 |
Conference papers
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification
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, out-performing existing frequency-based criteria.
Cited literature [54 references]
https://hal-centralesupelec.archives-ouvertes.fr/hal-01848880
Contributor : Fragkiskos Malliaros <>
Submitted on : Wednesday, July 25, 2018 - 12:02:11 PM
Last modification on : Thursday, July 9, 2020 - 4:06:04 PM
Long-term archiving on: : Friday, October 26, 2018 - 1:32:55 PM
Contributor : Fragkiskos Malliaros <>
Submitted on : Wednesday, July 25, 2018 - 12:02:11 PM
Last modification on : Thursday, July 9, 2020 - 4:06:04 PM
Long-term archiving on: : Friday, October 26, 2018 - 1:32:55 PM
File
fusing-document-collection.pdf
Files produced by the author(s)