<p>As <a href="https://en.wikipedia.org/wiki/Similarity_measure" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Similarity_measure</a> states:</p>

<blockquote>
  <p><a href="https://en.wikipedia.org/wiki/Cosine_similarity" rel="nofollow noreferrer">Cosine similarity</a> is a commonly used similarity measure for real-valued vectors, used in (among other fields) information retrieval to score the similarity of documents in the vector space model. In machine learning, common kernel functions such as the RBF kernel can be viewed as similarity functions</p>
</blockquote>

<p>Also see: <a href="https://en.wikipedia.org/wiki/Congruence_coefficient" rel="nofollow noreferrer">Congruence coefficient</a></p>

<p>Other measures: <a href="https://en.wikipedia.org/wiki/Euclidean_distance" rel="nofollow noreferrer">Euclidean distance</a></p>

CC BY-SA 4.0
2020-03-01T23:52:25.917Z
2020-03-01T23:52:25.917Z
simsi
<p>Say there is a group of OCEAN profiles. How do I calculate how well another profile fits into this group of profiles?</p>

<p>Is <a href="https://en.wikipedia.org/wiki/Congruence_coefficient" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Congruence_coefficient</a> the way to go or are there alternatives?</p>

CC BY-SA 4.0
2020-03-01T15:39:49.557Z
Another measure could be cosine similarity: https://en.wikipedia.org/wiki/Cosine_similarity
simsi
<personality><big-five>
What measures are available for calculating big 5 congruence with a collection of profiles?
simsi
# What measures are available for calculating big 5 congruence with a collection of profiles?

(Asked by: username_0 on 2020-02-22)

Say there is a group of OCEAN profiles. How do I calculate how well another profile fits into this group of profiles?

Is <https://en.wikipedia.org/wiki/Congruence_coefficient> the way to go or are there alternatives?

**Tags:** personality, big-five

> **Comments:**
> **username_0**: Another measure could be cosine similarity: https://en.wikipedia.org/wiki/Cosine_similarity  

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## 1 answers

### Answer by username_0 on 2020-03-01. Score: 1 | Accepted answer

As <https://en.wikipedia.org/wiki/Similarity_measure> states:

> [Cosine similarity](https://en.wikipedia.org/wiki/Cosine_similarity) is a commonly used similarity measure for real-valued vectors, used in (among other fields) information retrieval to score the similarity of documents in the vector space model. In machine learning, common kernel functions such as the RBF kernel can be viewed as similarity functions

Also see: [Congruence coefficient](https://en.wikipedia.org/wiki/Congruence_coefficient)

Other measures: [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)


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