TY - GEN
T1 - A collective approach to scholar name disambiguation (extended abstract)
AU - Luo, Dongsheng
AU - Ma, Shuai
AU - Yan, Yaowei
AU - Hu, Chunmin
AU - Zhang, Xiang
AU - Huai, Jinpeng
N1 - Funding Information:
ACKNOWLEDGMENTS This work is supported in part by National Key R&D Program of China 2018AAA0102301 and NSFC 61925203 & U1636210. For any correspondence, please refer to Shuai Ma.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - This study investigates name disambiguation for scholarly data. We propose a collective approach, which considers the connections of different ambiguous names, such that it initially treats each author reference as a unique author entity and reformulates the bibliography data as a heterogeneous multipartite network. Disambiguation results of one author name propagate to the others in the network. To further deal with the sparsity problem caused by limited available information, we also introduce word-word and venue-venue similarities and measure author similarities by assembling similarities from multiple perspectives. Using three real-life datasets, we experimentally show that our approach is both effective and efficient.
AB - This study investigates name disambiguation for scholarly data. We propose a collective approach, which considers the connections of different ambiguous names, such that it initially treats each author reference as a unique author entity and reformulates the bibliography data as a heterogeneous multipartite network. Disambiguation results of one author name propagate to the others in the network. To further deal with the sparsity problem caused by limited available information, we also introduce word-word and venue-venue similarities and measure author similarities by assembling similarities from multiple perspectives. Using three real-life datasets, we experimentally show that our approach is both effective and efficient.
UR - http://www.scopus.com/inward/record.url?scp=85112866929&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112866929&partnerID=8YFLogxK
U2 - 10.1109/ICDE51399.2021.00244
DO - 10.1109/ICDE51399.2021.00244
M3 - Conference contribution
AN - SCOPUS:85112866929
T3 - Proceedings - International Conference on Data Engineering
SP - 2317
EP - 2318
BT - Proceedings - 2021 IEEE 37th International Conference on Data Engineering, ICDE 2021
PB - IEEE Computer Society
T2 - 37th IEEE International Conference on Data Engineering, ICDE 2021
Y2 - 19 April 2021 through 22 April 2021
ER -