%0 Journal Article %1 ge2024optimally %A Ge, Tong %A Luo, Xu %A Wang, Yunhai %A Sedlmair, Michael %A Cheng, Zhanglin %A Zhao, Ying %A Liu, Xin %A Deussen, Oliver %A Chen, Baoquan %D 2024 %I IEEE %J IEEE transactions on visualization and computer graphics %K %N 8 %P 5034-5046 %R 10.1109/TVCG.2023.3284499 %T Optimally Ordered Orthogonal Neighbor Joining Trees for Hierarchical Cluster Analysis %V 30

@article{ge2024optimally, added-at = {2024-12-18T16:59:48.000+0100}, affiliation = {Wang, YH (Corresponding Author), Shandong Univ, Dept Comp Sci, Jinan 250100, Shandong, Peoples R China. Ge, Tong; Luo, Xu; Wang, Yunhai, Shandong Univ, Dept Comp Sci, Jinan 250100, Shandong, Peoples R China. Sedlmair, Michael, Univ Stuttgart, D-70174 Stuttgart, Germany. Cheng, Zhanglin, SIAT, Shenzhen VisuCA Key Lab, Shenzhen 518055, Guangdong, Peoples R China. Zhao, Ying, Cent South Univ, Changsha 410017, Hunan, Peoples R China. Liu, Xin, Beijing Genom Inst BGI Shenzhen, Shenzhen 518083, Guangdong, Peoples R China. Deussen, Oliver, Univ Konstanz, D-78464 Constance, Germany. Chen, Baoquan, Peking Univ, Beijing 100871, Peoples R China.}, author = {Ge, Tong and Luo, Xu and Wang, Yunhai and Sedlmair, Michael and Cheng, Zhanglin and Zhao, Ying and Liu, Xin and Deussen, Oliver and Chen, Baoquan}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2ef7db0f5d8cd3475fcfcb18eb45a1faa/unibiblio}, doi = {10.1109/TVCG.2023.3284499}, interhash = {4cc6bc26a74a1abb896e7bff8aecf88c}, intrahash = {ef7db0f5d8cd3475fcfcb18eb45a1faa}, issn = {{1077-2626} and {1941-0506}}, journal = {IEEE transactions on visualization and computer graphics}, keywords = {}, language = {eng}, number = 8, orcid-numbers = {Liu, Xin/0000-0003-3256-2940 Cheng, Zhanglin/0000-0002-3360-2679 Luo, Xu/0000-0003-1501-7385}, pages = {5034-5046}, publisher = {IEEE}, research-areas = {Computer Science}, researcherid-numbers = {Deussen, Oliver/HKF-2004-2023 Liu, Xin/ABJ-9485-2022}, timestamp = {2024-12-18T15:59:48.000+0100}, title = {Optimally Ordered Orthogonal Neighbor Joining Trees for Hierarchical Cluster Analysis}, unique-id = {WOS:001262914400062}, volume = 30, year = 2024 }