Representation learning for very short texts using weighted word embedding aggregation
- Author
- Cedric De Boom (UGent) , Steven Van Canneyt (UGent) , Thomas Demeester (UGent) and Bart Dhoedt (UGent)
- Organization
- Keywords
- IBCN, Natural language processing, Information storage and retrieval, Artificial intelligence, Word embeddings, Representation learning
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8023857
- MLA
- De Boom, Cedric, et al. “Representation Learning for Very Short Texts Using Weighted Word Embedding Aggregation.” PATTERN RECOGNITION LETTERS, vol. 80, Elsevier, 2016, pp. 150–56, doi:10.1016/j.patrec.2016.06.012.
- APA
- De Boom, C., Van Canneyt, S., Demeester, T., & Dhoedt, B. (2016). Representation learning for very short texts using weighted word embedding aggregation. PATTERN RECOGNITION LETTERS, 80, 150–156. https://doi.org/10.1016/j.patrec.2016.06.012
- Chicago author-date
- De Boom, Cedric, Steven Van Canneyt, Thomas Demeester, and Bart Dhoedt. 2016. “Representation Learning for Very Short Texts Using Weighted Word Embedding Aggregation.” PATTERN RECOGNITION LETTERS 80: 150–56. https://doi.org/10.1016/j.patrec.2016.06.012.
- Chicago author-date (all authors)
- De Boom, Cedric, Steven Van Canneyt, Thomas Demeester, and Bart Dhoedt. 2016. “Representation Learning for Very Short Texts Using Weighted Word Embedding Aggregation.” PATTERN RECOGNITION LETTERS 80: 150–156. doi:10.1016/j.patrec.2016.06.012.
- Vancouver
- 1.De Boom C, Van Canneyt S, Demeester T, Dhoedt B. Representation learning for very short texts using weighted word embedding aggregation. PATTERN RECOGNITION LETTERS. 2016;80:150–6.
- IEEE
- [1]C. De Boom, S. Van Canneyt, T. Demeester, and B. Dhoedt, “Representation learning for very short texts using weighted word embedding aggregation,” PATTERN RECOGNITION LETTERS, vol. 80, pp. 150–156, 2016.
@article{8023857,
author = {{De Boom, Cedric and Van Canneyt, Steven and Demeester, Thomas and Dhoedt, Bart}},
issn = {{0167-8655}},
journal = {{PATTERN RECOGNITION LETTERS}},
keywords = {{IBCN,Natural language processing,Information storage and retrieval,Artificial intelligence,Word embeddings,Representation learning}},
language = {{eng}},
pages = {{150--156}},
publisher = {{Elsevier}},
title = {{Representation learning for very short texts using weighted word embedding aggregation}},
url = {{http://dx.doi.org/10.1016/j.patrec.2016.06.012}},
volume = {{80}},
year = {{2016}},
}
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