Efficient Merging and Filtering Algorithms for Approximate String Searches
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Efficient approximate entity extraction with edit distance constraints
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Bed-tree: an all-purpose index structure for string similarity search based on edit distance
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Faerie: efficient filtering algorithms for approximate dictionary-based entity extraction
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Pass-join: a partition-based method for similarity joins
Proceedings of the VLDB Endowment
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
An Efficient Trie-based Method for Approximate Entity Extraction with Edit-Distance Constraints
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
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This paper serves as a report for the participation of Special Interest Group In Data (SIGDATA), Indian Institute of Technology, Kanpur in the String Similarity Workshop, EDBT, 2013. We present a novel technique to efficiently process edit distance based string similarity queries. Our technique draws upon some previously conducted works in the field and introduces new methods to tackle the issues therein. We focus on achieving minimum possible execution time while being rather liberal with memory consumption. We propose and support the use of deletion neighborhoods for fast edit distance lookups in dictionaries. Our work emphasizes the power of deletion neighborhoods over other popular finger print based schemes for similarity search queries. Furthermore, we establish that it is possible to reduce the large space requirement of a deletion neighborhood based finger print scheme using simple hashing techniques, thereby making the scheme suitable for practical application. We compare our implementation with the state of the art libraries (Flamingo) and report speed ups of up to an order of magnitude.