Help:CirrusSearch/pt-br

O CirrusSearch é o novo mecanismo de busca para o MediaWiki. Ele apresenta melhorias importantes em relação ao antigo, LuceneSearch. Esta página descreve os recursos que são novos ou diferentes em comparação com as soluções do passado.

Very studs== Perguntas mais frequentes ==yymrnhbryftujhtyjksgx

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O que foi melhorado?
O novo mecanismo de busca dispõe de três principais melhorias em relação ao antigo, nomeadamente:


 * Melhor suporte para pesquisas em diferentes idiomas.
 * Atualizações mais rápidas para o índice de pesquisa, ou seja, as alterações nos artigos são refletidas muito mais rápido nos resultados.
 * Abrangência em predefinições, o que significa que todo o conteúdo num artigo que esteja incluído numa predefinição será refletido nos resultados da pesquisa.

Atualizações
Atualizações no índice de pesquisa são feitas quase em tempo real. Deverá ser capaz de pesquisar as mesmas assim que estas forem feitas. As mudanças em predefinições devem, em poucos minutos. As mudanças em predefinições usam a fila de espera, por isso o desempenho pode variar. Uma edição nula ao artigo irá forçar a mudança, mas isso não deverá ser necessário se tudo está estiver a correr bem.

Sugestões de pesquisa
As sugestões de pesquisa que aparecem quando você digita na caixa de pesquisa são ordenadas substancialmente pelo número de links internos recebidos. Algo digno de nota é que se você iniciar a sua pesquisa com um til (~), não vamos encontrar nenhum artigo e você pode seguir a qualquer momento, ao carregar na tecla "Enter", para a página de resultados de pesquisa.

ASCII/accents/diacritics folding is turned on for English text, but there are some formatting problems with the result. See 52656.

Pesquisa completa de texto
A pesquisa completa de texto (aquela que o leva à página de resultados) em títulos, redirecionamentos, cabeçalhos e textos de artigo não deverá trazer quaisquer surpresas. A grande alteração é que agora também abrange predefinições.

Existem alguns bugs abertos relevantes:


 * Frases correspondentes de forma rigorosa nem sempre estão devidamente destacadas

Filters (intitle:, incategory: and linksto:)


Reforçamos um pouco a sintaxe em torno destes exemplos.


 * intitle:foo
 * Encontre artigos cujos títulos contenham a palavra "foo". Permite pesquisa de derivados.
 * intitle:"bar foo"
 * Encontre artigos cujos títulos contenham as palavras "bar" e "foo". Permite pesquisa de derivados.
 * intitle:bar foo
 * Encontre artigos cujos títulos contenham a palavra "bar" e, quer seja título ou texto, possuam a palavra "foo"
 * -intitle:bar foo
 * Encontre artigos cujos títulos não contenham a palavra "bar", mas, quer seja no título ou texto incluso, possuam a palavra "foo".
 * intitle: bar foo
 * Erro de sintaxe, devolve aos resultados de pesquisa artigos cujos títulos ou textos incluam as palavras "intitle:", "foo" e/ou "bar".
 * incategory:Música
 * Encontra artigos que estejam na Categoria:Música
 * incategory:"História da música‎"
 * Encontra artigos que estejam na Categoria:História da música‎
 * incategory:"musicals" incategory:"1920"
 * Find articles that are in both Category:Musicals and Category:1920
 * -incategory:"musicals" incategory:"1920"
 * Find articles that are not in Category:Musicals but are in Category:1920
 * cow*
 * Find articles whose title or text contains words that start with cow
 * linksto:Help:CirrusSearch
 * find articles that link to a page
 * -linksto:Help:CirrusSearch CirrusSearch
 * find articles that mention CirrusSearch but do not link to the page Help:CirrusSearch

prefix:
Na sua forma atual, a sintaxe prefix: é invocada para vários tipos de funcionalidades, logo foi recriada com o maior tipo de exatidão possível.


 * prefix:cow
 * Encontre artigos nos domínios de conteúdo cujo título comece com a palavra "cow".
 * domestic prefix:cow
 * Encontre artigos nos domínios de conteúdo cujo título comece com a palavra "cow" e contenha a palavra "domestic".
 * domestic prefix:Cow/
 * Encontre todas as subpáginas do artigo "Cow" nos domínios de conteúdo que contenham a palavra "domestic". Este tipo de pesquisa é bastante comum e frequentemente construído com um parâmetro de URL especial chamado.
 * domestic prefix:Talk:Cow/
 * Find all sub-pages of the talk page "Talk:Cow" in the talk namespace that contain the word "domestic".
 * cow prefix:Pink Floyd/
 * Find all sub-pages of the article "Pink Floyd" in the content namespaces that contain the word "cow". The space is now insignificant.

Repare que a regra anterior, de incluir prefix: no final da consulta, ainda se aplica.

Prefixos especiais

 * morelike:Endothermic
 * Find articles whose text is similar to Endothermic.
 * Talk:Foo
 * Find articles in the talk namespace whose title or text contains the word foo

Será que quis dizer
"Did you mean" suggestions are designed to notice if you misspell an uncommon phrase that happens to be an article title. If so, they'll let you know. They also seem to suggest more things than they ought to sometimes.

Prefira correspondências de frase
If you don't have too much special syntax in your query we'll give perfect phrase matches a boost. I'm being intentionally vague because I'm not sure exactly what "too much special syntax" should be. Right now if you add any explicit phrases to your search we'll turn off this feature.

Busca do Fuzzy
Putting a ~ after a search term (but not double quotes) activates fuzzy search. You can also put a number from 0 to 1 to control the "fuzziness" fraction, e.g. nigtmare~.9 or lighnin~.1 or lighnin~0.1. Closer to one is less fuzzy.

Pesquisa de frase e de proximidade
Surrounding some words with quotes declares that you are searching for those words close together. You can add a ~ and then a number after the second quote to control just how close you mean. The proper name for this "closeness" is "phrase slop". The default "phrase slop" is 1.

Aspas e correspondências exatas
Quotes turn on exact term matches. You can add a ~ to the quote to go back to the more aggressive matcher you know and love.

prefer-recent:
You can give recently edited articles a boost in the search results by adding "prefer-recent:" to the beginning of your search. By default this will scale 60% of the score exponentially with the time since the last edit, with a half life of 160 days. This can be modified like this: "prefer-recent:,". proportion_of_score_to_scale must be a number between 0 and 1 inclusive. half_life_in_days must be greater than 0 but allows decimal points. This number works pretty well if very small. I've tested it around .0001, which is 8.64 seconds.

This will eventually be on by default for Wikinews, but there is no reason why you can't activate it in any of your searches.

hastemplate:
You can filter pages to just those that use a template by adding  to the search. We try to emulate the template inclusion syntax so  finds pages with   and   would find transclusions of the article   from the main namespace. You can omit the quotes if the template's title you are looking for does not contain a space. will filter pages that contain that template.

You can combine all sorts of fun search syntax to get only middle quality images of china.

boost-templates:
You can boost pages scores based on what templates they contain. This can be done directly in the search via  or you can set the default for all searches via the new   message. replaces the contents of  if the former is specified. The syntax is a bit funky but was chosen for simplicity. Some examples:


 * Find files in the China category sorting quality images first.
 * Find files in the China category sorting quality images first.


 * Find files in the China category sorting quality images first and low quality images last.
 * Find files in the China category sorting quality images first and low quality images last.


 * Find files about popcorn sorting quality images first and low quality images last. Remember that through the use of the  message this can be reduced to just.
 * Find files about popcorn sorting quality images first and low quality images last. Remember that through the use of the  message this can be reduced to just.

Don't try to add decimal points to the percentages. They don't work and search scoring is such that they are unlikely to matter much.

A word of warning about : if you add really really big or small percentages they can poison the full text scoring. Think, for example, if enwiki boosted featured articles by a million percent. Then searches for terms mentioned in featured articles would find the featured articles before exact title matches of the terms. Phrase matching would be similarly blown away so a search like  would find a featured article with those words scattered throughout it instead of the article for Brave New World.

Sorry for the inconsistent  in the name. Sorry again but the quotes are required on this one. Sorry also for the funky syntax. Sorry we don't try to emulate the template transclusion syntax like we do with.

insource:

 * Coming with 1.24wmf10.

will search text just in the wikitext. This will pick up template parameter names, URLs in link tags, etc. It has two flavors:
 * and
 * These work pretty similarly to  in that they search the pre-tokenized version of the source.  This should be just as quick as a regular search.  The quoted version searches for phrases in the source.


 * and
 * These run Regular expressions against the page source. They aren't efficient and we only allow a few of them to run at a time on the search cluster, but they are very powerful.  This link contains an explanation of the syntax and this link contains an actual grammar for the regex language. The version with the extra   runs the expression case insensitive and is even more inefficient.

Texto Auxiliar
Cirrus considers some text in the page to be "auxiliary" to what the page is actually about. Examples include table contents, image captions, and "This article is about the XYZ. For ZYX see ZYX" style links. You can also mark article text as auxiliary by adding the  class to the html element containing the text.

Auxiliary text is worth less then the rest of the article text and it is in the snippet only if there are no main article snippets matching the search.

Texto Principal
Cirrus assumes that non-auxiliary text that is between the top of the page and the first heading is the "lead in" paragraph. Matches from the lead in paragraph are worth more in article ranking.