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Challenges for Efficient Query Evaluation on Structured Probabilistic Data

Antoine Amarilli 1 Silviu Maniu 2 Mikaël Monet 1
1 DBWeb
LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : Query answering over probabilistic data is an important task but is generally intractable. However, a new approach for this problem has recently been proposed, based on structural decompositions of input databases, following, e.g., tree decompositions. This paper presents a vision for a database management system for probabilistic data built following this structural approach. We review our existing and ongoing work on this topic and highlight many theoretical and practical challenges that remain to be addressed.
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Submitted on : Monday, September 5, 2016 - 2:48:41 PM
Last modification on : Friday, July 9, 2021 - 4:35:29 AM
Long-term archiving on: : Tuesday, December 6, 2016 - 1:38:29 PM


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Antoine Amarilli, Silviu Maniu, Mikaël Monet. Challenges for Efficient Query Evaluation on Structured Probabilistic Data. SUM 2016 - 10th International Conference Scalable Uncertainty Management, Sep 2016, Nice, France. pp.323-330, ⟨10.1007/978-3-319-45856-4_22⟩. ⟨hal-01360167⟩



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