By Tharam S. Dillon, Elizabeth Chang, Farookh Hussain (auth.), Qing Li, Guoren Wang, Ling Feng (eds.)

This publication constitutes the refereed court cases of the fifth foreign convention on Web-Age info administration, WAIM 2004, held in Dalian, China in July 2004.

The fifty seven revised complete papers and 23 revised brief and commercial papers provided including three invited contributions have been rigorously reviewed and chosen from 291 submissions. The papers are prepared in topical sections on information circulate processing, time sequence facts processing, safety, cellular computing, cache administration, question evaluate, net se's, XML, internet providers, class, and information mining.

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SIGMOD, 2003. 6. P. J. Haas. Large-Sample and Deterministic Confidence Intervals for Online Aggregation. 9th International Conference on Scientific and Statistical Database Management (SSDBM, 1997). 7. J. M. Hellerstein, P. J. Hass, H. J. Wang. Online Aggregation. SIGMOD, 1997. 8. A. Arasu, B. Babu. Characterizing Memory Requirements for Queries over Continuous Data Streams. PODS, 2002. 9. J. Kang. J. F. Naughton, S. D. Viglas. Evaluating Window Joins over Unbounded Streams. ICDE, 2003. 10. A. Araru, S.

Dynamic inheritance. Inheritance is a common phenomenon in the organism world and it is also the key mechanism in the Object-Oriented methodology and systems for realizing reuse. How to realize the inheritance mechanism among evolving resources in an evolving environment is a challenging issue. 5. Degeneration rule of network. Researchers have studied the growth and distribution of the World Wide Web [1], but they have neglected the degeneration phenomenon. It is common in real world that the development of anything has a limitation.

In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding windows. Our algorithm makes one pass on the data stream and maintains an -approximate summary. It uses O( 12 log2 N ) space where N is the number of data items in the window. We extend this framework to further process generalized constrained sliding window queries and proved that our technique is applicable for flexible window settings.

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