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Semantic search denotes search with meaning, as distinguished from lexical search where the search engine looks for literal matches of the query words or variants of them, without understanding the overall meaning of the query. [ 1] Semantic search seeks to improve search accuracy by understanding the searcher's intent and the contextual ...
A semantic data model ( SDM) is a high-level semantics-based database description and structuring formalism ( database model) for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the ...
The Semantic Web, sometimes known as Web 3.0 (not to be confused with Web3 ), is an extension of the World Wide Web through standards [1] set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description ...
The main academic full-text databases are open archives or link-resolution services, although others operate under different models such as mirroring or hybrid publishers. Such services typically provide access to full text and full-text search, but also metadata about items for which no full text is available.
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 (meaning of language constructs) in unstructured text to produce a better search result.
Graph database. A graph database ( GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. [1] A key concept of the system is the graph (or edge or relationship). The graph relates the data items in the store to a collection of nodes and edges, the edges representing the ...
Semantic Scholar. Semantic Scholar is a research tool for scientific literature powered by artificial intelligence. It is developed at the Allen Institute for AI and was publicly released in November 2015. [ 2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing ...
Monster Introduces SeeMore™, its Semantic Search and Analytics Recruiting Platform in France The first in a series of non-English versions to be rolled out globally MAYNARD, Mass.--(BUSINESS ...