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Supporting ranking pattern-based aggregate queries in sequence data cubes

Published: 02 November 2009 Publication History

Abstract

Sequence data processing has been studied extensively in the literature.
In recent years, the warehousing and online-analytical processing (OLAP) of archived sequence data have received growing attentions. In particular, the concept of sequence OLAP is recently proposed with the objective of evaluating various kinds of so-called Pattern-Based Aggregate (PBA) queries so that various kinds of data analytical tasks on sequence data can be carried out efficiently. This paper studies the evaluation of ranking PBA queries, which rank the results of PBA queries and return only the top-ranked ones to users. We discuss how ranking PBA queries drastically improve the usability of S-OLAP systems and present techniques that can evaluate various kinds of ranking PBA queries efficiently.

References

[1]
B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom. Models and issues in data stream systems. In PODS '02: Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pages 1--16, 2002.
[2]
N. Bruno and H. Wang. The threshold algorithm: From middleware systems to the relational engine. IEEE Trans. on Knowl. and Data Eng., 19(4):523--537, 2007.
[3]
J. Chen, D. J. DeWitt, F. Tian, and Y. Wang. Niagaracq: a scalable continuous query system for internet databases. SIGMOD Rec., 29(2):379--390, 2000.
[4]
G. Das, D. Gunopulos, N. Koudas, and D. Tsirogiannis. Answering top-k queries using views. In VLDB, pages 451--462, 2006.
[5]
R. Fagin, A. Lotem, and M. Naor. Optimal aggregation algorithms for middleware. In PODS, pages 102--113, 2001.
[6]
L. Golab and M. T. Özsu. Issues in data stream management. SIGMOD Record, 32(2):5--14, 2003.
[7]
H. Gonzalez, J. Han, and X. Li. FlowCube: Constructuing RFID FlowCubes for Multi-Dimensional Analysis of Commodity Flows. In VLDB, pages 834--845, 2006.
[8]
H. Gonzalez, J. Han, X. Li, and D. Klabjan. Warehousing and Analyzing Massive RFID Data Sets. In ICDE, page 83, 2006.
[9]
U. Güntzer, W.-T. Balke, and W. Kießling. Optimizing multi-feature queries for image databases. In VLDB, pages 419--428, 2000.
[10]
I. F. Ilyas, R. Shah, W. G. Aref, J. S. Vitter, and A. K. Elmagarmid. Rank-aware query optimization. In SIGMOD, pages 203--214, 2004.
[11]
R. Kohavi, C. Brodley, B. Frasca, L. Mason, and Z. Zheng. KDD-Cup 2000 organizers' report: Peeling the onion. SIGKDD Explorations, 2(2):86--98, 2000.
[12]
C. Li, K. C.-C. Chang, and I. F. Ilyas. Supporting ad-hoc ranking aggregates. In SIGMOD Conference, pages 61--72, 2006.
[13]
E. Lo, B. Kao, W.-S. Ho, S. D. Lee, C. K. Chui, and D. W. Cheung. OLAP on Sequence Data. In SIGMOD, pages 649--660, 2008.
[14]
A. Marian, N. Bruno, and L. Gravano. Evaluating top-k queries over web-accessible databases. TODS, 29(2):319--362, 2004.
[15]
R. Ramakrishnan, D. Donjerkovic, A. Ranganathan, K. S. Beyer, and M. Krishnaprasad. SRQL: Sorted Relational Query Language. In SSDBM, pages 84--95, 1998.
[16]
R. Sadri, C. Zaniolo, A. Zarkesh, and J. Adibi. Optimization of sequence queries in database systems. In PODS, pages 71--81, 2001.
[17]
P. Seshadri, M. Livny, and R. Ramakrishnan. Sequence query processing. In SIGMOD, pages 430--441, 1994.
[18]
P. Seshadri, M. Livny, and R. Ramakrishnan. The design and implementation of a sequence database system. In VLDB, pages 99--110, 1996.
[19]
F. Wang and P. Liu. Temporal management of rfid data. In VLDB, pages 1128--1139, 2005.
[20]
T. Wu, D. Xin, and J. Han. Arcube: supporting ranking aggregate queries in partially materialized data cubes. In SIGMOD Conference, pages 79--92, 2008.

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    cover image ACM Conferences
    CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management
    November 2009
    2162 pages
    ISBN:9781605585123
    DOI:10.1145/1645953
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    Published: 02 November 2009

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    Author Tags

    1. OLAP
    2. data cube
    3. query processing
    4. sequence
    5. top-k

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