@article{1152,
  author = {Fayçal rédha Saidani, Idir Rassoul},
  title = {Co-occurrential Analysis for a Selection of Discriminating Features in Opinion Detection},
  journal = {Progress in Computing Applications},
  year = {2013},
  volume = {2},
  number = {1},
  doi = {},
  url = {http://www.dline.info/pca/fulltext/v2n1/2.pdf},
  abstract = {In this article we describe the experience applied to opinions classification with textometric tools. Our objective is to show, in one hand, the contribution of cooccurrentional analysis to the classification of opinions polarity compared to the purely lexical proceeds, and, in the other hand, the manner of mutualizing the advantages of the co-occurrences study and the classification methods based on supervised learning. Relying on a corpus of parliamentary debates issued from the third edition of Text Mining Challenge 2007 we present the results obtained from the characteristics selection according to the textometric analysis.},
}