Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Data cleaning in microsoft SQL server 2005
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
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
Transformation-based Framework for Record Matching
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
Efficient approximate search on string collections
Proceedings of the VLDB Endowment
Learning top-k transformation rules
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
| Hi-index | 0.00 |
Today's record matching infrastructure does not allow a flexible way to account for synonyms such as "Robert" and "Bob" which refer to the same name, and more general forms of string transformations such as abbreviations. We expand the problem of record matching to take such user-defined string transformations as input. These transformations coupled with an underlying similarity function are used to define the similarity between two strings. We demonstrate the effectiveness of this approach via a fuzzy match operation that is used to lookup an input record against a table of records, where we have an additional table of transformations as input. We demonstrate an improvement in record matching quality and efficient retrieval based on our index structure that is cognizant of transformations.