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pro vyhledávání: '"Kochut, A."'
Autor:
Bozorgi, Elika, Alqaiidi, Sakher Khalil, Shams, Afsaneh, Arabnia, Hamid Reza, Kochut, Krzysztof
Machine learning, deep learning, and NLP methods on knowledge graphs are present in different fields and have important roles in various domains from self-driving cars to friend recommendations on social media platforms. However, to apply these metho
Externí odkaz:
http://arxiv.org/abs/2406.07402
Knowledge Graphs have been widely used to represent facts in a structured format. Due to their large scale applications, knowledge graphs suffer from being incomplete. The relation prediction task obtains knowledge graph completion by assigning one o
Externí odkaz:
http://arxiv.org/abs/2405.02738
Autor:
Bozorgi, Elika, Soleimani, Saber, Alqaiidi, Sakher Khalil, Arabnia, Hamid Reza, Kochut, Krzysztof
Graph is an important data representation which occurs naturally in the real world applications \cite{goyal2018graph}. Therefore, analyzing graphs provides users with better insights in different areas such as anomaly detection \cite{ma2021comprehens
Externí odkaz:
http://arxiv.org/abs/2405.02240
Knowledge Graphs (KGs) are widely employed in artificial intelligence applications, such as question-answering and recommendation systems. However, KGs are frequently found to be incomplete. While much of the existing literature focuses on predicting
Externí odkaz:
http://arxiv.org/abs/2404.16206
Named Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format. We present a survey of recent deep learning models that address nam
Externí odkaz:
http://arxiv.org/abs/2310.19055
The relation classification task assigns the proper semantic relation to a pair of subject and object entities; the task plays a crucial role in various text mining applications, such as knowledge graph construction and entities interaction discovery
Externí odkaz:
http://arxiv.org/abs/2309.13718
Large-scale datasets in the form of knowledge graphs are often used in numerous domains, today. A knowledge graphs size often exceeds the capacity of a single computer system, especially if the graph must be stored in main memory. To overcome this, k
Externí odkaz:
http://arxiv.org/abs/2203.14888
Large-scale knowledge graphs are increasingly common in many domains. Their large sizes often exceed the limits of systems storing the graphs in a centralized data store, especially if placed in main memory. To overcome this, large knowledge graphs n
Externí odkaz:
http://arxiv.org/abs/2203.14884
Autor:
Taujale, Rahil, Gravel, Nathan, Zhou, Zhongliang, Yeung, Wayland, Kochut, Krystof, Kannan, Natarajan
Publikováno v:
In Drug Discovery Today March 2024 29(3)
Autor:
Saber Soleymani, Nathan Gravel, Liang-Chin Huang, Wayland Yeung, Elika Bozorgi, Nathaniel G. Bendzunas, Krzysztof J. Kochut, Natarajan Kannan
Publikováno v:
PeerJ, Vol 11, p e16087 (2023)
The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships among protein kinase sequence, structure, function, and disease in a human and machine-readable format. In this study, we have signif
Externí odkaz:
https://doaj.org/article/78b90c5c43b64d39a100206dd4b76e41