Word Embedding
تضمين الكلمة
تمثيل متجهي كثيف ثابت الأبعاد لكلمة في فضاء متصل، حيث تتقارب الكلمات المتشابهة دلالياً وتتباعد المختلفة. أسّسها بنجيو عام 2003 وأصبحت ركيزة كل نموذج لغوي حديث.
A dense, fixed-dimensional vector representation of a word in a continuous space where semantically similar words are geometrically close. Introduced by Bengio in 2003, it became the foundation of every modern language model.
Also translated asالتمثيل المتجهي للكلمة، المتجه الدلالي للكلمة
First appears in this corpus in: Learning Distributed Representations of Concepts (1986)
Appears in these papers
- Representation Learning with Contrastive Predictive Coding2018in the sky ✦
- Learning Distributed Representations of Concepts1986in the sky ✦
- Enriching Word Vectors with Subword Information2017in the sky ✦
- Enriching Word Vectors with Subword Information2017in the sky ✦
- Gaussian Error Linear Units (GELUs)2016in the sky ✦
- GloVe: Global Vectors for Word Representation2014in the sky ✦
- GloVe: Global Vectors for Word Representation2014in the sky ✦
- ImageBind: One Embedding Space to Bind Them All2023in the sky ✦
- Show and Tell: A Neural Image Caption Generator2015in the sky ✦
- Show and Tell: A Neural Image Caption Generator2015in the sky ✦
- Universal Language Model Fine-Tuning for Text Classification2018in the sky ✦
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction2018in the sky ✦
- Deep Neural Networks for YouTube Recommendations2016in the sky ✦