Open AccessConstructing Optimal Wavelet Synopses
Author(s) -
Dimitris Sacharidis
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-46788-2
DOI - 10.1007/11896548_10
Subject(s) - computer science , wavelet , data stream mining , context (archaeology) , data mining , categorization , algorithm , theoretical computer science , artificial intelligence , paleontology , biology
The wavelet decomposition is a proven tool for constructing concise synopses of massive data sets and rapid changing data streams, which can be used to obtain fast approximate, with accuracy guarantees, answers. In this work we present a generic formulation for the problem of constructing optimal wavelet synopses under space constraints for various error metrics, both for static and streaming data sets. We explicitly associate existing work and categorize it according to the previous problem formulation and, further, we present our current work and identify its contributions in this context. Various interesting open problems are described and our future work directions are clearly stated. © Springer-Verlag Berlin Heidelberg 2006
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