[Objective] This paper tries to automatically finish the disambiguation of author names in institutional repositories, and then provide human intervention mechanism at the right time. [Methods] First, we analyzed the unqiue features of the author name disambiguation. Then, we constructed a general disambiguation framework for the institutional repository. [Results] Our framework achieved good results in practice with more than 99% of precision. [Limitations] We did not examine the author names without affiliation addresses, and there may be exceptions in the alias of authors and institutions. [Conclusions] This framework could effectively disambiguate author names in institutional repositories, which helps us provide more value-added services.
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上海科技大学知识管理系统[EB/OL]. [2018-02-20]. .(ShanghaiTech University Knowledge Management System)[EB/OL]. [2018-02-20].