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http://dx.doi.org/10.9728/dcs.2012.13.1.021

A Method of Frequent Structure Detection Based on Active Sliding Window  

Hwang, Jeong-Hee (남서울대학교 컴퓨터학과)
Publication Information
Journal of Digital Contents Society / v.13, no.1, 2012 , pp. 21-29 More about this Journal
Abstract
In ubiquitous computing environment, rising large scale data exchange through sensor network with sharply growing the internet, the processing of the continuous stream data is required. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the active window sliding using trigger rule. The proposed method is a basic research to control the stream data flow for data mining and continuous query by trigger rules.
Keywords
XML Stream; XML Mining; Frequent Structure; Trigger;
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  • Reference
1 J. Han, J. Pei, Y. Yin, "Mining Frequent Patterns without Candidate Generation", In Proc. of ACM SIGMOD International Conference on the Management of Data, 2000.
2 NIAGARA query engine. http://www.cs.wisc.edu/niagara/data.html.
3 H. F. Li, S. Y. Lee, "Mining Frequent Itemsets over Data Streams using Efficient Window Sliding Techniques", International Journal of Expert Systems with Applications, 2009.
4 J. Chen, D. J. DeWitt, F. Tian, U. Wang, "A Scalable Continuous Query System for Internet Database", ACM SIGMOD, 2000.
5 L.H. Yang, M.L. Lee, W. Hsu, "Finding Hot Query Patterns over An XQuery Stream", VLDB Journal Special Issue on Data Stream Processing, 2004.
6 T. Asai, K. Abe, S. Kawasoe, H.Sakamoto, et al., "Online Algorithms for Mining Semi-Structured Data Stream", In.Proc. ICDM, 2002.
7 C. K. S. Leung Q. I. Khan, "DSTree:A Tree Structure for the Mining of Frequent Sets from Data Streams", In proc. ICDM 2006.
8 J. H. Hwang, M. S. Gu, "Finding Frequent Structures in XML Stream Data", Computational Science and Its Applications, ICCSA, 2009.
9 M. C. Hsieh, Y. H. Wu, A. L. Chen, "Discovering Frequent Tree Patterns over Data Stream", In Proc of SIAM, 2006.
10 C. K. S. Leung Q. I. Khan, T. Hoque, "CanTree:A Tree Structure for Efficient Incremental Mining of Frequent Pattern Sets", In proc. ICDM 2005.
11 G. S. Manku, R. Motwani, "Approximate Frequency Counts over Data Streams", VLDB 2002.
12 G. Chen, X. Wu, and X. Zhu, "Mining Sequential Patterns Across Data Streams", Univ. of Vermont Computer Science Technical Report(CS-05-04), 2005.
13 A. Deligiannakis, Y. Kotidis, and Roussopoulos", Hierarchical In-Network Data Aggregation with Quality Guarantees", LNCS(EDBT 2004), 2004.