Social Text Normalization using Contextual Graph Random Walks

@inproceedings{Hassan2013SocialTN,
  title={Social Text Normalization using Contextual Graph Random Walks},
  author={Hany Hassan and Arul Menezes},
  booktitle={ACL},
  year={2013}
}
We introduce a social media text normalization system that can be deployed as a preprocessing step for Machine Translation and various NLP applications to handle social media text. The proposed system is based on unsupervised learning of the normalization equivalences from unlabeled text. The proposed approach uses Random Walks on a contextual similarity bipartite graph constructed from n-gram sequences on large unlabeled text corpus. We show that the proposed approach has a very high precision… CONTINUE READING
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  • We show that the proposed approach has a very high precision of (92.43) and a reasonable recall of (56.4).

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