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...

• Type: Conference
• Year: 2010
• Where: EDBT
• Authors: K. Selçuk Candan, Mario Cataldi, Maria Luisa Sapino
• Keywords: Database, EDBT 2010, Table Summarization, Table Summarization Process, Table Summarization Time