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ICDE
2009
IEEE

Clustering Uncertain Data with Possible Worlds

11 years 6 months ago
Clustering Uncertain Data with Possible Worlds
The topic of managing uncertain data has been explored in many ways. Different methodologies for data storage and query processing have been proposed. As the availability of management systems grows, the research on analytics of uncertain data is gaining in importance. Similar to the challenges faced in the field of data management, algorithms for uncertain data mining also have a high performance degradation compared to their certain algorithms. To overcome the problem of performance degradation, the MCDB approach was developed for uncertain data management based on the possible world scenario. As this methodology shows significant performance and scalability enhancement, we adopt this method for the field of mining on uncertain data. In this paper, we introduce a clustering methodology for uncertain data and illustrate current issues with this approach within the field of clustering uncertain data.
Peter Benjamin Volk, Frank Rosenthal, Martin Hahma
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where ICDE
Authors Peter Benjamin Volk, Frank Rosenthal, Martin Hahmann, Dirk Habich, Wolfgang Lehner
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