Extremely simple and fast word2vec implementation with Negative Sampling + Sub-sampling

Implementing Facebook's FastText with java

Using pre trained word embeddings (Fasttext, Word2Vec)

Dict2vec is a framework to learn word embeddings using lexical dictionaries.

Web服务：使用腾讯 800 万词向量模型和 spotify annoy 引擎得到相似关键词

Cross-Lingual Alignment of Contextual Word Embeddings

Storage and retrieval of Word Embeddings in various databases

基于知识库信息的词向量模型

PyTorch implementation of the Word2Vec (Skip-Gram Model) and visualizing the trained embeddings using TSNE

This repository contains source code to binarize any real-value word embeddings into binary vectors.

Dutch word embeddings, trained on a large collection of Dutch social media messages and news/blog/forum posts.

Aspect-Based Sentiment Analysis

Extending conceptual thinking with semantic embeddings.

Repository for the experiments described in the paper named "DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus"

TwitPersonality: Computing Personality Traits from Tweets using Word Embeddings and Supervised Learning

flairR: Bring Amazing Flair NLP to R

📖 📚 📰 Workshop that demonstrates using and analyzing text in R.

Improving Word Embeddings by combining word embeddings with their POS (Part Of Speech) tag.

RiverText is a framework that standardizes the Incremental Word Embeddings proposed in the state-of-art. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!