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Title of Journal: Methodol Comput Appl Probab

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Abbravation: Methodology and Computing in Applied Probability

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Springer US

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DOI

10.1007/bf01440885

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1573-7713

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Random Databases with Approximate Record Matching

Authors: Oleg Seleznjev Bernhard Thalheim
Publish Date: 2008/07/31
Volume: 12, Issue: 1, Pages: 63-89
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Abstract

In many database applications in telecommunication environmental and health sciences bioinformatics physics and econometrics realworld data are uncertain and subjected to errors These data are processed transmitted and stored in large databases We consider stochastic modelling for databases with uncertain data and for some basic database operations for example join selection with exact and approximate matching Approximate join is used for merging or data deduplication in large databases Distribution and mean of the join sizes are studied for random databases A random database is treated as a table with independent random records with a common distribution or a set of random tables These results can be used for integration of information from different databases multiple join optimization and various probabilistic algorithms for structured random data

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Other Papers In This Journal:
  1. Effect of Data Transformations on Predictive Risk Indicators
  2. Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models
  3. Importance and Sensitivity Analysis in Dynamic Reliability
  4. Random Survival Forests Models for SME Credit Risk Measurement
  5. Selecting the Best Population Using a Test for Equality Based on Minimal Wilcoxon Rank-sum Precedence Statistic
  6. Saddlepoint Approximations to Tail Probabilities and Quantiles of Inhomogeneous Discounted Compound Poisson Processes with Periodic Intensity Functions
  7. On Estimation of the Intensity Function of a Point Process
  8. Call Option Prices Based on Bessel Processes
  9. Goodness-of-Fit Tests for Continuous Regression
  10. Waiting Time Distribution for the Emergence of Superpatterns
  11. Computing the Expected Markov Reward Rates with Stationarity Detection and Relative Error Control
  12. Estimating Stochastic Dynamical Systems Driven by a Continuous-Time Jump Markov Process
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