Word Similarity

109 papers with code • 0 benchmarks • 2 datasets

Calculate a numerical score for the semantic similarity between two words.


Use these libraries to find Word Similarity models and implementations

Most implemented papers

Efficient Estimation of Word Representations in Vector Space

mindspore-courses/DeepNLP-models-MindSpore 16 Jan 2013

We propose two novel model architectures for computing continuous vector representations of words from very large data sets.

Enriching Word Vectors with Subword Information

facebookresearch/fastText TACL 2017

A vector representation is associated to each character $n$-gram; words being represented as the sum of these representations.

All-but-the-Top: Simple and Effective Postprocessing for Word Representations

lgalke/vec4ir ICLR 2018

The postprocessing is empirically validated on a variety of lexical-level intrinsic tasks (word similarity, concept categorization, word analogy) and sentence-level tasks (semantic textural similarity and { text classification}) on multiple datasets and with a variety of representation methods and hyperparameter choices in multiple languages; in each case, the processed representations are consistently better than the original ones.

How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks

kudkudak/word-embeddings-benchmarks 7 Feb 2017

Maybe the single most important goal of representation learning is making subsequent learning faster.

Calculating the similarity between words and sentences using a lexical database and corpus statistics

nihitsaxena95/sentence-similarity-wordnet-sementic 15 Feb 2018

To calculate the semantic similarity between words and sentences, the proposed method follows an edge-based approach using a lexical database.

Unsupervised Multilingual Word Embeddings

ccsasuke/umwe EMNLP 2018

Multilingual Word Embeddings (MWEs) represent words from multiple languages in a single distributional vector space.

WordRank: Learning Word Embeddings via Robust Ranking

shihaoji/wordrank EMNLP 2016

Then, based on this insight, we propose a novel framework WordRank that efficiently estimates word representations via robust ranking, in which the attention mechanism and robustness to noise are readily achieved via the DCG-like ranking losses.

Definition Modeling: Learning to define word embeddings in natural language

northanapon/dict-definition 1 Dec 2016

Distributed representations of words have been shown to capture lexical semantics, as demonstrated by their effectiveness in word similarity and analogical relation tasks.

Construction of a Japanese Word Similarity Dataset

tmu-nlp/JapaneseWordSimilarityDataset LREC 2018

An evaluation of distributed word representation is generally conducted using a word similarity task and/or a word analogy task.

ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational Knowledge

commonsense/conceptnet-numberbatch SEMEVAL 2017

This paper describes Luminoso's participation in SemEval 2017 Task 2, "Multilingual and Cross-lingual Semantic Word Similarity", with a system based on ConceptNet.