arxiv: 1706.05111 · v1 · pith:XCHPCXDBnew · submitted 2017-06-15 · 💻 cs.CL

A Mixture Model for Learning Multi-Sense Word Embeddings

Dai Quoc Nguyen , Dat Quoc Nguyen , Ashutosh Modi , Stefan Thater , Manfred Pinkal This is my paper

classification 💻 cs.CL

keywords wordmodeldifferentembeddingslearningmixturemulti-senseprevious

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Word embeddings are now a standard technique for inducing meaning representations for words. For getting good representations, it is important to take into account different senses of a word. In this paper, we propose a mixture model for learning multi-sense word embeddings. Our model generalizes the previous works in that it allows to induce different weights of different senses of a word. The experimental results show that our model outperforms previous models on standard evaluation tasks.

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A Mixture Model for Learning Multi-Sense Word Embeddings

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