@article{TACL895,
	author = {Osborne, Dominique  and Narayan, Shashi  and Cohen, Shay },
	title = {Encoding Prior Knowledge with Eigenword Embeddings},
	journal = {Transactions of the Association for Computational Linguistics},
	volume = {4},
	year = {2016},
	keywords = {},
	abstract = {Canonical correlation analysis (CCA) is a method for reducing the dimension of data represented using two views. It has been previously used to derive word embeddings, where one view indicates a word, and the other view indicates its context. We describe a way to incorporate prior knowledge into CCA, give a theoretical justification for it, and test it by deriving word embeddings and evaluating them on a myriad of datasets.},
	issn = {2307-387X},
	url = {https://www.transacl.org/ojs/index.php/tacl/article/view/895},
	pages = {417--430}
}