@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://transacl.org/ojs/index.php/tacl/article/view/895},
pages = {417--430}