The core product is a knowledge ... knowledge graph points to universities. Research in many areas, including physics, medicine, and more, can be enhanced by the power of machine learning to ...

Another contribution of Lin's work is on what is called symbolic compositionality of knowledge graph relations in embedding approaches. Embedding is a technique widely used in machine learning ...

With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand. As well as being a useful format for feeding training data to ...

Using Knowledge Graphs for Ultimate Business Knowledge Data and key business information can continuously be extracted with the help of specialized AI techniques and machine learning models ...

Scientist Yi Nian is sharing his machine-learning ... constructed knowledge graphs with NLP tools from Alzheimer’s Disease literature. He conducted research in state-of-the-art graph neural ...

We take the opportunity to discuss the database market, graph, and beyond, with CEO and co-founder Claudius Weinberger and Head of Engineering and Machine Learning Jörg Schad. ArangoDB was ...

Co-founded by CEO Sakari Arvela, who has 15 years experience as a patent attorney, IPRally has built a knowledge graph to help ... recent out-of-the-box machine learning models are way too ...

Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language ...