Name segmentation using hidden Markov models and its application in record linkage

Cadernos de Saúde Pública

Rita De Cassia Braga Gonçalves¹  Sergio Miranda Freire¹ 

关键词: Markov Chains;    Information Systems;    Database;    Cadenas de Markov;    Sistemas de Información;    Base de Datos;    Cadeias de Markov;    Sistemas de Informação;    Base de Dados;   

DOI  :  10.1590/0102-311X00191313

来源: SciELO

【 摘 要 】

This study aimed to evaluate the use of hidden Markov models (HMM) for the segmentation of person names and its influence on record linkage. A HMM was applied to the segmentation of patient’s and mother’s names in the databases of the Mortality Information System (SIM), Information Subsystem for High Complexity Procedures (APAC), and Hospital Information System (AIH). A sample of 200 patients from each database was segmented via HMM, and the results were compared to those from segmentation by the authors. The APAC-SIM and APAC-AIH databases were linked using three different segmentation strategies, one of which used HMM. Conformity of segmentation via HMM varied from 90.5% to 92.5%. The different segmentation strategies yielded similar results in the record linkage process. This study suggests that segmentation of Brazilian names via HMM is no more effective than traditional segmentation approaches in the linkage process.

【 授权许可】

CC BY   
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