Abstract:
Accuracy is critical when multiple databases are merged into a single system, because an error in a single record could lead to multiple mismatches. Address normalization...Show MoreMetadata
Abstract:
Accuracy is critical when multiple databases are merged into a single system, because an error in a single record could lead to multiple mismatches. Address normalization is fairly common in database merging. We have developed a system to accurately and efficiently normalize mailing addresses. However, our system differs from other neural network architectures. Its key ingredients are an address dictionary and a scoring system. The scoring system is based on analog neural network systems, but the address dictionary follows a digital approach. The two key processes in our system are learning and address normalization. Learning is further split into dictionary creation updating and system parameters training.<>
Published in: IEEE Expert ( Volume: 9, Issue: 6, December 1994)
DOI: 10.1109/64.363266
Citations are not available for this document.
Cites in Patents (3)Patent Links Provided by 1790 Analytics
1.
Xiong, Jun, "Text address processing method and apparatus"
Inventors:
Xiong, Jun
Abstract:
The present application provides text address processing methods and apparatuses. Some method embodiments include: determining, according to social relation circles of users in a service system, at least one address set, each address set including at least two original text addresses; and performing, for each address set, normalization processing on original text addresses in the address set, to obtain a target text address corresponding to the address set. Some embodiments of the present application divides to-be-normalized original text addresses according to social relation circles of users, which, on one hand, is equivalent to reducing the range of the to-be-normalized original text addresses, and on the other hand, is equivalent to locking the normalization of text addresses between text addresses having an association. Therefore, it may be easier to control a fault-tolerant boundary between the text addresses, and may be conducive to improving accuracy of the normalization result.
Assignee:
ALIBABA GROUP HOLDING LTD
Filing Date:
11 August 2017
Grant Date:
06 October 2020
Patent Classes:
Current International Class:
G06F0169570000, G06F0160000000, G06F0169500000, G06F0401000000
2.
Gundersen, Mark A.; DeGiule, Michael A.; Niang, Muhammad Al-Amin, "Address database reconciliation"
Inventors:
Gundersen, Mark A.; DeGiule, Michael A.; Niang, Muhammad Al-Amin
Abstract:
Methods for reconciling an address database include comparing addresses in an update database to addresses in a production database. A second comparison of unique addresses from the first comparison is executed, the second comparison allowing matching of addresses that the first comparison did not match.
Assignee:
VALASSIS DIRECT MAIL INC
Filing Date:
03 July 2007
Grant Date:
26 June 2018
Patent Classes:
Current International Class:
G06F0070000000, G06F0173000000, G06F0170000000
3.
Salcedo, Jonathan, "Method and apparatus for identifying and resolving conflicting data records"
Inventors:
Salcedo, Jonathan
Abstract:
A method and apparatus for identifying and resolving conflicting data records are disclosed. The individual data fields of a master record are compared with the corresponding data fields of each source record in a particular data set. For each, one of various matching algorithms is used to assign a field matching score indicating the extent to which the data in the two data fields matches. The particular algorithm used to determine the extent of a match and to assign the corresponding score is dependent on the type of the data field. Once all of the data fields for a particular source record have been analyzed, the sum of the field matching scores is tallied to determine an overall record matching score for that particular source record.
Assignee:
ASURION LLC
Filing Date:
05 March 2012
Grant Date:
24 February 2015
Patent Classes:
Current U.S. Class:
707780000, 707610000
Current International Class:
G06F0173000000
