/tensor-factorization

Primary LanguageC

Code for Frame-Based Continuous Lexical Semantics through Exponential Family Factorization and Semantic Proto-Roles

Paper

The paper can be found here.

Instructions

TODO: Add instructions on how to generate embeddings based on our n-way tensor factorization.

Important files:

  1. word2vecT.c - our modifications to Cotterel et. al. (2017)'s word2vec3.c tensor factorization code to generate word embeddings

Citation

If make use of our code, please use the following citation:

@InProceedings{ferraro-EtAl:2017:starSEM,
  author    = {Ferraro, Francis  and  Poliak, Adam  and  Cotterell, Ryan  and  Van Durme, Benjamin},
  title     = {Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles},
  booktitle = {Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {97--103},
  abstract  = {We study how different frame annotations complement one another when learning
	continuous lexical semantics. We learn the representations from a tensorized
	skip-gram model that consistently encodes syntactic-semantic content better,
	with multiple 10% gains over baselines.},
  url       = {http://www.aclweb.org/anthology/S17-1011}
}