BibPro: A Citation Parser Based on Sequence Alignment

Abstract

Dramatic increase in the number of academic publications has led to growing demand for efficient organization of the resources to meet researchers' needs. As a result, a number of network services have compiled databases from the public resources scattered over the Internet. However, publications by different conferences and journals adopt different citation styles. It is an interesting problem to accurately extract metadata from a citation string which is formatted in one of thousands of different styles. It has attracted a great deal of attention in research in recent years. In this paper, based on the notion of sequence alignment, we present a citation parser called BibPro that extracts components of a citation string. To demonstrate the efficacy of BibPro, we conducted experiments on three benchmark data sets. The results show that BibPro achieved over 90 percent accuracy on each benchmark. Even with citations and associated metadata retrieved from the web as training data, our experiments show that BibPro still achieves a reasonable performance.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 35 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.