Similarity Search and Mining in Uncertain Databases

Managing, searching and mining uncertain data has achieved much attention in the database community recently due to new sensor technologies and new ways of collecting data. There is a number of challenges in terms of collecting, modelling, representing, querying, indexing and mining uncertain data. In its scope, the diversity of approaches addressing these topics is very high because the underlying assumptions of uncertainty are different across different papers. This tutorial provides a comprehensive and comparative overview of general techniques for the key topics in the fields of querying, indexing and mining uncertain data. In particular, it identifies the most generic types of probabilistic similarity queries and discusses general algorithmic methods to answer such queries efficiently. In addition, the tutorial sketches probabilistic methods for important data mining applications in the context of uncertain data with special emphasis on probabilistic clustering and probabilist...

• Type: Journal
• Year: 2010
• Where: PVLDB
• Authors: Matthias Renz, Reynold Cheng, Hans-Peter Kriegel, Andreas Züfle, Thomas Bernecker
• Keywords: Mining, Probabilistic, PVLDB 2010, Uncertain Data