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                 [23]   Ge TZ, He KM, Ke QF, Sun J. Optimized product quantization for approximate nearest neighbor search. In: Proc. of the 2013 IEEE Conf.
                     on Computer Vision and Pattern Recognition. Portland: IEEE, 2013. 2946–2953. [doi: 10.1109/CVPR.2013.379]
                 [24]   Jégou  H,  Douze  M,  Schmid  C.  Product  quantization  for  nearest  neighbor  search.  IEEE  Trans.  on  Pattern  Analysis  and  Machine
                     Intelligence, 2011, 33(1): 117–128. [doi: 10.1109/TPAMI.2010.57]
                 [25]   Wang ZH, Yu DH, Li Q, Shen SG, Yao S. SR-HGN: Semantic- and relation-aware heterogeneous graph neural network. Expert Systems
                     with Applications, 2023, 224: 119982. [doi: 10.1016/j.eswa.2023.119982]
                 [26]   Johnson J, Douze M, Jégou H. Billion-scale similarity search with GPUs. IEEE Trans. on Big Data, 2021, 7(3): 535–547. [doi: 10.1109/
                     TBDATA.2019.2921572]
                 [27]   Feng XK, Peng YG, Cui JT, Liu YF, Li H. Locality sensitive hashing index based on optimal linear order. Chinese Journal of Computers,
                     2020, 43(5): 930–947 (in Chinese with English abstract). [doi: 10.11897/SP.J.1016.2020.00930]
                 [28]   Dasgupta  A,  Kumar  R,  Sarlos  T.  Fast  locality-sensitive  hashing.  In:  Proc.  of  the  17th  ACM  SIGKDD  Int’l  Conf.  on  Knowledge
                     Discovery and Data Mining. San Diego: ACM, 2011. 1073–1081. [doi: 10.1145/2020408.2020578]
                 [29]   Hassantabar S, Wang ZY, Jha NK. SCANN: Synthesis of compact and accurate neural networks. IEEE Trans. on Computer-aided Design
                     of Integrated Circuits and Systems, 2022, 41(9): 3012–3025. [doi: 10.1109/TCAD.2021.3116470]
                 [30]   Cheng A, Chu D, Li T, Chan J, Crooks N, Hellerstein JM, Stoica I, Yu XY. Take out the TraChe: Maximizing (Tra)nsactional Ca(che) hit
                     rate.  In:  Proc.  of  the  17th  USENIX  Symp.  on  Operating  Systems  Design  and  Implementation.  Boston:  USENIX  Association,  2023.
                     419–439.
                 [31]   Ahmed M, Seraj R, Islam SMS. The k-means algorithm: A comprehensive survey and performance evaluation. Electronics, 2020, 9(8):
                     1295. [doi: 10.3390/electronics9081295]
                 [32]   Lei XF, Xie KQ, Lin F, Xia ZY. An efficient clustering algorithm based on local optimality of K-Means. Ruan Jian Xue Bao/Journal of
                     Software, 2008, 19(7): 1683–1692 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/19/1683.htm [doi: 10.3724/SP.J.
                     1001.2008.01683]
                 [33]   Jégou  H,  Douze  M,  Schmid  C.  Searching  with  quantization:  Approximate  nearest  neighbor  search  using  short  codes  and  distance
                     estimators. Technical Report, RR-7020, INRIA, 2009.
                 [34]   Simhadri HV, Williams G, Aumüller M, Douze M, Babenko A, Baranchuk D, Chen Q, Hosseini L, Krishnaswamny R, Srinivasa G,
                     Subramanya SJ, Wang JD. Results of the NeuriPS’21 challenge on billion-scale approximate nearest neighbor search. In: Proc. of the
                     NeurIPS 2021 Competitions and Demonstrations Track. 2022. 177–189.

                 附中文参考文献
                 [27]   冯小康, 彭延国, 崔江涛, 刘英帆, 李辉. 基于最优排序的局部敏感哈希索引. 计算机学报, 2020, 43(5): 930–947. [doi: 10.11897/
                     SP.J.1016.2020.00930]
                 [32]   雷小锋, 谢昆青, 林帆, 夏征义. 一种基于  K-Means 局部最优性的高效聚类算法. 软件学报, 2008, 19(7): 1683–1692. http://www.jos.
                     org.cn/1000-9825/19/1683.htm [doi: 10.3724/SP.J.1001.2008.01683]

                 作者简介
                 周依杰, 博士生, CCF  学生会员, 主要研究领域为向量数据库, 图存储系统.
                 林圣原, 硕士生, CCF  学生会员, 主要研究领域为向量数据库, 图存储系统.
                 巩树凤, 博士, 讲师, 博士生导师, CCF  专业会员, 主要研究领域为向量数据库, 图存储与图计算系统.
                 余松, 博士生, 主要研究领域为向量数据库, 图存储系统.
                 范书豪, 本科生, 主要研究领域为向量数据库.
                 张岩峰, 博士, 教授, 博士生导师, CCF  高级会员, 主要研究领域为数据库, 大数据处理, 分布式系统.
                 于戈, 博士, 教授, 博士生导师, CCF  会士, 主要研究领域为数据库, 分布式系统.
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