Morphological Word Embeddings

2019-07-04 · Ryan Cotterell, Hinrich Schütze

Linguistic similarity is multi-faceted. For instance, two words may be similar with respect to semantics, syntax, or morphology inter alia. Continuous word-embeddings have been shown to capture most of these shades of similarity to some degree. This work considers guiding word-embeddings with morphologically annotated data, a form of semi-supervised learning, encouraging the vectors to encode a word's morphology, i.e., words close in the embedded space share morphological features. We extend the log-bilinear model to this end and show that indeed our learned embeddings achieve this, using German as a case study.

📄 PDF Abstract BibTeX arXiv:1907.02423

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Tasks

Word Embeddings

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Information Retrieval Retrieval Word Embeddings Word Similarity

A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation

2017-04-24 · Murathan Kurfali, Ahmet Üstün, Burcu Can

In this paper, we introduce a trie-structured Bayesian model for unsupervised morphological segmentation. We adopt prior information from different sources in the model. We use neural word embeddings to discover words th…

Segmentation Word Embeddings

Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings

2017-11-15 · Syed Sarfaraz Akhtar, Arihant Gupta, Avijit Vajpayee, Arjit Srivastava 외

We present a language independent, unsupervised method for building word embeddings using morphological expansion of text. Our model handles the problem of data sparsity and yields improved word embeddings by relying on …

Word Embeddings Word Similarity