@InProceedings{skianis-malliaros-vazirgiannis:2018:W18-17,
  author    = {Skianis, Konstantinos  and  Malliaros, Fragkiskos  and  Vazirgiannis, Michalis},
  title     = {Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification},
  booktitle = {Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {49--58},
  abstract  = {Contrary to the traditional Bag-of-Words approach, we consider the Graph-of-Words(GoW) model in which each document is represented by a graph that encodes relationships between the different terms. Based on this formulation, the importance of a term is determined by weighting the corresponding node in the document, collection and label graphs, using node centrality criteria. We also introduce novel graph-based weighting schemes by enriching graphs with word-embedding similarities, in order to reward or penalize semantic relationships. Our methods produce more discriminative feature weights for text categorization, outperforming existing frequency-based criteria.},
  url       = {http://www.aclweb.org/anthology/W18-1707}
}