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IDENTITY RESOLUTION IN BIG, NOISY, AND/OR UNSTRUCTURED DATA
IDENTITY RESOLUTION IN BIG, NOISY, AND/OR UNSTRUCTURED DATA
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机译:大数据,嘈杂数据和/或非结构化数据中的身份解析
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摘要
In an environment containing big data, noisy data, and/or unstructured data, it is desirable to identify an entity referenced by input data. The entity can be identified by generating records corresponding to characteristics of the entity based on the input data. These records can be merged when it is determined that more than one record corresponds to the same entity. By doing so it is possible to more easily identify and classify information related to an entity, though such information may have been obtained in a manner that might otherwise be deemed unstructured or noisy. The method can be applied across large sets of data (“big data”) to obtain meaning from data that may otherwise be unclassifiable to a human observer.
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