[1] CHEN M S,HAN J W,YU P S.Data mining:an overview from a database perspective[J].IEEE Transactions on Knowledge and Data Engineering,1996,8(6):866-883.
[2] ESTER M,KRIEGEL H,SANDER J,et al.A density-based algorithm for discovering clusters in large spatial databases with noise[C]//Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining,Portland,Aug 2-4,1996:226-231.
[3] ANKERST M,BREUNIG M M,KRIEGEL H P,et al.OPTICS:ordering points to identify the clustering structure[C]//Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data,Philadelphia,Jun 1-3,1999:49-60.
[4] 金辉,钱雪忠.自然最近邻优化的密度峰值聚类算法[J].计算机科学与探索,2019,13(4):711-720.
JIN H,QIAN X Z.Optimized density peak clustering algorithm by natural nearest neighbor[J].Journal of Frontiers of Computer Science and Technology,2019,13(4):711-720.
[5] 李文杰,闫世强,蒋莹,等.自适应确定DBSCAN算法参数的算法研究[J].计算机工程与应用,2019,55(5):1-7.
LI W J,YAN S Q,JIANG Y,et al.Research on method of self-adaptive determination of DBSCAN algorithm parameters[J].Computer Engineering and Applications,2019,55(5):1-7.
[6] 胡健,朱海湾,毛伊敏.基于自适应蜂群优化的DBSCAN聚类算法[J].计算机工程与应用,2019,55(14):105-114.
HU J,ZHU H W,MAO Y M.DBSCAN clustering algorithm based on adaptive bee colony optimization[J].Computer Engineering and Applications,2019,55(14):105-114.
[7] 王珊,王会举,覃雄派,等.架构大数据:挑战、现状与展望[J].计算机学报,2011,34(10):1741-1752.
WANG S,WANG H J,QIN X P,et al.Architecting big data:challenges,studies and forecasts[J].Chinese Journal of Computers,2011,34(10):1741-1752.
[8] 王万良,张兆娟,高楠,等.基于人工智能技术的大数据分析方法研究进展[J].计算机集成制造系统,2019,25(3):529-547.
WANG W L,ZHANG Z J,GAO N,et al.Progress of big data analytics methods based on artificial intelligence technology[J].Computer Integrated Manufacturing Systems,2019,25(3):529-547.
[9] 宋杰,孙宗哲,毛克明,等.MapReduce大数据处理平台与算法研究进展[J].软件学报,2017,28(3):514-543.
SONG J,SUN Z Z,MAO K M,et al.Research advance on MapReduce based big data processing platforms and algorithms[J].Journal of Software,2017,28(3):514-543.
[10] 胡小强,吴翾,闻立杰,等.基于Spark的并行分布式过程挖掘算法[J].计算机集成制造系统,2019,25(4):791-797.
HU X Q,WU X,WEN L J,et al.Parallel distributed process mining algorithm based on Spark[J].Computer Integrated Manufacturing Systems,2019,25(4):791-797.
[11] WU X D,ZHU X Q,WU G Q,et al.Data mining with big data[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(1):97-107.
[12] ZHANG Y F,CHEN S M,YU G.Efficient distributed density peaks for clustering large data sets in Map-Reduce[J].IEEE Transactions on Knowledge and Data Engineering,2016,28(12):3218-3230.
[13] ALJUMAILY H,LAEFER D F,CUADRA D.Urban point cloud mining based on density clustering and MapReduce[J].Journal of Computing in Civil Engineering,2017,31(5):1-11.
[14] YU Y W,ZHAO J D,WANG X D,et al.Cludoop:an efficient distributed density-based clustering for big data using hadoop[J].International Journal of Distributed Sensor Networks,2015,11:579391.
[15] LI L J,XI Y.Research on clustering algorithm and its parallelization strategy[C]//Proceedings of the 2011 International Conference on Computational and Information Sciences,Chengdu,Oct 21-23,2011.Washington:IEEE Computer Society,2011:325-328.
[16] MAHRAN S,MAHAR K.Using grid for accelerating density-based clustering[C]//IEEE International Conference on Computer and Information Technology,Sydney,Australia,2008:35-40.
[17] 宋董飞,徐华.DBSCAN算法研究及并行化实现[J].计算机工程与应用,2018,54(24):52-56.
SONG D F,XU H.Research and parallelization of DBSCAN algorithm[J].Computer Engineering and Applications,2018,54(24):52-56.
[18] HUANG F,ZHU Q,ZHOU J,et al.Research on the parallelization of the DBSCAN clustering algorithm for spatial data mining based on the Spark platform[J].Remote Sensing,2017,9(12):1301.
[19] 王兴,吴艺,蒋新华,等.大规模数据集下基于DBSCAN算法的增量并行化快速聚类[J].计算机应用与软件,2018,35(4):269-275.
WANG X,WU Y,JIANG X H,et al.Incremental parallelization of fast clustering based on DBSCAN algorithm under largescale data set[J].Computer Applications and Software,2018,35(4):269-275.
[20] DAI B R,LIN I C.Efficient Map/Reduce-based DBSCAN algorithm with optimized data partition[C]//IEEE Fifth International Conference on Cloud Computing,2012:59-66.
[21] 吴翠先,何少元.基于区间数的不确定性数据聚类算法:UD-OPTICS[J].计算机工程与科学,2019,41(7):1303-1311.
WU C X,HE S Y.UD-OPTICS:an uncertain data clustering algorithm based on interval number[J].Computer Engineering & Science,2019,41(7):1303-1311.
[22] XIONG Z Y,CHEN R T,ZHANG Y F,et al.Multi-density DBSCAN algorithm based on density levels partitioning[J].Journal of Information and Computational Science,2012,9(10):2739-2749.
[23] BHARDWAJ S,DASH S K.VDMR-DBSCAN:varied density MapReduce DBSCAN[M]//Big data analytics.[S.l.]:Springer International Publishing,2015:134-150.
[24] HEIDARI S,ALBORZI M,RADFAR R,et al.Big data clustering with varied density based on MapReduce[J].Journal of Big Data,2019,6(1):77.
[25] 曹佳豪,刘宇.基于多叉树和Spark的改进Apriori算法[J].信息技术,2018(6):128-132.
CAO J H,LIU Y.An improved Apriori algorithm based on multi-tree and Spark[J].Information Technology,2018(6):128-132.