M.Tech / M.E / PhD Thesis | Information Technology | India | Volume 5 Issue 7, July 2016
Information Retrieval Using Semantic Distance between WordNet
Rahul Shirbhate, Vishal Mogal
Semantic search seeks to improve search accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable data space, whether on the Web or within a closed system, to generate more relevant results. There are 11 approaches that join semantics to search and provide an overview that lists semantic search systems and identifies other uses of semantics in the search process. Semantic search systems consider various points including context of search, location, intent, and variation of words, synonyms, generalized and specialized queries, concept matching and natural language queries to provide relevant search results. Major web search engines like Google and Bing incorporate some elements of semantic search. The semantic web is a idea of teaching the web which is to say teaching the next generation of web search engines and web browsers how to understand the content rather than just the structure on the web.
Keywords: geographic concepts, semantic similarity, geo-knowledge graphs, network-lexical similarity measure NLS, lexical similarity, network similarity
Edition: Volume 5 Issue 7, July 2016
Pages: 1593 - 1596
How to Cite this Article?
Rahul Shirbhate, Vishal Mogal, "Information Retrieval Using Semantic Distance between WordNet", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART2016505, Volume 5 Issue 7, July 2016, 1593 - 1596
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