blocks|key|1510977|text|这是一个很难回答的问题，像谷歌这样的公司正在努力解决这个问题。看看Google+Enterprise+Search+Appliance或Exalead+Enterprise+Search吧。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1510978|然后，作为我个人的观点，我不认为任何“朴素”的方法与朴素的关键字搜索和按文档上的浏览量排序相比，都不会有太大的改善。|1510979|如果你有可能将你的知识库暴露在网络上，那么就去做吧，让你最喜欢的搜索引擎为你处理搜索。|1510980|entityMap|0|LINK|mutability|MUTABLE|url|http://www.google.com/enterprise/gsa/|1|http://www.exalead.com/software/solutions/enterprise-search/^0|X|Y|0|1W|P|1|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]|$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|6|7|Y|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|Z|8|@]|9|@]|C|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|C|$]]]|I|$J|$5|K|L|M|C|$N|O]]|P|$5|K|L|M|C|$N|Q]]]]

That's a hard question, and companies like Google are pushing a lot of efforts to address this question. Have a look at <a href="http://www.google.com/enterprise/gsa/" rel="nofollow noreferrer">Google Enterprise Search Appliance</a> or <a href="http://www.exalead.com/software/solutions/enterprise-search/" rel="nofollow noreferrer">Exalead Enterprise Search</a>.

Then, as a personal opinion, I don't think that any "naive" approach is going to improve much the result compared to naive keyword search and ordering by the number of views on the documents.

If you have the possibility to expose your knowledge base to the web, then, just do it, and let your favorite search engine handles the search for you.

blocks|key|1511042|text|当处理问题时，关键字匹配是不够的，你需要理解意图，正如joannes所说的搜索中的一个非常热门的主题|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1511043|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

keyword matching is not enough when dealing with questions, you need to understand intent, as joannes say a very hot topic in search

blocks|key|1511113|text|你的确切问题更具体一点会更好。你可以使用很多不同的技术。其中许多都是由其他数据驱动的。当然，您可以使用Lucene并构建自己的索引。lucene有许多语言的绑定。接下来是Solr项目，它包含了很多工具和额外的功能。这可能更符合你正在寻找的东西。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1511114|意图是棘手的，大多数现代搜索引擎依赖于统计意图来帮助对结果进行排序。您可以始终使用is+this文章有用按钮，并存储指向有用文档的查询文本。然后，您可以向索引中添加一层信息，以增强特定的单词或短语，并帮助它们指向特定的文档。|1511115|一些东西，以思考about...How许多文件？平均长度是多少？它们是否经常更新？用户如何处理这些文档？将独特的单词传播到文档是什么样子的？(更简单的是，根据常见的独特特征将查询与特定文档进行匹配是否很容易。)|1511116|如果它是在网络上，你总是可以做一个谷歌自定义搜索引擎，只搜索你的网站，尽管你可能会发现由于各种原因，这是次优的。|1511117|您总是可以从一个简单的索引开始，然后通过与用户交谈和捕获数据来逐渐使其变得更加复杂。|1511118|entityMap|0|LINK|mutability|MUTABLE|url|http://lucene.apache.org/|1|http://lucene.apache.org/solr/^0|1F|6|0|2D|4|1|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@]|9|@$A|W|B|X|1|Y]|$A|Z|B|10|1|11]]|C|$]]|$1|D|3|E|5|6|7|12|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|13|8|@]|9|@]|C|$]]|$1|H|3|I|5|6|7|14|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|15|8|@]|9|@]|C|$]]|$1|L|3|-4|5|6|7|16|8|@]|9|@]|C|$]]]|M|$N|$5|O|P|Q|C|$R|S]]|T|$5|O|P|Q|C|$R|U]]]]

A little more specificity of your exact problem would be good. There are a lot of different techniques that you can use. Many of these are driven by other pieces of data. You can of course use <a href="http://lucene.apache.org/" rel="nofollow noreferrer">Lucene</a> and build your own indexes. There are bindings for many languages to lucene. Moving up there is also the <a href="http://lucene.apache.org/solr/" rel="nofollow noreferrer">Solr</a> project which is Lucene with a lot of tools and extra functionality around it. That may be more along the lines of what you are looking for.

Intent is tricky and most modern search engines rely on statistical intent to aid in the ordering of results. You can always have an is this article useful button and store the query text that leads to useful documents. You could then add a layer of information to the index to boost specific words or phrases and help them point to certain documents. 

Some things to think about...How many documents? What is the average length? Are they updated frequently? What do users do with the documents? What does the spread of unique words to documents look like? (More simply is it easy to match a query with a specific document(s) based on common unique features.) 

If it is on the web you can always make a google custom search engine that just searches your site although you may find this to be sub-optimal for a variety of reasons. 

You can always start with a simple index and gradually make it more sophisticated by talking with users and capturing data.

When developing a database of articles in a Knowledge Base (for example) - what are the best ways to sort and display the most relevant answers to a users' question?

Would you use additional data such as keyword weighting based on whether previous users found the article of help, or do you find a simple keyword matching algorithm to be sufficient?

Search ranking/relevance algorithms

数据库

在开发知识库中的文章数据库时(例如)-排序和显示用户问题的最相关答案的最佳方法是什么？您是否会根据以前的用户是否找到帮助文章来使用其他数据，例如关键字权重，或者您是否认为简单的关键字匹配算法就足够了？

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