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Semantic search seeks to improve search accuracy by understanding searcher 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. Author Seth Grimes lists "11 approaches that join semantics to search", and Hildebrand et al. provide an overview that lists semantic search systems and identifies other uses of semantics in the search process. [ 1 ] 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 ] Major web search engines like Google and Bing incorporate some elements of semantic search.