metaphactory: A platform for knowledge graph management

Semantic Web ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 1109-1125 ◽  
Author(s):  
Peter Haase ◽  
Daniel M. Herzig ◽  
Artem Kozlov ◽  
Andriy Nikolov ◽  
Johannes Trame
Author(s):  
Omar Al-Safi ◽  
Christian Mader ◽  
Ioanna Lytra ◽  
Mikhail Galkin ◽  
Kemele Endris ◽  
...  

Author(s):  
Luigi Bellomarini ◽  
Georg Gottlob ◽  
Andreas Pieris ◽  
Emanuel Sallinger

Many modern companies wish to maintain knowledge in the form of a corporate knowledge graph and to use and manage this knowledge via a knowledge graph management system (KGMS). We formulate various requirements for a fully fledged KGMS. In particular, such a system must be capable of performing complex reasoning tasks but, at the same time, achieve efficient and scalable reasoning over Big Data with an acceptable computational complexity. Moreover, a KGMS needs interfaces to corporate databases, the web, and machine-learning and analytics packages. We present KRR formalisms and a system achieving these goals.


2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Suzanna Schmeelk ◽  
Lixin Tao

Many organizations, to save costs, are movinheg to t Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate.  Our research examines software assurance methodologies specifically focusing on security analysis coverage of the program analysis for mobile malware detection, mitigation, and prevention.  This research focuses on secure software development of Android applications by developing knowledge graphs for threats reported by the Open Web Application Security Project (OWASP).  OWASP maintains lists of the top ten security threats to web and mobile applications.  We develop knowledge graphs based on the two most recent top ten threat years and show how the knowledge graph relationships can be discovered in mobile application source code.  We analyze 200+ healthcare applications from GitHub to gain an understanding of their software assurance of their developed software for one of the OWASP top ten moble threats, the threat of “Insecure Data Storage.”  We find that many of the applications are storing personally identifying information (PII) in potentially vulnerable places leaving users exposed to higher risks for the loss of their sensitive data.


2019 ◽  
Author(s):  
Jemmy Wiratama
Keyword(s):  

I'm an Science & Technology enthusiast. I still learn how to build a knowledge graph and how to write a paper.


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