Papers with neural word embeddings
Lexical Relation Mining in Neural Word Embeddings (2020.coling-main)
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| Challenge: | Conventionally, lexical relations in word vector space have been defined by collections of relatively consistent relationships, or vector offsets, between word-pairs. |
| Approach: | They propose to use Word2Vec space of word-pairs to find lexical relations . they also demonstrate a method for approximating the presence of syntactic and semantic relations based on word vectors extracted from word embeddings. |
| Outcome: | The proposed method outperforms other validated methods in the presence of noisy offsets. |
Constructing High Quality Sense-specific Corpus and Word Embedding via Unsupervised Elimination of Pseudo Multi-sense (L18-1)
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| Challenge: | Existing word embedding frameworks distinguish different senses of words by their contexts. |
| Approach: | They propose a framework for unsupervised corpus sense tagging which trains multi-sense word embeddings on a given corpus. |
| Outcome: | The proposed framework detects pseudo multi-senses without extra language resources without additional language resources. |