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In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...
Systems Biology Ontology (SBO), for computational models in biology; SWEET, [70] Semantic Web for Earth and Environmental Terminology; SSN/SOSA, [71] The Semantic Sensor Network Ontology (SSN) and Sensor, Observation, Sample, and Actuator Ontology (SOSA) are W3C Recommendation and OGC Standards for describing sensors and their observations.
In representation learning, knowledge graph embedding (KGE), also called knowledge representation learning (KRL), or multi-relation learning, [1] is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning.
For example, knowledge about a compressor system includes that a compressor system consists of a compressor, a lubrication system, etc., whereas a lubrication system consists of a pump system, etc. Assume that this knowledge is expressed in a knowledge representation language that expresses knowledge as a collection of relations between two ...
Edward Hitchcock's fold-out paleontological chart in his 1840 Elementary Geology. Although tree-like diagrams have long been used to organise knowledge, and although branching diagrams known as claves ("keys") were omnipresent in eighteenth-century natural history, it appears that the earliest tree diagram of natural order was the 1801 "Arbre botanique" (Botanical Tree) of the French ...
A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [1] In general, networks or graphs are used to capture relationships between entities or objects. [1]
Classification is the process in which ideas and objects are recognized, differentiated, and understood, and classification charts are intended to help create and eventually visualize the outcome. According to Brinton "in a classification chart the facts, data etc. are arranged so that the place of each in relation to all others is readily seen.
His 2004 classification treated the archaeobacteria as part of a subkingdom of the kingdom Bacteria, i.e., he rejected the three-domain system entirely. [72] Stefan Luketa in 2012 proposed a five "dominion" system, adding Prionobiota (acellular and without nucleic acid) and Virusobiota (acellular but with nucleic acid) to the traditional three ...