Algorithms for clustering data
Algorithms for clustering data
Equi-depth multidimensional histograms
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
Estimating alphanumeric selectivity in the presence of wildcards
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Improved histograms for selectivity estimation of range predicates
SIGMOD '96 Proceedings of the 1996 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
A comparison of selectivity estimators for range queries on metric attributes
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Dynamic Maintenance of Wavelet-Based Histograms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Approximate String Joins in a Database (Almost) for Free
Proceedings of the 27th International Conference on Very Large Data Bases
On Approximate String Matching
Proceedings of the 1983 International FCT-Conference on Fundamentals of Computation Theory
One-dimensional and multi-dimensional substring selectivity estimation
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Record Linkage in Large Data Sets
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
On the Resemblance and Containment of Documents
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Generalized substring selectivity estimation
Journal of Computer and System Sciences - Special issue on PODS 2000
Finding Interesting Associations without Support Pruning
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
A Comparison of Standard Spell Checking Algorithms and a Novel Binary Neural Approach
IEEE Transactions on Knowledge and Data Engineering
Selectivity Estimation for String Predicates: Overcoming the Underestimation Problem
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Fast Pattern Detection in Stream Data
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1
An improved data stream summary: the count-min sketch and its applications
Journal of Algorithms
Selectivity estimation for fuzzy string predicates in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Indexing mixed types for approximate retrieval
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Hashed samples: selectivity estimators for set similarity selection queries
Proceedings of the VLDB Endowment
Approximate substring selectivity estimation
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Efficient approximate entity extraction with edit distance constraints
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Efficient approximate search on string collections
Proceedings of the VLDB Endowment
A hash trie filter method for approximate string matching in genomic databases
Applied Intelligence
Can we beat the prefix filtering?: an adaptive framework for similarity join and search
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Efficient top-k algorithms for approximate substring matching
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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Approximate queries on string data are important due to the prevalence of such data in databases and various conventions and errors in string data. We present the VSol estimator, a novel technique for estimating the selectivity of approximate string queries. The VSol estimator is based on inverse strings and makes the performance of the selectivity estimator independent of the number of strings. To get inverse strings we decompose all database strings into overlapping substrings of length q (q-grams) and then associate each q-gram with its inverse string: the IDs of all strings that contain the q-gram. We use signatures to compress inverse strings, and clustering to group similar signatures. We study our technique analytically and experimentally. The space complexity of our estimator only depends on the number of neighborhoods in the database and the desired estimation error. The time to estimate the selectivity is independent of the number of database strings and linear with respect to the length of query string. We give a detailed empirical performance evaluation of our solution for synthetic and real-world datasets. We show that VSol is effective for large skewed databases of short strings.