Content-Based Citation Recommendation

@inproceedings{Bhagavatula2018ContentBasedCR,
  title={Content-Based Citation Recommendation},
  author={Chandra Bhagavatula and Sergey Feldman and Russell Power and Waleed Ammar},
  booktitle={NAACL-HLT},
  year={2018}
}
We present a content-based method for recommending citations in an academic paper draft. We embed a given query document into a vector space, then use its nearest neighbors as candidates, and rerank the candidates using a discriminative model trained to distinguish between observed and unobserved citations. Unlike previous work, our method does not require metadata such as author names which can be missing, e.g., during the peer review process. Without using metadata, our method outperforms the… CONTINUE READING
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Key Quantitative Results

  • Without using metadata, our method outperforms the best reported results on PubMed and DBLP datasets with relative improvements of over 18% in F1@20 and over 22% in MRR.

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