blocks|key|2765274|text|AFAIK如果不在SOLR中存储数据，这是不可能的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2765275|如果你想做文本分析(我知道这比你要求的更广泛)，我会推荐下面的替代方案：|2765276|2765277|MAUI+-+does关键词组和术语extraction.|ordered-list-item|offset|length|2765278|Gensim+-+does+modelling|2765279|Kea+-+keyword+extraction|2765280|2765281|我还遇到了一些执行词频分析的python脚本。看看Mincemeat，特别是这个例子，它进行词频计算。|2765282|entityMap|0|LINK|mutability|MUTABLE|url|http://code.google.com/p/maui-indexer/|1|http://radimrehurek.com/gensim/|2|http://www.nzdl.org/Kea/|3|https://github.com/michaelfairley/mincemeatpy^0|0|0|0|0|4|0|0|0|6|1|0|0|3|2|0|0|P|9|3|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|15|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|16|8|@]|9|@]|A|$]]|$1|E|3|F|5|G|7|17|8|@]|9|@$H|18|I|19|1|1A]]|A|$]]|$1|J|3|K|5|G|7|1B|8|@]|9|@$H|1C|I|1D|1|1E]]|A|$]]|$1|L|3|M|5|G|7|1F|8|@]|9|@$H|1G|I|1H|1|1I]]|A|$]]|$1|N|3|-4|5|6|7|1J|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|1K|8|@]|9|@$H|1L|I|1M|1|1N]]|A|$]]|$1|Q|3|-4|5|6|7|1O|8|@]|9|@]|A|$]]]|R|$S|$5|T|U|V|A|$W|X]]|Y|$5|T|U|V|A|$W|Z]]|10|$5|T|U|V|A|$W|11]]|12|$5|T|U|V|A|$W|13]]]]

AFAIK this isn't possible without storing data in SOLR.

If you are looking to do text analysis (I understand this is broader than what you ask for), I would recommend the below alternatives:

<ol>
<li><a href="http://code.google.com/p/maui-indexer/" rel="nofollow">MAUI</a> - does keyphrase and terminology extraction.</li>
<li><a href="http://radimrehurek.com/gensim/" rel="nofollow">Gensim</a> - does topic modelling</li>
<li><a href="http://www.nzdl.org/Kea/" rel="nofollow">Kea</a> - keyword extraction</li>
</ol>

I've also come across some python scripts that do term frequency analysis. Have a look at <a href="https://github.com/michaelfairley/mincemeatpy" rel="nofollow">Mincemeat</a>, particulary the example, which does term frequency calculation.

blocks|key|825260|text|根据你的要求，我得出结论，你实际上需要一个搜索库，而不是一个完整的搜索引擎(服务)。这个库就是Lucene。也许，这会对初学者有所帮助：How+to+extract+Document+Term+Vector+in+Lucene+3.5.0。您可以将索引存储在RAM中，以便计算必要的位，然后删除索引。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|825261|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/8776794/how-to-extract-document-term-vector-in-lucene-3-5-0^0|1W|1F|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

From what you ask for I conclude that you actually need a search library, not a full search engine (service). That library is Lucene. Perhaps, this will help for starters: <a href="https://stackoverflow.com/questions/8776794/how-to-extract-document-term-vector-in-lucene-3-5-0">How to extract Document Term Vector in Lucene 3.5.0</a>. You could store the index in RAM for the sake of computing necessary bits and then get rid of the index.

blocks|key|825269|text|几年前，我用Java编写了一个基于Lucene进行繁重文本分析的应用程序。我不得不自定义编写搜索函数来查找彼此之间一定距离内的单词。您可以将文本文档导入到软件中，让它计算词频，或者您可以根据需要提取代码并对其进行泰勒处理。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|825270|免费下载：http://www.minoesoftware.com/download.php|offset|length|825271|来源：https://github.com/danspiteri/MINOE/blob/master/src/minoe/SearchFiles.java|825272|entityMap|0|LINK|mutability|MUTABLE|url|http://www.minoesoftware.com/download.php|1|https://github.com/danspiteri/MINOE/blob/master/src/minoe/SearchFiles.java^0|0|5|15|0|0|3|22|1|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@$D|T|E|U|1|V]]|A|$]]|$1|F|3|G|5|6|7|W|8|@]|9|@$D|X|E|Y|1|Z]]|A|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|O]]|P|$5|K|L|M|A|$N|Q]]]]

I wrote an application in Java several years ago that did heavy text analysis based on Lucene. I had to custom-write the search functions to find words within a certain distance of each other. You can import your text documents into the software and have it count the term frequencies, or you can take the code and taylor it to your needs.

Free download:
<a href="http://www.minoesoftware.com/download.php" rel="nofollow">http://www.minoesoftware.com/download.php</a>

Source:
<a href="https://github.com/danspiteri/MINOE/blob/master/src/minoe/SearchFiles.java" rel="nofollow">https://github.com/danspiteri/MINOE/blob/master/src/minoe/SearchFiles.java</a>

blocks|key|825287|text|如果您使用的是Solr4而不是存储文本，则可以在文本字段上使用a+Solr+pivot。但是，很明显，在分析器处理之后，您将获得术语：|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|825288|http://192.168.0.202:8080/solr/fr_00_0425_sem/select?q=renault&wt=xml&facet=true&facet.pivot=uniqueKey,yourText|code-block|syntax|javascript|825289|这是一个相当繁重的查询，我希望您没有太多匹配的文档...|825290|entityMap^0|V|C|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@]|D|@]|E|$]]|$1|M|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|N|$]]

If you are using Solr4 and you are not storing the text, you can use a Solr pivot on the text field. But then, obviously you will get terms after the analyzer processing:

<pre><code>http://192.168.0.202:8080/solr/fr_00_0425_sem/select?q=renault&amp;wt=xml&amp;facet=true&amp;facet.pivot=uniqueKey,yourText
</code></pre>

This is a pretty heavy query, I hope you don't have too many documents that match...

Using <a href="http://wiki.apache.org/solr/TermVectorComponent" rel="noreferrer">http://wiki.apache.org/solr/TermVectorComponent</a> I can get indexed terms and their frequencies for any document stored in my index. How can I get the same information for a text, without storing the text in my index? I just want SOLR to process the text and return the information, but without having to store the document in my index.

SOLR: Create term vector (like data returned from TermVectorComponent) from raw text

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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使用，我可以获得索引中存储的任何文档的索引项及其频率。如何才能在不将文本存储在索引中的情况下为文本获取相同的信息？我只想让SOLR处理文本并返回信息，而不必将文档存储在索引中。

问SOLR:从原始文本创建术语向量(如从TermVectorComponent返回的数据)
EN

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问SOLR:从原始文本创建术语向量(如从TermVectorComponent返回的数据)EN