TY - GEN
T1 - Bridging Text Data and Graph Data
T2 - 17th ACM International Conference on Web Search and Data Mining, WSDM 2024
AU - Jin, Bowen
AU - Zhang, Yu
AU - Li, Sha
AU - Han, Jiawei
N1 - Research was supported in part by US DARPA KAIROS Program No. FA8750-19-2-1004 and INCAS Program No. HR001121C0165, National Science Foundation IIS-19-56151, IIS-17-41317, and IIS 17-04532
PY - 2024/3/4
Y1 - 2024/3/4
N2 - Graphs and texts are two key modalities in data mining. In many cases, the data presents a mixture of the two modalities and the information is often complementary: in e-commerce data, the product-user graph and product descriptions capture different aspects of product features; in scientific literature, the citation graph, author metadata, and the paper content all contribute to modeling the paper impact.
AB - Graphs and texts are two key modalities in data mining. In many cases, the data presents a mixture of the two modalities and the information is often complementary: in e-commerce data, the product-user graph and product descriptions capture different aspects of product features; in scientific literature, the citation graph, author metadata, and the paper content all contribute to modeling the paper impact.
KW - graph mining
KW - pretrained language model
UR - http://www.scopus.com/inward/record.url?scp=85191699293&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85191699293&partnerID=8YFLogxK
U2 - 10.1145/3616855.3636450
DO - 10.1145/3616855.3636450
M3 - Conference contribution
AN - SCOPUS:85191699293
T3 - WSDM 2024 - Proceedings of the 17th ACM International Conference on Web Search and Data Mining
SP - 1122
EP - 1125
BT - WSDM 2024 - Proceedings of the 17th ACM International Conference on Web Search and Data Mining
PB - Association for Computing Machinery
Y2 - 4 March 2024 through 8 March 2024
ER -