Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
Ontologies are a representation of knowledge that defines concepts and the relationships among them. Ontologies enable machines to structure and reason information in a…