Efficient algorithms for fast integration on large data sets from multiple sources.

ABSTRACT:

Background

Recent large scale deployments of health information technology have created opportunities for the integration of patient medical records with disparate public health, human service, and educational databases to provide comprehensive information related to health and development. Data integration techniques, which identify records belonging to the same individual that reside in multiple data sets, are essential to these efforts. Several algorithms have been proposed in the literatures that are adept in integrating records from two different datasets. Our algorithms are aimed at integrating multiple (in particular more than two) datasets efficiently.

Methods

Hierarchical clustering based solutions are used to integrate multiple (in particular more than two) dataset

SUBMITTER: Mi T 

PROVIDER: S-EPMC3439324 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature