Random sampling with a reservoir
ACM Transactions on Mathematical Software (TOMS)
Balancing histogram optimality and practicality for query result size estimation
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
New sampling-based summary statistics for improving approximate query answers
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Wavelet-based histograms for selectivity estimation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Wavelets for computer graphics: theory and applications
Wavelets for computer graphics: theory and applications
The complexity of the matrix eigenproblem
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Wavelet synopses with error guarantees
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Accurate estimation of the number of tuples satisfying a condition
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Distinct Sampling for Highly-Accurate Answers to Distinct Values Queries and Event Reports
Proceedings of the 27th International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Extended wavelets for multiple measures
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Probabilistic wavelet synopses
ACM Transactions on Database Systems (TODS)
Deterministic wavelet thresholding for maximum-error metrics
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Wavelet synopsis for data streams: minimizing non-euclidean error
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Space efficiency in synopsis construction algorithms
VLDB '05 Proceedings of the 31st international conference on Very large data bases
One-pass wavelet synopses for maximum-error metrics
VLDB '05 Proceedings of the 31st international conference on Very large data bases
General purpose database summarization
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Approximation algorithms for wavelet transform coding of data streams
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Techniques for Warehousing of Sample Data
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Compressed histograms with arbitrary bucket layouts for selectivity estimation
Information Sciences: an International Journal
Summarizing data using a similarity based mountain method
Information Sciences: an International Journal
XWAVE: optimal and approximate extended wavelets
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Fast approximate wavelet tracking on streams
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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Approximate query answering has recently emerged as an effective method for generating a viable answer. Among various techniques for approximate query answering, wavelets have received a lot of attention. However, wavelet techniques minimizing the root squared error (i.e., the L"2 norm error) have several problems such as the poor quality of reconstructed data when the original data is biased. In this paper, we present AMID (Approximation of MultI-measured Data using SVD) for multi-measured data. In AMID, we adapt the singular value decomposition (SVD) to compress multi-measured data. We show that SVD guarantees the root squared error, and also drive an error bound of SVD for an individual data value, using mathematical analyses. In addition, in order to improve the accuracy of approximated data, we combine SVD and wavelets in AMID. Since SVD is applied to a fixed matrix, we use various properties of matrices to adapt SVD to the incremental update environment. We devise two variants of AMID for the incremental update environment: incremental AMID and local AMID. To the best of our knowledge, our work is the first to extend SVD to incremental update environments.