blocks|key|1491533|text|您可以将所有分数与最高分数相除，得到0到1之间的分数。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1491534|但是，请注意，归一化分数仅用于比较单个查询的结果。比较两个不同查询结果的分数(归一化或非归一化)是不正确的。|1491535|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

You can divide all scores with the maximum score to get scores between 0 and 1.

However, please note that the normalised scores should be used to compare the results of a single query only. It is not correct to compare the scores (normalised or not) of results from 2 different queries.

blocks|key|1491489|text|使用lucene没有很好的标准化分数的标准方法。阅读：ScoresAsPercentages和这个explanation|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1491490|在您的示例中，如果结果按分数排序，则最高分数是第一个结果的分数。但对于每个其他查询，此分数将是不同的。|1491491|另请参阅how-do-i-normalise-a-solr-lucene-score|1491492|entityMap|0|LINK|mutability|MUTABLE|url|http://wiki.apache.org/lucene-java/ScoresAsPercentages|1|http://article.gmane.org/gmane.comp.jakarta.lucene.user/12076|2|https://stackoverflow.com/questions/3986220/how-do-i-normalise-a-solr-lucene-score^0|R|J|0|1D|B|1|0|0|4|12|2|0^^$0|@$1|2|3|4|5|6|7|T|8|@]|9|@$A|U|B|V|1|W]|$A|X|B|Y|1|Z]]|C|$]]|$1|D|3|E|5|6|7|10|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|11|8|@]|9|@$A|12|B|13|1|14]]|C|$]]|$1|H|3|-4|5|6|7|15|8|@]|9|@]|C|$]]]|I|$J|$5|K|L|M|C|$N|O]]|P|$5|K|L|M|C|$N|Q]]|R|$5|K|L|M|C|$N|S]]]]

There is no good standard way to normalize scores with lucene. Read this: <a href="http://wiki.apache.org/lucene-java/ScoresAsPercentages" rel="nofollow noreferrer">ScoresAsPercentages</a> and this <a href="http://article.gmane.org/gmane.comp.jakarta.lucene.user/12076" rel="nofollow noreferrer">explanation</a>

In your case the highest score is the score of the first result, if the results are sorted by score. But this score will be different for every other query.

See also <a href="https://stackoverflow.com/questions/3986220/how-do-i-normalise-a-solr-lucene-score">how-do-i-normalise-a-solr-lucene-score</a>

blocks|key|3558414|text|Solr没有最高分，它依赖于太多的变量，所以无法预测。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3558415|但是您可以实现不推荐的称为标准化分数(Scores+As+Percentages)的东西。|offset|length|3558416|有关更多详细信息，请参阅相关链接：|3558417|Is+it+possible+to+set+a+Solr+Score+threshold+'reasonably',+independent+of+results+returned?+(i.e.+Is+Solr+Scoring+standardized+in+any+way)|3558418|how+do+I+normalise+a+solr/lucene+score?|3558419|Remove+results+below+a+certain+score+threshold+in+Solr/Lucene?|3558420|entityMap|0|LINK|mutability|MUTABLE|url|http://wiki.apache.org/lucene-java/ScoresAsPercentages|1|https://stackoverflow.com/questions/8237714/is-it-possible-to-set-a-solr-score-threshold-reasonably-independent-of-result|2|https://stackoverflow.com/questions/3986220/how-do-i-normalise-a-solr-lucene-score|3|https://stackoverflow.com/questions/2871558/remove-results-below-a-certain-score-threshold-in-solr-lucene/15765203^0|0|J|L|0|0|0|0|3U|1|0|0|13|2|0|0|1Q|3|0^^$0|@$1|2|3|4|5|6|7|11|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|12|8|@]|9|@$D|13|E|14|1|15]]|A|$]]|$1|F|3|G|5|6|7|16|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|17|8|@]|9|@$D|18|E|19|1|1A]]|A|$]]|$1|J|3|K|5|6|7|1B|8|@]|9|@$D|1C|E|1D|1|1E]]|A|$]]|$1|L|3|M|5|6|7|1F|8|@]|9|@$D|1G|E|1H|1|1I]]|A|$]]|$1|N|3|-4|5|6|7|1J|8|@]|9|@]|A|$]]]|O|$P|$5|Q|R|S|A|$T|U]]|V|$5|Q|R|S|A|$T|W]]|X|$5|Q|R|S|A|$T|Y]]|Z|$5|Q|R|S|A|$T|10]]]]

There is no maximum score in Solr, it depends on too many variables, so it can't be predicted.

But you can implement something called normalized score (<a href="http://wiki.apache.org/lucene-java/ScoresAsPercentages" rel="nofollow noreferrer">Scores As Percentages</a>) which is not recommended.

See related links for more details:

<a href="https://stackoverflow.com/questions/8237714/is-it-possible-to-set-a-solr-score-threshold-reasonably-independent-of-result">Is it possible to set a Solr Score threshold &#39;reasonably&#39;, independent of results returned? (i.e. Is Solr Scoring standardized in any way)</a>

<a href="https://stackoverflow.com/questions/3986220/how-do-i-normalise-a-solr-lucene-score">how do I normalise a solr/lucene score?</a>

<a href="https://stackoverflow.com/questions/2871558/remove-results-below-a-certain-score-threshold-in-solr-lucene/15765203">Remove results below a certain score threshold in Solr/Lucene?</a>

blocks|key|5158232|text|常规归一化只能帮助您比较查询(及其检索到的列表)之间的得分分布。您不能简单地标准化分数来比较查询之间的性能。考虑一个查询，所有检索到的文档都高度相关，并且收到相同的(高分)，而在另一个查询上，检索到的列表包含大麦相关文档(同样，具有相同的分数)-现在，无论您对每个查询进行标准化，归一化的分数都是相同的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5158233|您需要考虑一个可以将所有分数提高到同一水平的交叉查询因子。|5158234|例如，可以计算查询和整个索引之间的相似度，并以某种方式将该分数与文档分数一起使用|5158235|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

A regular normalization will only help you to compare the scoring distribution among queries (and theirs retrieved lists).
You cannot simply normalize the score to compare the performance between queries.
Think of a query which all retrieved documents are highly relevant and received the same (high score), and on another query that the retrieved list comprise barley relevant document (again, with the same score) - now, no matter the per-query normalization you make - the normalized score will be the same.

You need to think on a cross-query factor that can bring all the scores to the same level.

For example - maybe computing similarity between the query and the whole index, and use that score somehow along with the document-score

blocks|key|1491630|text|如果你想比较两个或更多的查询，我找到了一个解决方法。您可以使用LevenstheinDistance或LuceneLevenstheinDistance(Damerau)类将得分最高的文档与查询词进行比较，以获得查询词和结果之间的距离。结果就是它们之间的相似性。对每个要进行比较的查询执行此操作。现在，您有了一个工具，可以使用querytherm和最高结果的相似性来比较您的查询。现在，您可以选择相似度得分最高的查询，并将其用于下一步正确的操作。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|1491631|++++//Damerau+LevenstheinDistance
++++LuceneLevenshteinDistance+d+=+new+LuceneLevenshteinDistance();

++++similiarity+=+d.getDistance(queryterm,+yourResult+);|code-block|syntax|javascript|1491632|entityMap^0|V|J|1F|Z|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|S|8|@]|D|@]|E|$]]]|L|$]]

If you want to compare two or more queries, i found an workaround.
You can compare your highest scored document with your queryterm using the LevenstheinDistance or LuceneLevenstheinDistance(Damerau) class to get the distance between your queryterm and your result. The result is the similiarity between them. Do this for each query you want to compare against. Now you have a tool to compare your queries using the similiarity of your querytherm and your highest result. You can now choose the query with the highest score of similiarity and use this for next proper actions.

<pre><code> //Damerau LevenstheinDistance
 LuceneLevenshteinDistance d = new LuceneLevenshteinDistance();

 similiarity = d.getDistance(queryterm, yourResult );
</code></pre>

blocks|key|3558519|text|我应用了一个非线性函数来压缩每个查询。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3558520|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|$]]

I applied a non-linearity function in order to compress every queries.

I need to normalize the Lucene scores between 0 and 1.

For example, a random query returns the following scores... 

<pre><code>8.864665
2.792687
2.792687
2.792687
2.792687
0.49009037
0.33730242 
0.33730242 
0.33730242 
0.33730242 
</code></pre>

What's the biggest score ? 10.0 ?

thanks

How to normalize Lucene scores?

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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我需要将Lucene分数归一化，介于0和1之间。例如，随机查询返回以下分数...8.8646652.7926872.7926872.7926872.7926870.490090370.33730242 0.33730242 0.33730242 0.33730242 最高分是多少? 10.0？谢谢

问如何将Lucene分数归一化？
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