NLP and Content Server : Word vectors
A similarity between two texts is determined using Word vectors from the natural Language Processing part of AI. This can also be used to determine whether texts are equal or unequal. This is done by the comparism of the word vectors. Word vectors generally look like this as a simplified example:
In this table, each dimension has a clearly defined meaning. For example, if the first dimension represents the meaning of the word “animal,” then each numerical value represents how closely the line relates to “animal.”
Similar words are drawn in vector space. What is interesting is how close “cat” and “dog” are to the term “pet”, how close “elephant”, “lion”, “tiger” are and how descriptive words (“wild”, “zoo”, “domesticated”) are. appear in groups. Word vectors are available in every language depenmding on the pretrained models.
Funny: You can add two word vektors. By adding “German + airlines” you get Lufthansa