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Based on the vector values of two words in word2vec, could we judge whether they co-occur and frequencies of coocurrence?

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Let the two words be $a,b$ and let $u_a,v_b$ be the respective in/out representation vectors of each word (usually word2vec retains only the in representation, but both are needed for training). Then the probability of co-occurance within the training window size should be:

$$\frac{\exp(u_a\cdot v_b)}{\sum_i \exp(u_a\cdot v_i)}$$,

Where the sum is over your vocabulary.

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  • $\begingroup$ Thanks, but what I mean is two in representation of two distinct words, does the usage of vector similarity measure like consine similarity helps in determine the concurrence of two words? $\endgroup$
    – william007
    Jul 4, 2019 at 5:30
  • $\begingroup$ @william007: No. it doesn’t make sense to measure co-occurrence with the same representation. Words are similar if they are used in similar contexts, but that doesn’t imply they co-occur $\endgroup$
    – Alex R.
    Jul 4, 2019 at 6:38

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