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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 meaning ...
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.
Results of their work include the RDF(S) based Corese [52] search engine, and the application of semantic web technology in the realm of distributed artificial intelligence for knowledge management (e.g. ontologies and multi-agent systems for corporate semantic Web) [53] and E-learning. [54]
Monster's 6Sense® Semantic Search Technology Launches in the Netherlands Power Resume Search®, Powered by 6Sense®, Improves Hiring Efficiency and Effectiveness for Companies around the World ...
In 2011, Lexxe launched a beta version [2] [3] with a new search technology called Semantic Key. Semantic Keys enable users to query with a conceptual keyword (or a keyword with a special meaning, hence the term Semantic Key) in order to find instances under the concept, e.g. price → $5.95 or €200, color → red, yellow, white.
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
In general, information retrieval research and technology can be divided into two broad categories: semantic and statistical. Information retrieval systems that fall into the semantic category will attempt to implement some degree of syntactic and semantic analysis of the natural language text that a human user would provide (also see computational linguistics).
Semantic computing is a field of computing that combines elements of semantic analysis, natural language processing, data mining, knowledge graphs, and related fields. Semantic computing addresses three core problems: Understanding the (possibly naturally-expressed) intentions of users and expressing them in a machine-processable format