Conferences in Research and Practice in Information Technology
  

Online Version - Last Updated - 20 Jan 2012

 

 
Home
 

 
Procedures and Resources for Authors

 
Information and Resources for Volume Editors
 

 
Orders and Subscriptions
 

 
Published Articles

 
Upcoming Volumes
 

 
Contact Us
 

 
Useful External Links
 

 
CRPIT Site Search
 
    

Continuously Maintaining Order Statistics over Data Streams

Lin, X.

    A rank query is essentially to find a data element with a given rank against a monotonic order specified on data elements. It has several equivalent variations [8, 17, 30]. Rank queries over data streams have been investigated in the form of quantile computation. A _-quantile (_ 2 (0, 1]) of a collection of N data elements is the element with rank d_Ne against a monotonic order specified on data elements. Rank and quantile queries have many applications [1, 3, 6, 7, 10, 14-16, 26, 27], including monitoring high speed networks, trends and fleeting opportunities detection in the stock market, sensor data analysis,Web ranking aggregation and log mining, etc. In these applications, they not only play very important roles in the decision making but also have been used in summarizing data distributions of data streams.
Cite as: Lin, X. (2007). Continuously Maintaining Order Statistics over Data Streams. In Proc. Eighteenth Australasian Database Conference (ADC 2007), Ballarat, Australia. CRPIT, 63. Bailey, J. and Fekete, A., Eds. ACS. 7-10.
pdf (from crpit.com) pdf (local if available) BibTeX EndNote GS
 

 

ACS Logo© Copyright Australian Computer Society Inc. 2001-2014.
Comments should be sent to the webmaster at crpit@scem.uws.edu.au.
This page last updated 16 Nov 2007