledge graphs that are managed and maintained in a decentralized or distributed manner through group collaboration.Compared with the existing centrally managed knowledge graph, the collective knowledge graph has ...
Mingyang CHEN +4 more
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Knowledge Graph Embeddings [PDF]
, 2012 With the growing popularity of multi-relational data on the Web, knowledge graphs (KGs) have become a key data source in various application domains, such as Web search, question answering, and natural language understanding. In a typical KG such as Freebase (Bollacker et al.
Rosso, Paolo +2 more
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Enhancing Biomedical Knowledge Representation Through Knowledge Graphs
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceThere is a plethora of information related to the biomedical domain on the internet. Unfortunately, retrieving this information online is challenging because of insufficient semantic metadata embedded within the web documents that help search engines ...
Sebastian Chalarca +4 more
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Knowledge Graph Identification [PDF]
, 2013 Large-scale information processing systems are able to extract massive collections of interrelated facts, but unfortunately transforming these candidate facts into useful knowledge is a formidable challenge. In this paper, we show how uncertain extractions about entities and their relations can be transformed into a knowledge graph.
Jay Pujara +3 more
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Knowledge Graphs and Explainable AI in Healthcare
Information, 2022 Building trust and transparency in healthcare can be achieved using eXplainable Artificial Intelligence (XAI), as it facilitates the decision-making process for healthcare professionals.
Enayat Rajabi, Somayeh Kafaie
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K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain
IEEE Access, 2022 The use of superior algorithms and complex architectures in language models have successfully imparted human-like abilities to machines for specific tasks.
Vivek Kumar +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Pediatric cancer remains a leading cause of morbidity and mortality worldwide, particularly in low‐and middle‐income countries. Cancer treatment may impair nutritional status, alter body composition, and exacerbate cancer‐related fatigue (CRF).
Luís Carlos Lopes‐Junior +11 more
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A Knowledge Graph Recommendation Approach Incorporating Contrastive and Relationship Learning
IEEE Access, 2023 Knowledge graphs, encompassing abundant structured and semantic information, exhibit remarkable potential within personalized recommendation fields.
Xintao Shen, Yulai Zhang
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FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
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