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2010
ACM

Reducing metadata complexity for faster table summarization

9 years 4 months ago
Reducing metadata complexity for faster table summarization
Since the visualization real estate puts stringent constraints on how much data can be presented to the users at once, table summarization is an essential tool in helping users quickly explore large data sets. An effective summary needs to minimize the information loss due to the reduction in details. Summarization algorithms leverage the redundancy in the data to identify value and tuple clustering strategies that represent the (almost) same amount of information with a smaller number of data representatives. It has been shown that, when available, metadata, such as value hierarchies associated to the attributes of the tables, can help greatly reduce the resulting information loss. However, table summarization, whether carried out through data analysis performed on the table from scratch or supported through already available metadata, is an expensive operation. We note that the table summarization process can be significantly sped up when the metadata used for supporting the summa...
K. Selçuk Candan, Mario Cataldi, Maria Luis
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2010
Where EDBT
Authors K. Selçuk Candan, Mario Cataldi, Maria Luisa Sapino
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