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Due to the characteristics of the data in public databases, it is difficult to clean the redundant data. It is an ideal solution to make full use of the features of original data to perform technical data cleaning. The entity identification technology is one of the effective solutions. Based on the key technologies of entity identification, combining the characteristics of the Chinese text data of Chinese public databases and the network relationships existing in the data, an entity identification framework based on text clustering and social network community division was proposed for the challenges with the same representation of different entities. The framework has been experimented on China's library database. Experimental results show the validity and accuracy of the framework.
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