HYU Research Team Wins Best Research Paper Award Honorable Mention at KDD 2025 for AI-Based 스포츠토토 베팅샵 Embedding Technology

A research team led by Professor Kim Sang-wook of the Department of Computer Science at Hanyang University has been awarded the “Best Research Paper Award Honorable Mention” at the 31st ACM KDD 2025, the most prestigious international conference in the field of data science. The award recognizes their development of SIGEM, a novel artificial intelligence (AI)-based network embedding technology.

스포츠토토 베팅샵s (graphs) are data structures used to represent complex relationships between objects. 스포츠토토 베팅샵 embedding refers to the process of converting these 스포츠토토 베팅샵s into low-dimensional vectors that are easier for AI models to process. The technology is widely used by global companies such as Meta (Facebook), Amazon, Netflix, and Google in recommendation, search, and personalization services.

However, existing embedding techniques have limitations. They often focus only on local neighbor relationships, failing to capture the overall 스포츠토토 베팅샵 structure. In addition, they struggle to learn from sparsely connected nodes, cannot distinguish directional connections, and are often limited to specific types of 스포츠토토 베팅샵s, restricting both accuracy and generalizability.

To address these challenges, Professor Kim’s team developed SIGEM. This new technique precisely calculates the similarity between all pairs of nodes in a network, faithfully reflecting their relationships in the resulting vector representations. It also incorporates edge directionality into the learning process, preserving the global structure of the network. As a result, SIGEM is highly versatile, applicable to both directed and undirected networks.

The team also proposed a novel similarity calculation method, LINOW, which enables fast and accurate similarity estimation even in large-scale 스포츠토토 베팅샵s, enhancing the practical applicability of their approach to real-world complex 스포츠토토 베팅샵 analysis.

In benchmark tests conducted on eight real-world 스포츠토토 베팅샵s, SIGEM achieved a 102% improvement in link prediction performance and up to a 21% increase in node classification accuracy, outperforming state-of-the-art techniques. Its consistent performance in large and complex 스포츠토토 베팅샵 environments also highlighted its potential for industrial applications.

Professor Kim remarked, “We are honored to receive one of the top three awards out of more than 2,000 submissions at ACM KDD, the leading global conference in data science. This recognition affirms the originality and technological strength of our team.” He added, “SIGEM offers a practical solution for analyzing massive networks in real-world industrial settings.”

This research was supported by the SW StarLab Program and the AI Graduate School Support Program of the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP). The paper, titled “SIGEM: A Simple yet Effective Similarity-based Graph Embedding Method”, lists Research Professor Reyhani Hamedani Masoud as the first author, with researchers Oh Jeong-seok and Cho Sung-woon as the second and third authors, respectively. Professor Kim Sang-wook served as the corresponding author.