Estimating alphanumeric selectivity in the presence of wildcards
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Substring selectivity estimation
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Approximate String Joins in a Database (Almost) for Free
Proceedings of the 27th International Conference on Very Large Data Bases
Robust and efficient fuzzy match for online data cleaning
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Selectivity Estimation for String Predicates: Overcoming the Underestimation Problem
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Efficient set joins on similarity predicates
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Indexing text data under space constraints
Proceedings of the thirteenth ACM international conference on Information and knowledge management
n-gram/2L: a space and time efficient two-level n-gram inverted index structure
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Selectivity estimation for fuzzy string predicates in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
q-Gram Matching Using Tree Models
IEEE Transactions on Knowledge and Data Engineering
A Primitive Operator for Similarity Joins in Data Cleaning
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Record linkage: similarity measures and algorithms
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Efficient exact set-similarity joins
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Estimating the selectivity of approximate string queries
ACM Transactions on Database Systems (TODS)
Scaling up all pairs similarity search
Proceedings of the 16th international conference on World Wide Web
Extending q-grams to estimate selectivity of string matching with low edit distance
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient Merging and Filtering Algorithms for Approximate String Searches
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Improving "email speech acts" analysis via n-gram selection
ACTS '09 Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech
Efficient top-k count queries over imprecise duplicates
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Incremental maintenance of length normalized indexes for approximate string matching
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Efficient approximate entity extraction with edit distance constraints
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Space-economical partial gram indices for exact substring matching
Proceedings of the 18th ACM conference on Information and knowledge management
Efficient approximate search on string collections
Proceedings of the VLDB Endowment
Reference-based alignment in large sequence databases
Proceedings of the VLDB Endowment
SimDB: a similarity-aware database system
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Approximate entity extraction in temporal databases
World Wide Web
Foundations and Trends in Databases
WHAM: a high-throughput sequence alignment method
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficient exact edit similarity query processing with the asymmetric signature scheme
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficient similarity joins for near-duplicate detection
ACM Transactions on Database Systems (TODS)
A fast and accurate method for approximate string search
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Efficient fuzzy full-text type-ahead search
The VLDB Journal — The International Journal on Very Large Data Bases
A generic framework for efficient and effective subsequence retrieval
Proceedings of the VLDB Endowment
Efficient range queries over uncertain strings
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
WHAM: A High-Throughput Sequence Alignment Method
ACM Transactions on Database Systems (TODS)
Proceedings of the Joint EDBT/ICDT 2013 Workshops
FPI: a novel indexing method using frequent patterns for approximate string searches
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Cache-aware parallel approximate matching and join algorithms using BWT
Proceedings of the Joint EDBT/ICDT 2013 Workshops
LinkIT: privacy preserving record linkage and integration via transformations
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
A partition-based method for string similarity joins with edit-distance constraints
ACM Transactions on Database Systems (TODS)
Similarity queries: their conceptual evaluation, transformations, and processing
The VLDB Journal — The International Journal on Very Large Data Bases
Asymmetric signature schemes for efficient exact edit similarity query processing
ACM Transactions on Database Systems (TODS)
Data & Knowledge Engineering
Leveraging spatial join for robust tuple extraction from web pages
Information Sciences: an International Journal
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Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in data as well as queries. Several existing algorithms use the concept of "grams," which are substrings of strings used as signatures for the strings to build index structures. A recently proposed technique, called VGRAM, improves the performance of these algorithms by using a carefully chosen dictionary of variable-length grams based on their requencies in the string collection. Since an index structure using fixed-length grams can be viewed as a special case of VGRAM, a fundamental problem arises naturally: what is the relationship between the gram dictionary and the performance of queries? We study this problem in this paper. We propose a dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance. We analyze how a gram dictionary affects the index structure of the string collection and ultimately the performance of queries. We also propose an algorithm for automatically computing a dictionary of high-quality grams for a workload of queries. Our experiments on real data sets show the improvement on query performance achieved by these techniques. To our best knowledge, this study is the first cost-based quantitative approach to deciding good grams for approximate string queries.