Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval

@article{Wang2007TopicalNP,
  title={Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval},
  author={Xuerui Wang and Andrew McCallum and Xing Wei},
  journal={Seventh IEEE International Conference on Data Mining (ICDM 2007)},
  year={2007},
  pages={697-702}
}
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. [] Key Method Successive bigrams form longer phrases. We present experiments showing meaningful phrases and more interpretable topics from the NIPS data and improved information retrieval performance on a TREC collection.

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