spaces through forms of embedding has benefits in expressing entity relationships as well as extracting relations from mediums like text. There are many approaches to learning these embeddings, notably using Bayesian clustering frameworks or energy-based frameworks, and more recently, TransE (NIPS 2013). Applications of embedding knowledge base data include Social network analysis and Relationship extraction. See also Abstract semantic graph Chunking (psychology) CmapTools Concept map Network diagram Ontology (information science) Repertory grid Semantic lexicon Semantic similarity network Semantic neural network SemEval – an ongoing series of evaluations of computational semantic analysis systems Sparse distributed memory Taxonomy (general) Unified Medical Language System (UMLS) Word-sense disambiguation (WSD) Resource Description Framework Other examples Cognition Network Technology Lexipedia OpenCog Open Mind Common Sense (OMCS) Schema.org SNOMED CT Universal Networking Language (UNL) Wikidata Freebase References Further reading Allen, J. and A. Frisch (1982). "What's in a Semantic Network". In: Proceedings of the 20th. annual meeting of ACL, Toronto, pp. 19–27. John F. Sowa, Alexander Borgida (1991). Principles of Semantic Networks: Explorations in the Representation of Knowledge. Segev, E. (Ed.) (2022). Semantic Network Analysis in Social Sciences. New York: Routledge. External links "Semantic Networks" by John F. Sowa "Semantic Link Network" by Hai Zhuge Knowledge representation Networks Semantic relations