Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Analytical profile estimation in database systems
Information Systems
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Introduction to inference for Bayesian networks
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
Join synopses for approximate query answering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
The Aqua approximate query answering system
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Compressed data cubes for OLAP aggregate query approximation on continuous dimensions
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Approximate Query Answering Using Data Warehouse Striping
Journal of Intelligent Information Systems - Special issue on data warehousing and knowledge discovery
Approximate query processing using wavelets
The VLDB Journal — The International Journal on Very Large Data Bases
Approximate Query Answering with Frequent Sets and Maximum Entropy
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Selectivity estimation of range queries based on data density approximation via cosine series
Data & Knowledge Engineering
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A probabilistic model for data cube compression and query approximation
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
Approaches of quality outputs from the business systems
CIMMACS'06 Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
TuG synopses for approximate query answering
ACM Transactions on Database Systems (TODS)
Data reduction for data analysis
ECC'08 Proceedings of the 2nd conference on European computing conference
Fundamentals of Database Systems
Fundamentals of Database Systems
AQUAGP: approximate QUery answers using genetic programming
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Metrics for approximate query engine evaluation
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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Approximate query processing is often based on analytical methodologies able to provide fast responses to queries. As a counterpart, the approximate answers are affected with a small quantity of error. Nowadays, these techniques are being exploited in data warehousing environments, because the queries devoted to extract information involve high-cardinality relations and, therefore, require a high computational time. Approximate answers are profitably used in the decision making process, where the total precision is not needed. Thus, it is important to provide decision makers with accuracy estimates of the approximate answers; that is, a measure of how much reliable the approximate answer is. Here, a probabilistic model is presented for providing such an accuracy measure when the analytical methodology used for decisional analyses is based on polynomial approximation. This probabilistic model is a Bayesian network able to estimate the relative error of the approximate answers.