blocks|key|4216527|text|我认为这个功能没有开箱即用的功能。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4216528|在任何情况下，您都可以考虑使用这种简单的方法|offset|length|style|BOLD|4216529|4216530|为每个感兴趣的单词加载预训练嵌入(availaible+here)|ordered-list-item|4216531|Get+availaible+of+nearest+for每个感兴趣的单词)|4216532|在两个单词的最近邻居中搜索交叉点|4216533|4216534|注意:这是一种粗糙的方法。如果需要，甚至可以使用相似度余弦执行更复杂的操作。|4216535|代码示例：|4216536|import+fasttext

#+load+the+pretrained+model
#+(in+the+example+I+use+the+Italian+model)
model=fasttext.load_model('./ml_models/cc.it.300.bin')

#+get+nearest+neighbors+for+the+interested+words+(100+neighbors)
arancia_nn=model.get_nearest_neighbors('arancia',+k=100)
kiwi_nn=model.get_nearest_neighbors('kiwi',+k=100)

#+get+only+words+sets+(discard+the+similarity+cosine)
arancia_nn_words=set([el[1]+for+el+in+arancia_nn])
kiwi_nn_words=set([el[1]+for+el+in+kiwi_nn])

#+compute+the+intersection
common_similar_words=arancia_nn_words.intersection(kiwi_nn_words)|code-block|syntax|javascript|4216537|输出示例(意大利语)：|4216538|{'agrume',
+'agrumi',
+'ananas',
+'arance',
+'arancie',
+'arancio',
+'avocado',
+'banana',
+'ciliegia',
+'fragola',
+'frutta',
+'lime',
+'limone',
+'limoni',
+'mandarino',
+'mela',
+'mele',
+'melograno',
+'melone',
+'papaia',
+'papaya',
+'pera',
+'pompelmi',
+'pompelmo',
+'renetta',
+'succo'}|4216539|entityMap|0|LINK|mutability|MUTABLE|url|https://fasttext.cc/docs/en/crawl-vectors.html^0|0|K|2|0|0|S|4|0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1B|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1C|8|@$D|1D|E|1E|F|G]]|9|@]|A|$]]|$1|H|3|-4|5|6|7|1F|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|1G|8|@]|9|@$D|1H|E|1I|1|1J]]|A|$]]|$1|L|3|M|5|K|7|1K|8|@]|9|@]|A|$]]|$1|N|3|O|5|K|7|1L|8|@]|9|@]|A|$]]|$1|P|3|-4|5|6|7|1M|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1N|8|@]|9|@]|A|$]]|$1|S|3|T|5|6|7|1O|8|@]|9|@]|A|$]]|$1|U|3|V|5|W|7|1P|8|@]|9|@]|A|$X|Y]]|$1|Z|3|10|5|6|7|1Q|8|@]|9|@]|A|$]]|$1|11|3|12|5|W|7|1R|8|@]|9|@]|A|$X|Y]]|$1|13|3|-4|5|6|7|1S|8|@]|9|@]|A|$]]]|14|$15|$5|16|17|18|A|$19|1A]]]]

I think that there isn't out of the box function for this feature.
In any case, you can think about this simple approach:
<ol>
<li>Load a pretrained embedding (availaible <a href="https://fasttext.cc/docs/en/crawl-vectors.html" rel="nofollow noreferrer">here</a>)</li>
<li>Get a decent amount of nearest neighbors for every interested word</li>
<li>Search for intersections in the nearest neighbors of the two words</li>
</ol>
A small note: this is a crude approach. If necessary, even more sophisticated operations can be performed using the similarity cosine.
Code example:
<pre><code>import fasttext

# load the pretrained model
# (in the example I use the Italian model)
model=fasttext.load_model('./ml_models/cc.it.300.bin')

# get nearest neighbors for the interested words (100 neighbors)
arancia_nn=model.get_nearest_neighbors('arancia', k=100)
kiwi_nn=model.get_nearest_neighbors('kiwi', k=100)

# get only words sets (discard the similarity cosine)
arancia_nn_words=set([el[1] for el in arancia_nn])
kiwi_nn_words=set([el[1] for el in kiwi_nn])

# compute the intersection
common_similar_words=arancia_nn_words.intersection(kiwi_nn_words)
</code></pre>
Example output (in Italian):
<pre><code>{'agrume',
 'agrumi',
 'ananas',
 'arance',
 'arancie',
 'arancio',
 'avocado',
 'banana',
 'ciliegia',
 'fragola',
 'frutta',
 'lime',
 'limone',
 'limoni',
 'mandarino',
 'mela',
 'mele',
 'melograno',
 'melone',
 'papaia',
 'papaya',
 'pera',
 'pompelmi',
 'pompelmo',
 'renetta',
 'succo'}
</code></pre>

blocks|key|5020135|text|多年来，我一直使用Gensim的W2V实现进行这样的计算，但Gensim也有FastText实现：https://radimrehurek.com/gensim/models/fasttext.html|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|5020136|entityMap|0|LINK|mutability|MUTABLE|url|https://radimrehurek.com/gensim/models/fasttext.html^0|1D|1G|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]]]]

I have used the Gensim W2V implementation for such computations for years now, but Gensim has also FastText implementation: <a href="https://radimrehurek.com/gensim/models/fasttext.html" rel="nofollow noreferrer">https://radimrehurek.com/gensim/models/fasttext.html</a>

I am trying to find words that are similar to two different words. I know that I can find the most similar word with FastText but I was wondering if there is a way to find a keyword that is similar to two keywords. For example, &quot;apple&quot; is similar to &quot;orange&quot; and also similar to &quot;kiwi&quot;. So, what I want to do is if I have two words, &quot;organ&quot; and &quot;kiwi&quot;, then I would like to get a suggestion of the keyword &quot;apple&quot; or any other fruits. Is there a way to do this?

How to find word that are similar to two keywords using FastText?

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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我正在尝试寻找与两个不同的单词相似的单词。我知道我可以用FastText找到最相似的单词，但我想知道是否有一种方法可以找到与两个关键词相似的关键词。例如，"apple“类似于"orange”，也类似于"kiwi“。所以，我想要做的是，如果我有两个词，“器官”和“奇异果”，那么我希望得到一个关键字“苹果”或任何其他水果的...

问如何使用FastText查找与两个关键字相似的单词？
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问如何使用FastText查找与两个关键字相似的单词？EN