Multiplicative synopses for relative-error metrics

Existing hierarchical summarization techniques fail to provide synopses good in terms of relative-error metrics. This paper introduces multiplicative synopses: a summarization paradigm tailored for effective relative-error summarization. This paradigm is inspired from previous hierarchical indexbased summarization schemes, but goes beyond them by altering their underlying data representation mechanism. Existing schemes have decomposed the summarized data based on sums and differences of values, resulting in what we call additive synopses. We argue that the incapacity of these models to handle relative-error metrics stems exactly from this additive nature of their representation mechanism. We substitute this additive nature by a multiplicative one. We argue that this is more appropriate for achieving low-relative-error data approximations. We develop an efficient linear-time dynamic programming scheme for onedimensional multiplicative synopsis construction under general relative-erro...

• Type: Conference
• Year: 2009
• Where: EDBT
• Authors: Panagiotis Karras
• Keywords: Database, EDBT 2009, Hierarchical Summarization Techniques, Indexbased Summarization Schemes, Maximum Relative Error