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Using Probabilistic Models for Data Management in
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Using Probabilistic Models for Data Management in Acquisitional Environments, Sam Madden MIT CSAIL, With Amol Deshpande (UMD), Carlos Guestrin (CMU),Outline Motivation Probabilistic Models New Queries and UI Applications Challenges and Concluding Remarks
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IT and Computers
-Database
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By
Paull Shocker
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Tags: Using Probabilistic Models Data Management Acquisitional Environments , Sam Madden , MIT CSAIL , Amol Deshpande (UMD) , Carlos Guestrin (CMU) , Outline , Motivation , Probabilistic Models , New Queries and UI , Applications , Challenges and Concluding Remarks
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MauveDB: Supporting Model-based User Views in Data
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MauveDB: Supporting Model-based User Views in Database Systems Amol Deshpande, University of Maryland Samuel Madden, MIT Motivation Unprecedented, and rapidly increasing, instrumentation of our every-day world Overwhelmingly large raw data volumes generated continuously Data must be processed in real-time The applications have strong acquisitional aspects Data may have to be actively acquired from the environment Typically imprecise, unreliable and incomplete data Inherent measurement noises (e.g. GPS) and low success rates (e.g. RFID) Communication link or sensor node failures (e.g. wireless sensor networks) Spatial and temporal biases because of measurement constraints Traditional data management tools are ill-equipped to handle these challenges
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IT and Computers
-Database
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By
Paull Shocker
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Tags: MauveDB , Supporting Model-based User Views Database Systems , Amol Deshpande , University Maryland , Samuel Madden , MIT , Wireless Sensor Networks
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