Semantic Query
A Semantic Query is a Pattern Matching that ...
- See: Semantic Wiki, Pattern Matching, Reasoning System, Named Graphs, Linked Data, Resource Description Framework#Overview, Semantic Search, Semantics, Unstructured Data, Natural Language Processing, SQL, Type Inheritance.
References
2016
- (Wikipedia, 2016) ⇒ http://wikipedia.org/wiki/semantic_query Retrieved:2016-3-24.
- Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results (possibly the distinctive selection of one single piece of information) or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.
Semantic queries work on named graphs, linked-data or triples. This enables the query to process the actual relationships between information and infer the answers from the network of data. This is in contrast to semantic search, which uses semantics (the science of meaning) in unstructured text to produce a better search result (see Natural language processing).
From a technical point of view semantic queries are precise relational-type operations much like a database query. They work on structured data and therefore have the possibility to utilize comprehensive features like operators (e.g. >, < and =), namespaces, pattern matching, subclassing, transitive relations, semantic rules and contextual full text search. The semantic web technology stack of the W3C is offering SPARQL to formulate semantic queries in a syntax similar to SQL. Semantic queries are used in triplestores, graph databases, semantic wikis, natural language and artificial intelligence systems.
- Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results (possibly the distinctive selection of one single piece of information) or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.