Unsupervised word embeddings provide rich linguistic and conceptual information about words. However, they may provide weak information about domain specific semantic relations for certain tasks such ...

Researchers identified two brain networks involved in word retrieval -- the cognitive process of accessing words we need to speak. A semantic network processes meaning in middle/inferior frontal ...

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong.

But as mobile hardware advances, Machine Learning (ML) techniques, particularly Graph Neural Networks (GNNs), are emerging as a powerful, efficient alternative to emulate physics on mobile. GNNs are ...

The film explores the complexities of meaning in language, highlighting three types: denotative meaning (the literal reference of a word), conceptual meaning (the ideas associated with a word ...

The graph of knowledge vs. the knowledge graph: GoK is a broader, more conceptual idea focusing on interconnected information, without necessarily being highly structured.

The team proposed a Graph-Segmenter, including a Graph Transformer and a Boundary-aware Attention module, which is an effective network for simultaneously modeling the more profound relation ...

Semantic Web Company and Ontotext announced that the two organizations are merging to create a knowledge graph and AI powerhouse, Graphwise. Semantic Web Company brings expertise in knowledge ...