翻訳と辞書
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・ "O" Is for Outlaw
・ "O"-Jung.Ban.Hap.
・ "Ode-to-Napoleon" hexachord
・ "Oh Yeah!" Live
・ "Our Contemporary" regional art exhibition (Leningrad, 1975)
・ "P" Is for Peril
・ "Pimpernel" Smith
・ "Polish death camp" controversy
・ "Pro knigi" ("About books")
・ "Prosopa" Greek Television Awards
・ "Pussy Cats" Starring the Walkmen
・ "Q" Is for Quarry
・ "R" Is for Ricochet
・ "R" The King (2016 film)
・ "Rags" Ragland
・ ! (album)
・ ! (disambiguation)
・ !!
・ !!!
・ !!! (album)
・ !!Destroy-Oh-Boy!!
・ !Action Pact!
・ !Arriba! La Pachanga
・ !Hero
・ !Hero (album)
・ !Kung language
・ !Oka Tokat
・ !PAUS3
・ !T.O.O.H.!
・ !Women Art Revolution


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taxonomy for search engines : ウィキペディア英語版
taxonomy for search engines
Taxonomy of entities for search engines are designed to improve relevance in vertical search. Taxonomies of entities are trees whose nodes are labelled with entities which expect to occur in a web search query. These trees are used to match keywords from search query with the keywords from answers (or snippets).
Taxonomies, thesauri and concept hierarchies are crucial components for many applications of information retrieval, natural language processing and knowledge management. Building, tuning and managing taxonomies and ontologies is rather costly since a lot of manual operations are required. A number of studies proposed the automated building of taxonomies based on linguistic resources and/or statistical machine learning
Web mining is one of the approach to build search engine taxonomies for web search. The taxonomy construction process starts from the seed entities and mines available source domains for new entities associated with these seed entities. New entities are formed by applying the machine learning to the current web search results for existing entities to form commonalities between them. These commonality expressions then form parameters of existing entities, and are turned into new entities at the next learning iteration
==References==


抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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