International Conference

名取 和玖 君と山下 剛志 君がGRADES-NDA 2026で発表しました。

• Kazuhisa Natori, Tsuyoshi Yamashita, and Kunitake Kaneko, ‘PerPreX: Fast Personalized Graph Summarization by Pre-executed Multi-Level Graph Division’, in Proceedings of the 9th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems and Network Data Analytics (GRADES-NDA), Sep. 2026, doi: 10.1145/3810460.3812777.
• Hiroki Fukuzawa, Tsuyoshi Yamashita, and Kunitake Kaneko, ‘Fast and Accurate Random Walk Index Maintenance for Graph Merging’, in Proceedings of the 9th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems and Network Data Analytics (GRADES-NDA), Sep. 2026, doi: 10.1145/3810460.3812775.

山下 剛志 君と名取 和玖 君がINFOCOM 2026のデモセッションで発表しました。

• Tsuyoshi Yamashita, Kazuhisa Natori and Kunitake Kaneko, “Decoupling information exploration and explanation for personalized recommendation with LLMs,” IEEE Conference on Computer Communications, 2026, pp. 2393-2394, doi: 10.1109/INFOCOM59046.2026.11571497.

山下 剛志 君がMSNDS 2025で発表しました。

• Tsuyoshi Yamashita and Kunitake Kaneko, “Flexible Adjustment of Feature Vector Correlations for Personalized Recommendations”, The International Workshop on Mining and Analyzing Social Networks for Decision Support (MSNDS), Aug 2025.

山下 剛志 君がICUFN 2025で発表しました。

• Kishin Okamatsu, Tsuyoshi Yamashita, and Kunitake Kaneko, “WalkSum: Graph Summarization for Accurate Random Walks”, The 16th International Conference on Ubiquitous and Future Networks (ICUFN), Jul 2025.

山下 剛志 君がIDA 2025で発表しました。

• Tsuyoshi Yamashita and Kunitake Kaneko, “Balancing Global Importance and Source Proximity for Personalized Recommendations Using Random Walk Length”, Advances in Intelligent Data Analysis XXIII (IDA), Lecture Notes in Computer Science, vol 15669, pp.141–153, May 2025, doi: 10.1007/978-3-031-91398-3_11.