TY - GEN
T1 - PGB
T2 - 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023
AU - Lee, Eric W.
AU - Ho, Joyce C.
N1 - Publisher Copyright:
© 2023 Copyright held by the owner/author(s).
PY - 2023/10/21
Y1 - 2023/10/21
N2 - There has been rapid growth in biomedical literature, yet capturing the heterogeneity of the bibliographic information of these articles remains relatively understudied. Graph neural networks have gained popularity, however, they may not fully capture the information available in the PubMed database, a biomedical literature repository containing over 33 million articles. We introduce PubMed Graph Benchmark (PGB), a new benchmark dataset for evaluating heterogeneous graph representations. PGB is one of the largest heterogeneous networks to date and aggregates the rich metadata into a unified source including abstract, authors, citations, keywords, and the associated keyword hierarchy. The benchmark contains an evaluation task of 21 systematic review topics, an essential knowledge translation tool.
AB - There has been rapid growth in biomedical literature, yet capturing the heterogeneity of the bibliographic information of these articles remains relatively understudied. Graph neural networks have gained popularity, however, they may not fully capture the information available in the PubMed database, a biomedical literature repository containing over 33 million articles. We introduce PubMed Graph Benchmark (PGB), a new benchmark dataset for evaluating heterogeneous graph representations. PGB is one of the largest heterogeneous networks to date and aggregates the rich metadata into a unified source including abstract, authors, citations, keywords, and the associated keyword hierarchy. The benchmark contains an evaluation task of 21 systematic review topics, an essential knowledge translation tool.
KW - Heterogeneous Information Network
KW - Network Embedding
KW - PubMed Benchmark
KW - Systematic Review
UR - http://www.scopus.com/inward/record.url?scp=85178096814&partnerID=8YFLogxK
U2 - 10.1145/3583780.3615128
DO - 10.1145/3583780.3615128
M3 - Conference contribution
AN - SCOPUS:85178096814
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 5331
EP - 5335
BT - CIKM 2023 - Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
PB - Association for Computing Machinery
Y2 - 21 October 2023 through 25 October 2023
ER -