Record linkage, in a genealogical context, is the process of identifying individuals from multiple sources which refer to the same real-world entity. Current solutions focus on the individuals in question and on complex rules developed by human experts. Genealogical databases are highly-structured with relationships existing between the individuals and other instances. These relationships can be utilized and human involvement greatly minimized by using a filtered structured neural network. These neural networks, using traditional back-propagation methods, are biased in a way to make the network human readable. The results show an increase in precision and recall when pedigree data is available and used.
Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-1481 |
Date | 10 July 2006 |
Creators | Pixton, Burdette N. |
Publisher | BYU ScholarsArchive |
Source Sets | Brigham Young University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | http://lib.byu.edu/about/copyright/ |
Page generated in 0.0018 seconds