Name
Title | ||
|---|---|---|
Wikipedia2Vec: An Optimized Tool for Learning Embeddings of Words and Entities from Wikipedia. |
Abstract | ||
|---|---|---|
We present Wikipedia2Vec, an open source tool for learning embeddings of words and entities from Wikipedia. This tool enables users to easily obtain high-quality embeddings of words and entities from a Wikipedia dump with a single command. The learned embeddings can be used as features in downstream natural language processing (NLP) models. The tool can be installed via PyPI. The source code, documentation, and pretrained embeddings for 12 major languages can be obtained at this http URL. |
Year | Venue | DocType |
|---|---|---|
2018 | arXiv: Computation and Language | Journal |
Volume | Citations | PageRank |
abs/1812.06280 | 2 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ikuya Yamada | 1 | 65 | 8.25 |
| Akari Asai | 2 | 9 | 4.28 |
| Hiroyuki Shindo | 3 | 75 | 13.80 |
| Hideaki Takeda | 4 | 179 | 25.16 |
| Yoshiyasu Takefuji | 5 | 262 | 33.68 |