Hash2Vec: Feature Hashing for Word Embeddings

In this paper we propose the application of feature hashing to create word embeddings for natural language processing. Feature hashing has been used successfully to create document vectors in related tasks like document classification. In this work we show that feature hashing can be applied to obta...

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Detalles Bibliográficos
Autores principales:	Argerich, Luis, Cano, Matías J., Torre Zaffaroni, Joaquín
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2016
Materias:	Ciencias Informáticas feature hashing word embedding Natural Language Processing
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/56977 http://45jaiio.sadio.org.ar/sites/default/files/ASAI-10_0.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-56977
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas feature hashing word embedding Natural Language Processing
spellingShingle	Ciencias Informáticas feature hashing word embedding Natural Language Processing Argerich, Luis Cano, Matías J. Torre Zaffaroni, Joaquín Hash2Vec: Feature Hashing for Word Embeddings
topic_facet	Ciencias Informáticas feature hashing word embedding Natural Language Processing
description	In this paper we propose the application of feature hashing to create word embeddings for natural language processing. Feature hashing has been used successfully to create document vectors in related tasks like document classification. In this work we show that feature hashing can be applied to obtain word embeddings in linear time with the size of the data. The results show that this algorithm, that does not need training, is able to capture the semantic meaning of words.We compare the results against GloVe showing that they are similar. As far as we know this is the first application of feature hashing to the word embeddings problem and the results indicate this is a scalable technique with practical results for NLP applications.
format	Objeto de conferencia Objeto de conferencia
author	Argerich, Luis Cano, Matías J. Torre Zaffaroni, Joaquín
author_facet	Argerich, Luis Cano, Matías J. Torre Zaffaroni, Joaquín
author_sort	Argerich, Luis
title	Hash2Vec: Feature Hashing for Word Embeddings
title_short	Hash2Vec: Feature Hashing for Word Embeddings
title_full	Hash2Vec: Feature Hashing for Word Embeddings
title_fullStr	Hash2Vec: Feature Hashing for Word Embeddings
title_full_unstemmed	Hash2Vec: Feature Hashing for Word Embeddings
title_sort	hash2vec: feature hashing for word embeddings
publishDate	2016
url	http://sedici.unlp.edu.ar/handle/10915/56977 http://45jaiio.sadio.org.ar/sites/default/files/ASAI-10_0.pdf
work_keys_str_mv	AT argerichluis hash2vecfeaturehashingforwordembeddings AT canomatiasj hash2vecfeaturehashingforwordembeddings AT torrezaffaronijoaquin hash2vecfeaturehashingforwordembeddings
bdutipo_str	Repositorios
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Hash2Vec: Feature Hashing for Word Embeddings

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