清单3显示了通配符查询的过程。
Listing 3 demonstrates the process of doing a wildcard search.
通常通过给对象中要搜索的一个或多个字段输入搜索文本(有时候支持通配符功能)来指定查询。
The query is typically specified by entering search text (sometimes with wildcard functionality) for one or more of the fields in the object to be searched.
使用通配符搜索的一个查询示例见清单21。
A sample query using wildcard search is shown in Listing 21.
在IICE查询语言中，通配符由 ‘*’（多个字符）和 ‘?’ （单个字符）表示，只能在全文或属性搜索中与LIKE 操作符一起使用。
Wildcards, represented by '*' (multiple characters) and '?' (a single character) in the II CE query language, can only be used with the LIKE operator in either a full-text or a property search.
很多应用程序都不需要LuceneQueryparser语法的全部，尤其是使用通配符和其他高级查询类型的情况下就更是如此。
Many applications do not need the full power of the Lucene query Parser Syntax, especially the use of wildcards and other more advanced query types.
xml索引和查询谓词中的通配符。
DB 2NetSearchExtender提供了一种灵活的查询语言，可以根据复杂的获取操作(例如涉及布尔组合、通配符和模糊搜索)寻找相关信息。
DB2 Net search Extender provides a flexible query language to find relevant information based on complex retrieval operations involving Boolean combination, wildcard, and fuzzy search, for example.
第一步是创建与每个查询词一致的正则表达式，只有在查询词包含通配符 * 时才需要修改。
The first step is to create a compatible regular expression out of each query word, although modification is only required if the word contains a wildcard character: *.
只要有可能，建议使用索引定义和查询中所需元素或属性的准确路径，而不使用通配符。
Wherever possible, it is recommended to use the exact path to the desired elements or attributes in index definitions and queries, without wildcards.
再次运行查询并手动删除任何不需要的通配符。
Run the query again and manually remove any unwanted wildcard characters.
中文原译数据提供者执行搜索查询失败，因为通配符术语与单个信息空间的太多术语匹配。
Data provider (s) failed to execute the search query because a wildcard term matches too many terms for a single information space.
其目的在于提高基于相似字符串匹配的查询在大规模字符串数据库中的查询效率，并且提供带通配符的字符串查询方式。
The purposes of it were to improve the efficiency of searching a string in a large-scale database by the means of approximate string matching and to provide a means to search a string with wildcards.
我们遇到带有通配符和邻近搜索的复杂查询，有时需要超过15秒才能获得前100个文档。
We encounter complex queries having wild CARDS and proximity searches together and it sometimes takes more than 15 secs to get top 100 documents.
我们遇到带有通配符和邻近搜索的复杂查询，有时需要超过15秒才能获得前100个文档。
We encounter complex queries having wild CARDS and proximity searches together and it sometimes takes more than 15 secs to get top 100 documents.
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