Name
Abstract | ||
|---|---|---|
Schema and record matching are tools to integrate files or databases. Record linkage is one of the tools used to link those records that while belonging to different files correspond to the same individual. Standard record linkage methods are applied when the records of both files are described using the same variables. One of the non-standard record linkage methods corresponds to the case when files are not described using the same variables. In this paper we study record linkage for non common variables. In particular, we use a supervised approach based on neural networks. We use a neural network to find the relationships between variables. Then, we use these relationships to translate the information in the domain of one file into the domain of the other file. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11681960_25 | MDAI |
Keywords | Field | DocType |
standard record linkage method,non common variable,record linkage,neural network,different file,re-identification problem,record matching,new approach,supervised approach,non-standard record linkage method,information privacy,database integration,data mining | Data integration,Record linkage,Data mining,Computer science,Decision support system,Artificial intelligence,Artificial neural network,Information privacy,Schema (psychology),Data link,Machine learning,Parameter identification problem | Conference |
Volume | ISSN | ISBN |
3885 | 0302-9743 | 3-540-32780-0 |
Citations | PageRank | References |
1 | 0.35 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jordi Nin | 1 | 311 | 26.53 |
| Vicenç Torra | 2 | 2666 | 234.27 |