在搜索包含具有数千页面文档的文件内容时，您所知道的内容往往比可以在字、短语或规则表达式中指定的内容多得多。
When searching for content in a file containing thousands of pages of documentation, you are likely to know much more than you can specify in just a word, phrase, or regular expression.
通过HTTP利用AS 2标准，如同八位字节流那样在伙伴之间发送二进制文档。
Binary documents are sent between partners as octet-streams using the AS2 standard over HTTP.
公正地说，查找包含关键字的文档列表是件很容易的事情，但是，排序技术却涉及到很多未知的技术和深奥的计算公式。
To be fair, finding the list of documents that contain the keywords is the easy part, while ranking techniques still involve a lot of black magic and secret evaluation formulas.
如果用户从读模式转换到编辑模式，则此属性可让关键字下拉公式在强制刷新文档时重新计算。
This allows the keyword drop-down formula to recalculate if the user switches from read mode to edit mode as long as the document is forced to refresh.
第一个参数是一个正则表达式，它代表触发客户机从数据库获取XML文档的关键字。
The first parameter is described using a regular expression and represents the keyword triggering the client to retrieve XML documents from the database.
如果字段有单个值，则简单的访问程序将把(关键字，值)对添加到文档中。
If a field has a single value, a simple accessor adds the (key, value) pair to the document.
尽管如此，如果您不得不处理吉字节的源文档，则相比较之下，即使兆字节大小的块也显得很好管理。
Still, if you have to worry about gigabyte source documents, even a megabyte block looks pretty manageable in comparison.
DOCID 存放查找文档的关键字。
要深入了解MySQL参照完整性，请参考MySQL产品文档中关于外部关键字的部分。
For more on MySQL referential integrity, please see the section on foreign keys constraints in the MySQL product documentation.
例如，good是good和better的词元，所以关键字搜索会返回包含任意一个词汇的文档。
For example, good is a lemma for good and better, so the keyword search returns documents containing either of these terms.
然而，关键字搜索不会只包含better的其他词元的单词，因此包含well的文档不会返回。
However, the keyword search does not include documents containing only words with other lemmas of better, thus documents containing well are not included.
所有文档字段(语言、文档类型、源等)和facet数据都被放到映射图中。映射图的关键字为字符串，以“ field. ”。
All document fields (language, document type, source, etc.) and facet data are put into the map.
每一个索引文档也具有多值字段unid，其中包含与为该索引文档分配的关键字相匹配的源数据库中的所有文档的UNID。
Each index document also has multi-value field UNIDs, which contain the UNIDs of all documents in the source database that match the keyword assigned for that index document.
每一个源文档的关键字持有者文档的数目与每个文档的搜索字段的数目相同。
The number of keyword holder documents per source document is the same as the number of search fields in each document.
这两个方法主要的共同之处是，它们都使用一个关键字作为参数，并返回一个或多个精确匹配的文档作为结果。
The main similarity between these two methods is that they both take one keyword as a parameter and return one or more exact matching documents as a result.
区域包含关于文档的信息，如所有权、版权和关键字；而 区域包含要显示的文档内容。
The area contains information about the document, such as ownership, copyright, and keywords; and the area contains the content of the document to be displayed.
如果没有找到文档，用户将看到一条消息指出没有带有该关键字的文档。
If no document was found, the user sees a message stating that no document with such a keyword exists.
事实上，对数以千计的、包含请求搜索的关键字的文档进行排序，以便将与用户最相关的文档列在最上方，这并不是一件容易的任务。
Indeed, taking the thousands of documents that contain the requested keywords and ordering them so the most relevant for the user are at the top is no easy task.
若必须处理许多兆字节的XML文档，花费内存、磁盘空间和CPU开销来操作这么大的文档通常是不实际的。
If you must deal with many-megabyte XML documents, it's often impractical to spend the memory, disk space, and CPU overhead to manipulate such huge documents.
关键字是帮助文档在搜索引擎快速查询结果的词语；一般技能领域和熟练程度。
Keywords are words that help a document appear in a search engine result; general skills areas and proficiencies.
保持对一个特殊的文档中多个关键字的跟踪。
如果用户希望访问较大的文档中前面的数个字节或数千字节，则延迟构建功能将改善该应用程序的内存需求情况。
If a user wants to access first couple of bytes or kilo bytes in a larger document, then the deferred building capability will enhance the memory requirement of that application.
从技术的角度来看，倒排索引用于存储文档中出现的关键字，并且支持搜索，它是一种广为熟悉并且精确描述的数据结构。
From a technical perspective, the inverted index, used to store keywords that appear in documents and enable searches, is a well-known and well-described data structure.
这与“使查找频率最小化”中描述的内容相似，并且在文档处于读模式时它可防止关键字下拉列表执行查找。
This is similar to what is described in "Maximize the frequency of your lookups," and it prevents the keyword drop-down list from performing the lookup if the document is in read mode.
它允许用户执行快速关键字查询，查找匹配给定查询的文档。
It lets users perform fast keyword look-ups and finds the documents that match a given query.
这表示任何小于或等于3000字节的文档都可以进行内联。
This means that any document that can be stored in 3000 bytes or less will be inlined.
关键字搜索会返回包含这些变化的文档。
Documents that contain such variations are returned for a keyword search.
上传文档的大小被限制为0字节到1兆字节。
The size of the uploaded document is limited between 0 bytes and 1 Megabyte.
作为特定关键字的搜索结果返回的文档数目多于500。
The number of documents returned as a search result for a particular keyword is greater than 500.
除了使用关键字进行搜索之外，您还可以使用浏览的方法进行搜索，这种方法使用分层结构的、类似于目录的结构来定位文档。
An alternative to using keywords, you can also search using a browsing approach, which locates documents using a hierarchical, directory-like structure.
应用推荐