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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 of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results. Semantic search systems consider various points including context of search, location, intent, variation of words, synonyms, generalized and specialized queries, concept matching and natural language queries to provide relevant search results.[2][better source needed]

Some authors regard semantic search as a set of techniques for retrieving knowledge from richly structured data sources like ontologies and XML as found on the Semantic Web.[3] Such technologies enable the formal articulation of domain knowledge at a high level of expressiveness and could enable the user to specify their intent in more detail at query time.[4]

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ReferencesEdit

  1. ^ Bast, Hannah; Buchhold, Björn; Haussmann, Elmar (2016). "Semantic search on text and knowledge bases". Foundations and Trends in Information Retrieval. 10 (2–3): 119–271. doi:10.1561/1500000032. Retrieved 1 December 2018.
  2. ^ John, Tony (March 15, 2012). "What is Semantic Search?". Techulator. Retrieved July 13, 2012.
  3. ^ Dong, Hai (2008). A survey in semantic search technologies. IEEE. pp. 403–408. Retrieved 1 May 2009.
  4. ^ Ruotsalo, T. (May 2012). "Domain Specific Data Retrieval on the Semantic Web". ESWC2012: 422–436. doi:10.1007/978-3-642-30284-8_35. Retrieved August 14, 2012.

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