I'm working with Euclidian Distance with Neo4J, and have come across what appears to be an error or challenge in the docs and hoping someone can shed some light on it.
See NEO4J documentation here: https://neo4j.com/docs/graph-algorithms/current/labs-algorithms/euclidean/
According to the documentation, the lower the similarity score, the MORE similar the items "a score of 0 would indicate that users have exactly the same preferences".
However, when I look closely at their examples, they say that "Zhen" and "Arya" with a similarity score of 0 are the closest in similarity. But when I look at their food rating scores, neither "Zhen" or "Arya" have rated the same food types, they have nothing in common. However, "Praveena" to "Arya" with a similarity score of 8.0 actually both rated (Portugese - 7) and they both at least rated (Mauritian).
Here, it seems as though the HIGHER the score, the MORE similar the users. Any thoughts on if this is just a mistake in the documentation or if I've missed something?