Context sensitive synonym discovery for web search queries. Exploiting web search to generate synonyms for entities. Surajit Chaudhuri, Venkatesh Ganti, and Dong Xin.In Proceedings of the 3rd International Workshop on Semantic Search Over the Web, pages 2:1-2:4, NY, USA, 2013. Discovering Attribute and Entity Synonyms for Knowledge Integration and Semantic Web Search. Hamid Mousavi, Shi Gao, and Carlo Zaniolo.IEEE Transactions on Knowledge and Data Engineering, 24(10):1862-1875, October 2012. Entity Synonyms for Structured Web Search. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1384-1392, NY, USA, 2012. A Framework for Robust Discovery of Entity Synonyms. Kaushik Chakrabarti, Surajit Chaudhuri, Tao Cheng, and Dong Xin.In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, pages 348-355, 2007. An Information Retrieval Approach to Sense Ranking. Spelling correction as an iterative process that exploits the collective knowledge of web users. In HT '13: Proceedings of the 24th ACM conference on Hypertext and hypermedia. Discovering semantic associations from web search interactions. Michael Antunovic, Glyn Caon, Mark Truran, and Helen Ashman.These results indicate that even when candidate synonym pairs are confirmed as being semantically associated using other methods, they still may not be suitable for query substitution, depending on the method of synonym discovery. The third method however returned a very similar level of superior results as the original query, and saw over 71% of substituted queries generating either improved or equally-relevant results. It was found that two of the discovery methods returned significantly worse results with the substitution than were returned by the original query for the majority of queries, with only around 20-22% of substituted queries generating either improved or equally-relevant results. The suitability of the candidate synonym pairs for the purpose of query substitution is evaluated in an experiment where 68 subjects assessed the search results generated by both the original query and the substituted query. This discovery of synonyms or other semantic associations arises from different methods applied over web search logs, and in this paper we review the candidate synonym pairs of words or phrases generated from three different methods applied over the same web search logs. Many synonyms are not synonyms in the traditional, thesaurus sense, but are semantic associations discovered automatically from online data, with the risk of semantic drift in substitution. The value of substitution depends on how well the synonyms preserve semantic meaning, as any attrition in meaning can result in semantic drift of query results. 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.Synonyms or other semantic associations can be used in web search in query substitution to improve or augment the query to retrieve more relevant search results. 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. ![]() Content that ranks well in semantic search is well-written in a natural voice, focuses on the user's intent, and considers related topics that the user may look for in the future. 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 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.
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