linguistic regularities in sparse and explicit word representations
DESCRIPTION
Linguistic Regularities in Sparse and Explicit Word Representations. Omer Levy Yoav Goldberg Bar- Ilan University Israel. Papers in ACL 2014*. * Sampling error: +/- 100%. Neural Embeddings. Representing words as vectors is not new!. Explicit Representations (Distributional). - PowerPoint PPT PresentationTRANSCRIPT
Linguistic Regularities in Sparse and Explicit
Word Representations
Omer Levy Yoav GoldbergBar-Ilan University
Israel
Papers in ACL 2014*
Neural Networks &
Word Embeddings
Other Topics
* Sampling error: +/- 100%
Neural Embeddings
•
Representing words as vectors is not new!
Explicit Representations (Distributional)•
Questions
• Are analogies unique to neural embeddings?Compare neural embeddings with explicit representations
• Why does vector arithmetic reveal analogies?Unravel the mystery behind neural embeddings and their “magic”
Background
Mikolov et al. (2013a,b,c)
• Neural embeddings have interesting geometries
Mikolov et al. (2013a,b,c)
• Neural embeddings have interesting geometries
• These patterns capture “relational similarities”
• Can be used to solve analogies:man is to woman as king is to queen
Mikolov et al. (2013a,b,c)
•
Mikolov et al. (2013a,b,c)
•
Mikolov et al. (2013a,b,c)
Mikolov et al. (2013a,b,c)
Mikolov et al. (2013a,b,c)
Mikolov et al. (2013a,b,c)
Mikolov et al. (2013a,b,c)
Mikolov et al. (2013a,b,c)
Are analogies unique to neural embeddings?
• Experiment: compare embeddings to explicit representations
Are analogies unique to neural embeddings?
Are analogies unique to neural embeddings?• Experiment: compare embeddings to explicit representations
Are analogies unique to neural embeddings?• Experiment: compare embeddings to explicit representations
• Learn different representations from the same corpus:
Are analogies unique to neural embeddings?•
Analogy Datasets
•
Embedding vs Explicit (Round 1)
Embedding vs Explicit (Round 1)
MSR Google0%
10%
20%
30%
40%
50%
60%
70%
Embedding54%
Embedding63%
Explicit29%
Explicit45%
Accu
racy
Many analogies recovered by explicit, but many more by embedding.
Why does vector arithmetic reveal analogies?
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
Why does vector arithmetic reveal analogies?•
royal? female?
What does each similarity term mean?• Observe the joint features with explicit representations!
uncrowned Elizabethmajesty Katherinesecond impregnate
… …
Can we do better?
Let’s look at some mistakes…
Let’s look at some mistakes…
Let’s look at some mistakes…
Let’s look at some mistakes…
The Additive Objective
•
The Additive Objective
•
The Additive Objective
•
The Additive Objective
•
The Additive Objective
•
The Additive Objective
•
• Problem: one similarity might dominate the rest• Much more prevalent in explicit representation• Might explain why explicit underperformed
How can we do better?
How can we do better?
• Instead of adding similarities, multiply them!
How can we do better?
•
How can we do better?
•
Embedding vs Explicit (Round 2)
Multiplication > Addition
MSR Google MSR GoogleEmbedding Explicit
0%
10%
20%
30%
40%
50%
60%
70%
80%
Add54%
Add63%
Add29%
Add45%
Mul59%
Mul67% Mul
57%
Mul68%Ac
cura
cy
Explicit is on-par with Embedding
MSR Google0%
10%
20%
30%
40%
50%
60%
70%
80%
Embedding59%
Embedding67%Explicit
57%
Explicit68%Ac
cura
cy
Explicit is on-par with Embedding
• Embeddings are not “magical”
• Embedding-based similarities have a more uniform distribution
• The additive objective performs better on smoother distributions
• The multiplicative objective overcomes this issue
Conclusion
• Are analogies unique to neural embeddings?No! They occur in sparse and explicit representations as well.
• Why does vector arithmetic reveal analogies?Because vector arithmetic is equivalent to similarity arithmetic.
• Can we do better?Yes! The multiplicative objective is significantly better.
More Results and Analyses (in the paper)• Evaluation on closed-vocabulary analogy questions (SemEval 2012)
• Experiments with a third objective function (PairDirection)
• Do different representations reveal the same analogies?
• Error analysis
• A feature-level interpretation of how word similarity reveals analogies
