We are pleased to announce that our Assistant Professor Dr SHI Jieming and his collaborators from Nanyang Technological University, National University of Singapore and Hamad Bin Khalifa University received the 2022 ACM SIGMOD (Special Interest Group on Management of Data) Research Highlight Award, for the paper titled “No PANE, No Gain: Scaling Attributed Network Embedding in a Single Server”. The work was also awarded Best Research Paper Award in VLDB (Very Large Data Bases Conference) in 2021.
This paper addresses the lack of scalability of existing attributed network embedding (ANE) techniques by proposing PANE, an effective and scalable approach for massive graphs in a single server that achieves state-of-the-art result quality on multiple benchmark datasets for two common prediction tasks: link prediction and node classification. Under the hood, PANE takes inspiration from well-established data management techniques to scale up ANE in a single server. Specifically, it exploits a carefully formulated problem based on a novel random walk model, a highly efficient solver, and non-trivial parallelization by utilizing modern multi-core CPUs. Extensive experiments demonstrate that PANE consistently outperforms all existing methods in terms of result quality, while being orders of magnitude faster.
The SIGMOD Research Highlight Award aims to make the selected works widely known in the database community, industry partners as well as the broader ACM community. It is a highly selective and prestigious award that showcases a set of research projects that exemplify core database research.
ACM SIGMOD is concerned with the principles, techniques and applications of database management systems and data management technology. Its members include software developers, academic and industrial researchers, practitioners, users, and students. SIGMOD sponsors the annual SIGMOD/PODS conference, which is one of the most important and selective in the field.
