From Word Embeddings To Document Distances
From Word Embeddings To
Document Distances
Matt J. Kusner
Yu Sun
Nicholas I. Kolkin
Kilian Q. Weinberger
Goal: a distance between
two documents
?
Applications
document classification multi-lingual document matching
song identification
Word Embedding
word2vec
[Mikolov et al., 2013]
different from
[Collobert & Weston, 2008]
[Mnih & Hinton, 2009]
word2vec is not deep!
trained on 100
billion words
words
3 million different
words embedded
R
d
Word Embedding
word2vec
[Mikolov et al., 2013]
xi
xj
X2R
d?n
distance between
words i and j:
words
kxi
xj k2
is roughly their
dissimilarity
R
d
................
................
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