Metadata-Version: 2.1
Name: wikipedia2vec
Version: 1.0.1
Summary: A tool for learning vector representations of words and entities from Wikipedia
Home-page: http://wikipedia2vec.github.io/
Author: Studio Ousia
Author-email: ikuya@ousia.jp
License: UNKNOWN
Description: Wikipedia2Vec
        =============
        
        [![Fury badge](https://badge.fury.io/py/wikipedia2vec.png)](http://badge.fury.io/py/wikipedia2vec)
        [![CircleCI](https://circleci.com/gh/wikipedia2vec/wikipedia2vec.svg?style=svg)](https://circleci.com/gh/wikipedia2vec/wikipedia2vec)
        
        Wikipedia2Vec is a tool used for obtaining embeddings (vector representations) of words and entities from Wikipedia.
        It is developed and maintained by [Studio Ousia](http://www.ousia.jp).
        
        This tool enables you to learn embeddings of words and entities simultaneously, and places similar words and entities close to one another in a continuous vector space.
        Embeddings can be easily trained by a single command with a publicly available Wikipedia dump as input.
        This tool has been used in several state-of-the-art NLP models such as [entity linking](https://arxiv.org/abs/1601.01343), [named entity recognition](http://www.aclweb.org/anthology/I17-2017), [entity relatedness](https://arxiv.org/abs/1601.01343), and [question answering](https://arxiv.org/abs/1803.08652).
        
        Documentation and pretrained embeddings are available online at [http://wikipedia2vec.github.io/](http://wikipedia2vec.github.io/).
        
        Reference
        ---------
        
        If you use Wikipedia2Vec in a scientific publication, please cite the following paper:
        
        Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, [Wikipedia2Vec: An Optimized Implementation for Learning Embeddings from Wikipedia](https://arxiv.org/abs/1812.06280).
        
        ```text
        @article{yamada2018wikipedia2vec,
          title={Wikipedia2Vec: An Optimized Implementation for Learning Embeddings from Wikipedia},
          author={Yamada, Ikuya and Asai, Akari and Shindo, Hiroyuki and Takeda, Hideaki and Takefuji, Yoshiyasu},
          journal={arXiv preprint 1812.06280},
          year={2018}
        }
        ```
        
        License
        -------
        
        [Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0)
        
Keywords: wikipedia,embedding,wikipedia2vec
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
