2020 Fiscal Year Annual Research Report
Bipartite Graph Embedding: As A Unified Framework
| Project/Area Number |
19K20352
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
劉 欣 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 主任研究員 (20803935)
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| Project Period (FY) |
2019-04-01 – 2021-03-31
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| Keywords | Graph Embedding / Graph Neural Network / Node Classification / Node Ranking / Bipartite Graph / Knowledge Graph |
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| Outline of Annual Research Achievements |
We have proposed new graph embedding approaches for 1) graphs containing missing features; 2) temporal knowledge graphs; 3) attributed graphs; 4) node ranking. Moreover, we applied graph embedding techniques for a real-world application of forecasting regional ambulance demand. In total, we have published seven papers, including two papers in top international conferences (CIKM2020, ICDE2021), two papers in top journals (ACM TKDD, FGCS), and another three papers in journals with impact factor (IEEE Access, Sensors, Computing).
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