Content-Based Citation Recommendation
Table 5: Results of our BM25 implementation on DBLP and Pubmed datasets.
['[BOLD] BM25 Implementation', '[BOLD] DBLP F@20', '[BOLD] DBLP MRR', '[BOLD] PubMed F@20', '[BOLD] PubMed MRR']
Okapi-BM25 is a popular ranking function. We use BM25 as an IR-based baseline for the task of citation recommendation. For the DBLP and Pubmed datasets, BM25 performance is provided in Ren et al. To create a competitive BM25 baseline for OpenCorpus, we first created indexes for the DBLP and Pubmed datasets and tuned the query to approximate the performance reported in previous work. We extract the key terms (using Whoosh’s key_terms_from_text method) from the title and abstract of each query document. The key terms from the document are concatenated to form the query string.