High-speed heuristic algorithm for mining frequent patterns in data stream

Ruan Jian Xue Bao/Journal of Software

Volumn 16, Issue 12, 2005, Pages 2099-2105

  Zhang, Xin ^a   Li, Xiao Guang ^a   Wang, Da Ling ^a   Yu, Ge ^a  

^a NORTHEASTERN UNIVERSITY   (China)

Author keywords

Data mining; Data stream; Frequent pattern; Tilted window

Indexed keywords

DATA FLOW ANALYSIS; DATA PROCESSING; FREQUENCIES; SPEED; WINDOWS;

DATA STREAM; FREQUENT PATTERN MINING; IMPROVED LEXICOGRAPHIC TREE(IL TREE); TILTED WINDOW;

DATA MINING;

EID: 33644964686     PISSN: 10009825     EISSN: None     Source Type: Journal    
DOI: 10.1360/jos162099     Document Type: Article

References (7)

1. Giannella C, Han JW, Pei J, Yan XF, Yu PS. Mining frequent patterns in data streams at multiple time granularities. http://maids.ncsa.uiuc.edu/documents/readings/fpstm03.pdf
2. Manku GS, Motwani R. Approximate frequency counts over data streams. In: Bernstein P, Ioannidis Y, Ramakrishnan R, eds. Proc. of the 28th Int'l Conf. on Very Large Data Bases. Hong Kong: Morgan Kaufmann Publishers, 2002. 346-357.
3. Hidber C. Online association rule mining. In: Delis A, Faloutsos C, Ghandeharizadeh S, eds. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data (SIGMOD 1999). Philadelphia: ACM Press, 1999. 145-156.
4. Chang J, Lee W. Finding recent frequent itemsets adaptively over online data streams. In: Lise G, Ted E. S, Pedro D, Christos F, eds. Proc. of the 9th ACM SIGKDD Int'l Conf. on Knowledge Discovery and Data Mining. Washington: ACM Press, 2003. 226-235.
5. Agrawal R, Srikant R. Fast algorithms for mining association rules. In: Beeri C, et al., eds. Proc. of the 20th Int'l Conf. on Very Large Databases. Santiago: Morgan Kaufmann Publishers, 1994. 487-499.
6. Agarwal RC, Aggarwal CC, Prasad VVV. A tree projection algorithm for finding frequent itemsets. Journal on Parallel and Distributed Computing, 2001,61(3):350-371.
7. http://www.almaden.ibm.com/software/quest/Resources/index.shtml