Search · four archives
Search · four archives
16 papers · ranked by Valyu relevance
Kairui Chen, Fuqun Huang, Zejing Liu, Haomiao Yu + 4 more
'Shasha Mo' 'Li Zhang' 'You Song'] A well-designed educational programming dataset is a valuable asset for students and educators. Such a dataset enables students to improve their programming performances continuously, provides researchers with significant data sources to identify students’ learning behaviours and…
Ciyuan Peng, Feng Xia, Mehdi Naseriparsa, Francesco Osborne
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledge of the real world. It has been well-recognized that knowledge graphs…
Amy K Glen, Eric W Deutsch, Stephen A Ramsey, Christina Kendziorski
Knowledge graphs (KGs) have emerged as useful abstractions for integrating heterogeneous biomedical data, making them convenient substrates for data mining and other computational reasoning techniques. The way in which such knowledge graphs are exposed for use varies; some graphs are only available for flat-file…
Parisa Kordjamshidi, Dan Roth, Kristian Kersting
Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these solutions. Often, a solution involves multiple learning models, along with significant levels of reasoning with the models'…
Zhisheng Huang, Qing Hu, Mingqun Liao, Cong Miao + 2 more
Kawasaki Disease is a vasculitis syndrome that is extremely harmful to children. Kawasaki Disease can cause severe symptoms of ischemic heart disease or develop into ischemic heart disease, leading to death in children. Researchers and clinicians need to analyze various knowledge and data resources to explore aspects…
Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger + 3 more
'Luigi Bellomarini' 'Emanuel Sallinger' 'Sahar Vahdati'] Knowledge Graphs (KGs) are one of the key trends among the next wave of technologies. Many definitions exist of what a Knowledge Graph is, and in this chapter, we are going to take the position that precisely in the multitude of definitions lies one of the…
Amy K. Glen, Eric W. Deutsch, Stephen A. Ramsey
1## Introduction Knowledge graphs (KGs) have emerged as useful abstractions for integrating heterogeneous biomedical data, making them convenient substrates for data mining and other computational reasoning techniques. The way in which such knowledge graphs are exposed for use varies; some graphs are only available for…
Qizheng Wang, Fan Yang, Lijie Quan, Mengjie Fu + 2 more
'Ju Wang'] Neurological disorders (e.g., Alzheimer’s disease and Parkinson’s disease) and mental disorders (e.g., depression and anxiety), pose huge challenges to global public health. The pathogenesis of these diseases can usually be attributed to many factors, such as genetic, environmental and socioeconomic status…
Lars Vogt, Kheir Eddine Farfar, Pallavi Karanth, Marcel Konrad + 3 more
Knowledge graphs and ontologies are promising technologies for achieving FAIR (findable, accessible, interoperable, and reusable) data. We identify four challenges as high barriers for the effective use of knowledge graphs. Since the construction of knowledge graphs is a modelling task and every model serves a purpose…
Shilpa Verma, Rajesh Bhatia, Sandeep Harit, Sanjay Batish
The necessity for scholarly knowledge mining and management has grown significantly as academic literature and its linkages to authors produce enormously. Information extraction, ontology matching, and accessing academic components with relations have become more critical than ever. Therefore, with the advancement of…
Guangrong Qin, Kamileh Narsinh, Qi Wei, Jared C. Roach + 15 more
'Arpita Joshi' 'Skye L. Goetz' 'Sierra T. Moxon' 'Matthew H. Brush' 'Colleen Xu' 'Yao Yao' 'Amy K. Glen' 'Evan D. Morris' 'Alexandra Ralevski' 'Ryan Roper' 'Basazin Belhu' 'Yue Zhang' 'Ilya Shmulevich' 'Jennifer Hadlock' 'Gwênlyn Glusman'] As large clinical and multiomics datasets and knowledge resources accumulate…
Dirk Weissenborn, Michael Schroeder, George Tsatsaronis
Background The complexity and scale of the knowledge in the biomedical domain has motivated research work towards mining heterogeneous data from both structured and unstructured knowledge bases. Towards this direction, it is necessary to combine facts in order to formulate hypotheses or draw conclusions about the…
Savaş Takan, Claudio Ardagna
A knowledge graph is convenient for storing knowledge in artificial intelligence applications. On the other hand, it has some shortcomings that need to be improved. These shortcomings can be summarised as the inability to automatically update all the knowledge affecting a piece of knowledge when it changes, ambiguity…
Chenwei Yan, Xinyue Fang, Xiaotong Huang, Chenyi Guo + 1 more
The knowledge graph is one of the essential infrastructures of artificial intelligence. It is a challenge for knowledge engineering to construct a high-quality domain knowledge graph for multi-source heterogeneous data. We propose a complete process framework for constructing a knowledge graph that combines structured…
Yichun Feng, Lu Zhou, Chao Ma, Yikai Zheng + 2 more
In this work, we tackle the problem of logical reasoning over the KG \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\mathcal {K}: {\it E}…
Houcemeddine Turki, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha, Grischa Fraumann + 2 more
Fully structured semantic resources representing facts in the form of triples (i.e., knowledge graphs) have a major function in driving computer applications, particularly the ones related to biomedicine, to library and information science and to digital humanities (; ). They can be easily processed using Application…