Interoperable Identity Graphs Are Future of Consumer Data: Infutor’s Kevin Dean – Beet.TV
Marketers and media owners are looking for ways to get the most out of consumer data amid changes to privacy laws and growing restraints on online audience tracking. They can un...
Development of an Ontology-based Approach for Knowledge Management in Software Testing
Software development organizations are seeking to add quality to their products. Testing processes are strategic elements to manage projects and product quality. However, advances in technology and the emergence of increasingly critical applications make testing a complex task and large volumes of information are generated. In fact, software testing is a knowledge intensive process. Because of this, these organizations have shown a growing interest in Knowledge Management (KM) programs, which in turn support the improvement of testing procedures. KM emerges as a means to manage testing knowledge, and, consequently, to improve software quality. However, there are only a few KM solutions supporting software testing. This paper reports experiences from the development of an approach, called Ontology-based Testing Knowledge Management (OntoT-KM), that aims to assist in launching KM initiatives in the software testing domain with the support of Knowledge Management Systems (KMSs). OntoT-KM provides a process guiding how to start applying KM in software testing. OntoT-KM is based on the findings of a systematic mapping on KM in software testing and the results of a survey with testing practitioners. Moreover, OntoT-KM considers the conceptualization established by a Reference Ontology on Software Testing (ROoST). As a proof of concept, OntoT-KM was applied to develop a KMS called Testing KM Portal (TKMP), which was evaluated in terms of usefulness, usability, and functional correctness. Results show that the developed KMS from OntoT-KM is a potential system for managing knowledge in software testing, so, the approach can guide KM initiatives in software testing.
"Our knowledge graph form of NOAA climate data facilitates the supply of semantic climate information to researchers and offers a variety of semantic applications that can be built on top of it." https://t.co/2C2ZAUGSJy pic.twitter.com/Z459afns5S— Aaron Bradley (@aaranged) October 20, 2021
"Language Models As or For Knowledge Bases" a position paper about strengths, limitations and complementarity of language model and knowledge bases.(Razniewski et al, 2021)https://t.co/TZisPy3hHH@maxplanckpress @andrewyates pic.twitter.com/252pQFxwau— WikiResearch (@WikiResearch) October 21, 2021
Some delayed thoughts on @bobdc's recent post "you probably don't need OWL". Interesting how our different backgrounds lead us to different perspectives, in the life sciences OWL seems more popular for ontologies 1/n https://t.co/LMC8pX176p— Chris Mungall (@chrismungall) October 20, 2021
A knowledge graph (KG) is a data structure which represents entities and relations as the vertices and edges of a directed graph with edge types. KGs are an important primitive in modern machine...
An increasing number of cities are creating 3D city models to support visualization and simulations in the urban planning process. The 3D city models...
Amazon Science on LinkedIn: Learning hierarchical graph neural networks for image clustering
In this publication, Amazon scientists propose a hierarchical graph neural network (GNN) model that learns how to cluster a set of images into an unknown...
The "meta way": On upper ontologies and data meshes
For some reason I keep hearing the word "upper ontology" more frequently in recent times. I find this problematic, because in many of the contexts I hear about it, it is introduced as a kind of secret sauce that 20 years of Semantic Web research have been hiding from the greater public.
ANNOUNCEMENT: Aaron Bradley - knowledge graph strategist at Electronic Arts (EA) – joins the Trace Labs advisory board to advise the team on strategies...
AtomGraph on LinkedIn: RDF Graph Database Powered by Apache Jena Fuseki - Free Edition
We have released the first free RDF triplestore on AWS Marketplace based on Apache Jena Fuseki. Give it a try – the installation takes 5 button clicks....
Why is your organization struggling to #collaborate ? Leaders can diagnose team dysfunction by looking for six common patterns. Read 👇🏽 https://lnkd.in...
Paco Nathan on LinkedIn: Exploring Complexity - Graph Data Science Panel - OpenCredo
We are excited to announce that we are running an online panel this November where will explore the foundations of why graphs are the right tool for complexity...
Why graph DB + AI may be the future of data management
Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.
3D Infomax improves GNNs for Molecular Property Prediction
Our new paper is out! ⚛️🎉 "3D Infomax improves GNNs for Molecular Property Prediction": https://lnkd.in/dKsTjSfj Code to pre-train your own GNN is available...
Ein Knowledge Graph als moderne Form der Datenarchitektur. Gäste werden künftig zunehmend auch sprachbasiert nach Informationen suchen. Die Sprachanfragen werden also mittels Diktierfunktion auf dem Smartphone eingesprochen oder in Form von Fragen an digitale Assistenten wie den Google Assistant oder Alexa von Amazon gerichtet. Bei der
Excited to share that our Open Graph Benchmark Large-Scale Challenge (OGB-LSC) paper has been accepted to NeurIPS! We have updated our datasets and released...
Richard Ahlfeld on LinkedIn: #neuralnetworks #simulation #artificialintelligence | 147 comments
Spectacular real-time simulation of complex physics through Neural Networks by a team from Google DeepMind! They do not use physics-informed neural ... 147 comments on LinkedIn
