this means that developers can integrate index and search into their applications, or build entirely new user interfaces around search.
这意味着开发人员能将索引和搜索整合到他们的应用中,或者围绕搜索构建全新的用户接口。
how to use the zend_search module and related classes to index and search data.
如何使用 zend_search模块和相关类来索引和搜索数据。
the example creates a simple search engine written in php that can index and search files using apache lucene.
此示例创建了使用php编写的简单搜索引擎,可以使用apachelucene 建立文件索引和进行搜索。
it is difficult for these systems to effectively index and search the rapidly increasing music materials.
这些系统难以对飞速产生的音乐资料进行及时有效地索引和检索。
that’s far different from traditional search engines which all index and search the public web.
这与标记、搜索公共网页的传统的搜索引擎大不相同。
this paper implements spatial data index and search of gis, which can ensure the quickness and exactness of the query and search results.
可实现gis中空间数据索引、检索功能,保证了空间数据查询的快速性和準确性。
fortunately, starting in ibm i 7.1, a solution exists that allows us to index and search the text data associated with these ibm i objects.
幸运的是,从ibmi7.1开始,就有一个解决方案允许我们索引和搜索与这些ibmi对象相关的文本数据。
firstly, this paper introduces the characteristics and classes of search engine, then anatomizes its system architecture, and analyzes the processes of index and search among them.
首先介绍搜索引擎技术的特点分类,再剖析搜索引擎的系统架构,然后详细分析其中的索引和搜索过程,最后预测了搜索引擎技术的发展趋势。
it also briefly describes the fundamental process and related api of using lucene to implement the index and search function.
简单说明了采用lucene进行索引和搜索的基本过程和相关的api。
index your files is an alternative way for you to index and search through all your files or folders on local or networked drives .
索引你的文件是另一种方式可以让您通过索引和搜索所有的文件夹或驱动器的本地或网络 。
for a real world example, this article steps through the creation of a simple search engine written in php that can index and search files using apache lucene.
有关真实示例,本文逐步说明了使用 php编写的简单搜索引擎的创建工作,此引擎可使用apachelucene 建立文件索引和进行搜索。
thus, the remainder of the article will focus on how to index and search spatial information using lucene and solr.
本文后面的内容将关注如何使用lucene和solr 为空间信息建立索引并搜索它们。
both solr and sphinx satisfy all of your requirements. they're fast and designed to index and search large bodies of data efficiently.
两者都满足你的需求。它们都很快,面向于大数据量下的高效率的建立索引,搜索。
you could embed a search-engine implementation, such as apache lucene, into your application to index and search text columns (see resources).
您可以将搜索引擎实现(如apachelucene)嵌入您的应用程序,以便索引并搜索文本列(请参考 参考资料)。
finally, according to the segmentation information, the indexing module finish the index and search work.
最后,索引部分根据分词信息完成搜索引擎的索引建立和检索工作。