Machine-learning classifiers for logographic name matching in public health applications: approaches for incorporating phonetic, visual, and keystroke similarity in large-scale probabilistic record linkage

7 Jan 2020Philip A. CollenderZhiyue Tom HuCharles LiQu ChengXintong LiYue YouSong LiangChanghong YangJustin V. Remais

Approximate string-matching methods to account for complex variation in highly discriminatory text fields, such as personal names, can enhance probabilistic record linkage. However, discriminating between matching and non-matching strings is challenging for logographic scripts, where similarities in pronunciation, appearance, or keystroke sequence are not directly encoded in the string data... (read more)

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