Indexing correlated probabilistic databases

With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc., effectively managing and querying them has become an important research direction. While there is an exhaustive body of literature on querying independent probabilistic data, supporting efficient queries over large-scale, correlated databases remains a challenge. In this paper, we develop efficient data structures and indexes for supporting inference and decision support queries over such databases. Our proposed hierarchical data structure is suitable both for inmemory and disk-resident databases. We represent the correlations in the probabilistic database using a junction tree over the tuple-existence or attribute-value random variables, and use tree partitioning techniques to build an index structure over it. We show how to efficiently answer inference and aggregation queries using such an index, resulting...

• Type: Conference
• Year: 2009
• Where: SIGMOD
• Authors: Bhargav Kanagal, Amol Deshpande
• Keywords: Correlated Probabilistic Data, Database, Independent Probabilistic Data, Keywords Probabilistic Databases, SIGMOD 2009