@InProceedings{balikas-EtAl:2016:COLING,
  author    = {Balikas, Georgios  and  Amoualian, Hesam  and  Clausel, Marianne  and  Gaussier, Eric  and  Amini, Massih R},
  title     = {Modeling topic dependencies in semantically coherent text spans with copulas},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {1767--1776},
  abstract  = {The exchangeability assumption in topic models like Latent Dirichlet Allocation
	(LDA) often results in inferring inconsistent topics for the words of text
	spans like noun-phrases, which are usually expected to be topically coherent.
	We propose copulaLDA, that extends LDA by integrating  part of the text
	structure to the model and relaxes the conditional independence assumption
	between the word-specific latent topics given the per-document topic
	distributions. To this end, we assume that the words of text spans like
	noun-phrases are topically bound and we model this dependence with copulas. 
	We demonstrate empirically the effectiveness of copulaLDA on both intrinsic and
	extrinsic evaluation tasks on several publicly available corpora.},
  url       = {http://aclweb.org/anthology/C16-1166}
}