News for hackers. Stuff that matters.

A comment on Item2Vec: Neural Item Embedding for Collaborative Filtering. Parent comment

Re:Item2Vec: Neural Item Embedding for Collaborative Filtering by rahimnathwani on Sunday July 10, 2016 @11:42PM (#12068746)
From the Spotify blog post: "We train a model on subsampled (5%) playlist data using skip-grams and 40 factors."

Any idea what those 40 factors might be?

(The item2vec paper describes using pairs of items that occur in the same set, i.e. just like using n-grams, but without a fixed n, and ignoring ordering.)

[ Parent | on HN ]
Re:Item2Vec: Neural Item Embedding for Collaborative Filtering by rm999 on Monday July 11, 2016 @12:02AM (#12068808)
That's the dimensionality of the resulting word vectors in word2vec; in the item2vec paper this is the "dimension parameter m".
[ Parent | on HN ]