Search results
Results from the WOW.Com Content Network
Biological rules and laws are often developed as succinct, broadly applicable ways to explain complex phenomena or salient observations about the ecology and biogeographical distributions of plant and animal species around the world, though they have been proposed for or extended to all types of organisms. Many of these regularities of ecology ...
Semantic versioning three-part version number. Semantic versioning (aka SemVer) [1] is a widely-adopted version scheme [7] that encodes a version by a three-part version number (Major.Minor.Patch), an optional pre-release tag, and an optional build meta tag. In this scheme, risk and functionality are the measures of significance.
In the context of the Semantic Web, Ontology versioning is the process of formally distinguishing between different versions of vocabularies. References
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.
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
Force dynamics is a semantic category that describes the way in which entities interact with reference to force. Force Dynamics gained a good deal of attention in cognitive linguistics due to its claims of psychological plausibility and the elegance with which it generalizes ideas not usually considered in the same context.
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.