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Semantic search seeks to improve search accuracy by understanding the searcher's intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results. Some authors regard semantic search as a set of techniques for retrieving knowledge from richly ...
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 ...
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 ...
Semantic technology. The ultimate goal of semantic technology is to help machines understand data. To enable the encoding of semantics with the data, well-known technologies are RDF (Resource Description Framework) [1] and OWL (Web Ontology Language). [2] These technologies formally represent the meaning involved in information.
Semantic integration. Semantic integration is the process of interrelating information from diverse sources, for example calendars and to do lists, email archives, presence information (physical, psychological, and social), documents of all sorts, contacts (including social graphs ), search results, and advertising and marketing relevance ...
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.
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.
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 ...