Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 1-11.
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LI Guang-pu, HUANG Miao-hua
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| [1]AGRAWAL R,SRIKANT R.Fast Algorithms for Mining Association Rules in Large Databases[C]∥International Con-ference on Very Large Data Bases.Morgan Kaufmann Publi-shers Inc.,1994:487-499. [2]ZAKI M J.CHARM:An Efficient Algorithm for Closed Itemset Mining[C]∥Siam International Conference on Data Mining.2002:457-473. [3]BAYARDO R J.Efficiently mining long patterns from databases[C]∥ACM SIGMOD International Conference on Management of Data.ACM,1998:85-93. [4]陈慧萍,王建东,王煜.频繁项集挖掘的研究与进展[J].计算机仿真,2006,23(4):68-73. [5]AGARWAL R C,AGGARWAL C C,PRASAD V V V.A Tree Projection Algorithm for Generation of Frequent Item Sets[M].Academic Press,2000. [6]HAN J,PEI J,YIN Y.Mining frequent patterns without candidate generation[C]∥Acm Sigmod International Conference on Management of Data.2000:1-12. [7]EL-HAJJ M.Inverted matrix:efficient discovery of frequent items in large datasets in the context of interactive mining[C]∥Acm Sigkdd International Conference on Knowledge Discovery &Data Mining.National Acad Sciences,2003:109-118. [8]GATUHA G,JIANG T.Smart frequent itemsets mining algorithm based on FP-tree and DIFFset data structures[J].Turkish Journal of Electrical Engineering & Computer Sciences,2017,25:2096-2107. [9]ZAKI M J.Scalable Algorithms for Association Mining[M].IEEE Educational Activities Department,2000:372-390. [10]蓝祺花,吴博.频繁项集挖掘算法研究[J].计算机与现代化,2009,2009(3):60-65. [11]PARK J S,CHEN M S,YU P S.An effective hash-based algorithm for mining association rules[J].ACM SIGMOD Record,1995,24(2):175-186. [12]SAVASERE A,OMIECINSKI E,NAVATHE S B.An Efficient Algorithm for Mining Association Rules in Large Databases[C]∥International Conference on Very Large Data Bases.Morgan Kaufmann Publishers Inc.,1995:432-444. [13]陈波,董鹏,邵勇.基于Apriori算法及其改进算法综述[C]∥中国通信学会第五届学术年会.2008. [14]TOIVONEN H.Sampling Large Databases for Association Rules[C]∥International Conference on Very Large Data Bases.Morgan Kaufmann Publishers Inc.,1996:134-145. [15]BRIN S,MOTWANI R,ULLMAN J D,et al.Dynamic itemset counting and implication rules for market basket data[C]∥Acm Sigmod International Conference on Management of Data.ACM,1997:255-264. [16]CHEUNG D W,HAN J,NG V T,et al.Maintenance of disco-vered association rules in large databases:an incremental updating technique[C]∥Twelfth International Conference on Data Engineering.IEEE,1996:106-114. [17]CHEUNG W L,LEE S D,KAO B.A General Incremental Technique for Maintaining Discovered Association Rules[C]∥International Conference on Database Systems for Advanced Applications.World Scientific Press,1997:185-194. [18]THOMAS S,BODAGALA S,ALSABTI K,et al.An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases[C]∥KDD.1997:263-266. [19]PARK J S,CHEN M S,YU P S.Efficient parallel data mining for association rules[C]∥International Conference on Information and Knowledge Management.ACM,1995:31-36. [20]AGRAWAL R,SHAFER J C.Parallel Mining of Association Rules[J].IEEE Transactions on Knowledge & Data Enginee-ring,2007,8(6):962-969. [21]CHEUNG D W,HAN J,NG V T,et al.A fast distributed algorithm for mining association rules[C]∥International Conference on Parallel and Distributed Information Systems.IEEE,1996:31-42. [23]LI H,ZHANG Y,ZHANG N,et al.A Heuristic Rule Based Approximate Frequent Itemset Mining Algorithm[J].Procedia Computer Science,2016,91:324-333. [24]ZAKI M J,PARTHASARATHY S,OGIHARA M,et al.Parallel Algorithms for Discovery of Association Rules[J].Data Mi-ning & Knowledge Discovery,1997,1(4):343-373. [25]HAN E H,KARYPIS G,KUMAR V.Scalable Parallel Data Mining for Association Rules[J].Acm Sigmod Record,1997,26(2):277-288. [26]CERIN C,GAY J S,MAHEC G L,et al.Efficient data-structures and parallel algorithms for association rules discovery[C]∥Proceedings of the Fifth Mexican International Conference in Computer Science,2004(ENC 2004).IEEE,2004:399-406. [27]THOMAS W.Parallel mining of association rules using a lattice based approach[C]∥SoutheastCon.IEEE,2009:645-650. [28]ISHIKAWA H,SHIOYA Y,OMI T,et al.A Peer-to-Peer Approach to Parallel Association Rule Mining[M]∥Knowledge-Based Intelligent Information and Engineering Systems.Berlin:Springer,2004:178-188. [29]YONG W,ZHE Z,FANG W.A parallel algorithm of association rules based on cloud computing[C]∥International ICST Conference on Communications and Networking in China.IEEE,2014:415-419. [30]GUPTA E,DONEPUDI H.A sparse memory allocation data structure for sequential and parallel association rule mining[M].Kluwer Academic Publishers,2016. [31]DANG N,VO B,LE B.Efficient strategies for parallel mining class association rules[J].Expert Systems with Applications,2014,41(10):4716-4729. [32]ASADPOUR M,SADREDDINI M H,DASTGHAIBYFARD G.Parallel Mining of Association Rules from Gene Expression Databases[C]∥International Conference on Fuzzy Systems and Knowledge Discovery.IEEE,2007:68-73. [33]YU K M,ZHOU J,HONG T P,et al.A load-balanced distributed parallel mining algorithm[J].Expert Systems with Applications,2010,37(3):2459-2464. [34]PELÁEZ V C,AUSÍN L,RUIZ M M,et al.Mining Fuzzy Association Rules Based on Parallel Particle Swarm Optimization Algorithm[J].Computer Science,2013,21(2):147-162. [35]LAN V,ALAGHBAND G.Novel parallel method for mining frequent patterns on multi-core shared memory systems[C]∥International Workshop on Data-Intensive Scalable Computing Systems.2013:49-54. [36]JIN D,ZIAVRAS S G.A Super-Programming Approach for Mining Association Rules in Parallel on PC Clusters[J].IEEE Transactions on Parallel & Distributed Systems,2004,15(9):783-794. [37]MANASKASEMSAK N B,BENJAMAS N N,RUNGSAWANG A,et al.Parallel association rule mining based on FI-growth algorithm[C]∥2007 International Conference on Parallel and Distributed Systems.2007:1-8. [38]EL-HAJJ M,ZAIANE O R.Parallel association rule mining with minimum inter-processor communication[C]∥InternationalWorkshop on Database and Expert Systems Applications.IEEE,2003:519-523. [39]BURDA M,PAVLISKA V,VALASEK R.Parallel mining of fuzzy association rules on dense data sets[C]∥2014 IEEE International Conference on Fuzzy Systems(FUZZ-IEEE).IEEE,2014:2156-2162. [40]ABRAHAM S,JOSEPH S.A Coherent Rule Mining Method for Incremental Datasets Based on Plausibility[J].Procedia Technology,2016,24:1292-1299. [41]LEE C H,LIN C R,CHEN M S.Sliding window filtering:An efficient method for incremental mining on a time-variant database[J].Information Systems,2005,30(3):227-244. [42]LU J,WANG L,FANG Y,et al.A novel method on incremental mining of spatial co-locations[C]∥International Conference on Big Data and Smart Computing.IEEE,2016:69-76. [43]LEE W J,LEE S J.A general mining method for incremental updation in large databases[C]∥IEEE International Conference on Systems,Man and Cybernetics.IEEE,2003:1423-1428. [44]AHMED C F,TANBEER S K,JEONG B S.An Efficient Me-thod for Incremental Mining of Share-Frequent Patterns[C]∥International Asia-Pacific Web Conference.IEEE Computer Society,2010:147-153. [45]OTEY M E,PARTHASARATHY S,WANG C,et al.Parallel and distributed methods for incremental frequent itemset mining[J].IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society,2004,34(6):2439-2450. [46]HE H T,ZHANG S L.A New Method for Incremental Updating Frequent Patterns Mining[C]∥International Conference on Innovative Computing,Informatio and Control.IEEE Computer Society,2007:561. [47]LIN C W,LAN G C,HONG T P.An incremental mining algorithm for high utility itemsets[M].Pergamon Press,2012. [48]LIN C W,HONG T P,LU W H.The Pre-FUFP algorithm for incremental mining[J].Expert Systems with Applications,2009,36(5):9498-9505. [49]YAFI E,ALAM A H M A,BISWAS R.Incremental Mining of Shocking Association Patterns[J].International Arab Journal of Information Technology,2011,9(6):504-510. [50]GHARIB T F,NASSAR H,TAHA M,et al.An efficient algorithm for incremental mining of temporal association rules[J].Data & Knowledge Engineering,2010,69(8):800-815. [51]MASSEGLIA F,PONCELET P,TEISSEIRE M.Incremental mining of sequential patterns in large databases[J].Data & Knowledge Engineering,2003,46(1):97-121. [52]LI H.An algorithm to discover the approximate probabilistic frequent itemsets with sampling method[C]∥International Conference on Natural Computation,Fuzzy Systems and Know-ledge Discovery.IEEE,2016:1428-1432. [53]WU X,FAN W,PENG J,et al.Iterative sampling based fre-quent itemset mining for big data[J].International Journal of Machine Learning & Cybernetics,2015,1(6):1-8. [54]RIONDATO M,UPFAL E.Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees[J].Acm Transactions on Knowledge Discovery from Data,2014,8(4):1-32. [55]PIETRACAPRINA A,RIONDATO M,UPFAL E,et al.Mining top-K frequent itemsets through progressive sampling[J].Data Mining & Knowledge Discovery,2010,21(2):310-326. [56]MAHAFZAH B A,AL-BADARNEH A F,ZAKARIA M Z.A new sampling technique for association rule mining[J].Journal of Information Science,2009,35(3):358-376. [57]ZAKI J,PARTHASARATHY S,LIN W,et al.Evaluation of sampling for data mining of association rules[C]∥Proceedings of Seventh International Workshop on Research Issues in Data Engineering.1997:42-49. [58]BRONNIMANN H,CHEN B,DASH M,et al.Efficient data reduction with EASE[C]∥Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.2003:59-68. [59]CHEN B,HAAS P,SCHEUERMANN P.A new two-phase sampling based algorithm for discovering association rules[C]∥Proceedings of the Eighth ACM SIGKDD International Confe-rence on Knowledge Discovery and Data Mining.2002:462-468. [60]AKCAN H,ASTASHYN A,BRONNIMANN H.Deterministic algorithms for sampling count data[J].Data and Knowledge Engineering,2008,64(2):405-418. [61]PARTHASARATHY S.Efficient progressive sampling for association rules[C]∥Proceedings of the IEEE International Conference on Data Mining.2002:354-361. [62]BANDYOPADHYAY S,SAHA S.GAPS:A clustering method using a new point symmetry-based distance measure[J].Pattern Recognition,2007,40(12):3430-3451. [63]ANERJEE A,KRUMPELMAN C,GHOSH J,et al.Model-based overlapping clustering[C]∥Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Disco-very in Data Mining.2005:532-537. [64]CHEN Y L,HU H L.An overlapping cluster algorithm to provide non-exhaustive clustering[J].European Journal of Operational Research,2006,173(3):762-780. [65]SAHA S,BANDYOPADHYAY S.Application of a new symmetry-based cluster validity index for satellite image segmentation[J].IEEE Geoscience and Remote Sensing Letters,2008,5(2):166-170. [66]CHEN C,HORNG S,HUANG C.Locality sensitive hashing for sampling-based algorithms in association rule mining[J].Expert Systems with Applications,2011,38(10):12388-12397. [67]EL-HAJJ M.COFI approach for mining frequent itemsets revi-sited[M]∥DMKD’04.Paris:ACM,2004:70-75. [68] EL-HAJJ M,ZAÍANE O.Inverted matrix:Efficient discovery of frequent items in large datasets in the context of interactive mining[C]∥Acm Sigkdd International Conference on Knowledge Discevery & Data Mining.National Acad Sciences,2003:109-118. [69]AGARWAL R C,AGGARWAL C C,V V,et al.Tree Projection Algorithm for Generation of Frequent Item Sets[J].Journal of Parallel and Distributed Computing,2001,61(3):350-371. [70]PEI J,HAN J,LU H,et al.H-mine:Hyper-structure mining of frequent patterns in large databases[C]∥IEEE International Conference on Data Mining.IEEE,2002:441. [71]LIU J,PAN Y,WANG K,et al.Mining frequent item sets by opportunistic projection[C]∥8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2002:229-238. [72]LIU G,LU H,LOU W,et al.Ascending Frequency Ordered Prefix-tree:Efficient Mining of Frequent Patterns[C]∥Procee-dings of KDD Conference.2003:65-73. [73]AGARWAL R,AGGARWAL C,PRASAD V.Depth first gene-ration of long patterns[C]∥ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2000:108-118. [74]PIETRACAPRINA A,ZANDOLIN D.Mining Frequent Item-sets Using Patricia Tries[C]∥Proceedings of the IEEE ICDM Workshop on FIMI.2003. [75]SUCAHYO Y G,GOPALAN R P.CT-ITL:efficient frequent item set mining using a compressed prefix tree with pattern growth[C]∥Australasian Database Conference.Australian Computer Society,2003:95-104. [76]SUCAHYO Y G,GOPALAN R P.CT-PRO:A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure[C]∥Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations(Fimi’04).Brighton,Uk,DBLP,2004. [77]GRAHNE G,ZHU J.Fast algorithms for frequent itemset mi-ning using FP-trees[J].IEEE Transactions on Knowledge & Data Engineering,2005,17(10):1347-1362. [78]秦亮曦,苏永秀,刘永彬,等.基于压缩FP-树和数组技术的频繁模式挖掘算法[J].计算机研究与发展,2008,45(z1):244-249. [79]ZHU Q,LIN X.Depth First Generation of Frequent Patterns Without Candidate Generation[M]∥Emerging Technologies in Knowledge Discovery and Data Mining.Springer Berlin Heidelberg,2007:378-388. [80]杨云,罗艳霞.FP-Growth算法的改进[J].计算机工程与设计,2010,31(7):1506-1509. [81]章志刚,吉根林.一种基于FP-Growth的频繁项目集并行挖掘算法[J].计算机工程与应用,2014,50(2):103-106. [82]WEI X,MA Y,ZHANG F,et al.Incremental FP-Growth mining strategy for dynamic threshold value and database based on Map-Reduce[C]∥IEEE,International Conference on Computer Supported Cooperative Work in Design.IEEE,2014:271-276. [83]陆可,桂伟,江雨燕,等.基于Spark的并行FP-Growth算法优化与实现[J].计算机应用与软件,2017,34(9):273-278. [84]王建明,袁伟.基于节点表的FP-Growth算法改进[J].计算机工程与设计,2018,39(1):140-145. [85]ZAKI M J.Scalable algorithms for association mining[M].IEEE Educational Activities Department,2000. [86]ZAKI M J,GOUDA K.Fast vertical mining using diffsets[C]∥ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining.ACM,2003:326-335. [87]SHENOY P,HARITSA J R,SUDARSHAN S,et al.Turbo-charging vertical mining of large databases[J].Acm Sigmod Record,2000,29(2):22-33. [88]XIONG Z Y,CHEN P E,ZHANG Y F.Improvement of Eclat algorithm for association rules based on hash Boolean matrix[J].Application Research of Computers,2010,27(4):1323-1325. [89]YU X,WANG H.Improvement of Eclat Algorithm Based on Support in Frequent Itemset Mining[J].Journal of Computers,2014,9(9):2116-2123. [90]ZHANG Y F,XIONG Z Y,GENG X F,et al.Analysis and Improvement of Eclat Algorithm[J].Computer Engineering,2010,36(23):28-30. [91]FENG P E,YU L,QIU Q Y,et al.Strategies of efficiency improvement for Eclat algorithm[J].Journal of Zhejiang University,2013,47(2):223-230. [92]PASQUIER N,BASTIDE Y,TAOUIL R,et al.Discovering Frequent Closed Itemsets for Association Rules[J].Lecture Notes in Computer Science,1999,1540:398-416. [93]PEI J,HAN J,MAO R.CLOSET:An Efficient Algorithm for Mining Frequent Closed Itemsets[C]∥SIGMOD International Workshop on Data Mining and Knowedge Discovery.2000:21-30. [94]WANG J,HAN J,PEI J.CLOSET+:searching for the best strategies for mining frequent closed itemsets[C]∥ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM,2003:236-245. [95]GRAHNE G.Efficiently using prefix-trees in mining frequent itemsets[C]∥Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations.2003. [96]CHENG H,YU P S,HAN J.AC-Close:Efficiently Mining Approximate Closed Itemsets by Core Pattern Recovery[C]∥International Conference on Data Mining.IEEE,2006:839-844. [97]UNO T,KIYOMI M,ARIMURA H.Efficient Mining Algo-rithms for Frequent/Closed/Maximal Itemsets[C]∥FIMI’04.2004. [98]LUCCHESE C,ORLANDO S,PEREGO R.Fast and Memory Efficient Mining of Frequent Closed Itemsets[J].IEEE Transa-ctions on Knowledge & Data Engineering,2006,18(1):21-36. [99]CHI Y,WANG H,YU P S,et al.Moment:maintaining closed frequent itemsets over a stream sliding window[C]∥IEEE International Conference on Data Mining.IEEE,2006:59-66. [100]CHIU S C,LI H F,HUANG J L,et al.Incremental mining of closed inter-transaction itemsets over data stream sliding windows[J].Journal of Information Science,2011,37(2):208-220. [101]NORI F,DEYPIR M,HADI M,et al.A new sliding window based algorithm for frequent closed itemset mining over data streams[J].Journal of Systems & Software,2013,86(3):615-623. [102]DONG J,HAN M.BitTableFI:An efficient mining frequent itemsets algorithm[J].Knowledge-Based Systems,2007,20(4):329-335. [103]SONG W,YANG B,XU Z.Index-BitTableFI:An improved algorithm for mining frequent itemsets[J].Knowledge-Based Systems,2008,21(6):507-513. [104]BAYARDO R J.Efficiently mining long patterns from databases[C]∥ACM SIGMOD International Conference on Management of Data.ACM,1998:85-93. [105]AGARWAL R C,AGGARWAL C C,PRASAD V V V.Depth first generation of long patterns[C]∥ACM SIGKDD International Conference on Knowedge Discovery and Data Mining.ACM,2000:108-118. [106]BURDICK D,CALIMLIM M,FLANNICK J,et al.MAFIA:A Maximal Frequent Itemset Algorithm[C]∥International Conference on Data Engineering.IEEE Computer Society,2001:443. [107]GOUDA K,ZAKI M J.Efficiently Mining Maximal Frequent Itemsets[C]∥IEEE International Conference on Data Mining.IEEE,2002:2405-2409. [108]ZOU Q,CHU W W,LU B.SmartMiner:A Depth First Algorithm Guided by Tail Information for Mining Maximal Frequent Itemsets[C]∥IEEE International Conference on Data Mining,2002(ICDM 2003).IEEE,2002:570-577. [109]宋余庆,朱玉全,孙志挥,等.基于FP-Tree的最大频繁项目集挖掘及更新算法[J].软件学报,2003,14(9):1586-1592. [110]颜跃进,李舟军,陈火旺,等.基于FP-Tree有效挖掘最大频繁项集[J].软件学报,2005,16(2):215-222. [111]秦亮曦,史忠植.SFP-Max-基于排序FP-树的最大频繁模式挖掘算法[J].计算机研究与发展,2005,42(2):217-223. [112]JU S,CHEN C.MMFI:An Effective Algorithm for Mining Maximal Frequent Itemsets[C]∥International Symposiums on Information Processing.IEEE Computer Society,2008:144-148. [113]钱雪忠,惠亮.关联规则中基于降维的最大频繁模式挖掘算法[J].计算机应用,2011,31(5):1339-1343. [114]ZHAO Z G,WANG F,WAN J.Maximal frequent itemsets mi-ning algorithm based on OWSFP-tree[J].Computer Engineering &Design,2013,34(5):1687-1680. [115]YANG P,PENG H,ZHOU X,et al.FP-MFIA:improved algorithm for mining maximum frequent itemsets based on frequent-pattern tree[J].Journal of Computer Applications,2015,35(3):775-778. |
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