Embeddings Evaluation

6 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

A Survey of Word Embeddings Evaluation Methods

avi-jit/SWOW-eval 21 Jan 2018

Word embeddings are real-valued word representations able to capture lexical semantics and trained on natural language corpora.

Expert Concept-Modeling Ground Truth Construction for Word Embeddings Evaluation in Concept-Focused Domains

yoortwijn/quine-ground-truth COLING 2020

We present a novel, domain expert-controlled, replicable procedure for the construction of concept-modeling ground truths with the aim of evaluating the application of word embeddings.

The Limitations of Cross-language Word Embeddings Evaluation

bakarov/cross-lang-embeddings SEMEVAL 2018

The aim of this work is to explore the possible limitations of existing methods of cross-language word embeddings evaluation, addressing the lack of correlation between intrinsic and extrinsic cross-language evaluation methods.

SART - Similarity, Analogies, and Relatedness for Tatar Language: New Benchmark Datasets for Word Embeddings Evaluation

tat-nlp/SART 31 Mar 2019

We evaluate state-of-the-art word embedding models for two languages using our proposed datasets for Tatar and the original datasets for English and report our findings on performance comparison.

Embeddings Evaluation Using a Novel Measure of Semantic Similarity

Crisp-Unimib/TaxoSS Cognitive Computation 2022

Then, we train several embedding models on a text corpus and select the best model, that is, the model that maximizes the correlation between the HSS and the cosine similarity of the pair of words that are in both the taxonomy and the corpus.