Abstract: Linguistic schema mapping via semi-supervised learning is used to map a customer schema to a particular industry-specific schema (ISS). The customer schema is received and a corresponding ISS is identified. An attribute in the customer schema is selected for labeling. Candidate pairs are generated that include the first attribute and one or more second attributes which may describe the first attribute. A featurizer determines similarities between the first attribute and second attribute in each generated pair, one or more suggested labels are generated by a machine learning (ML) model, and one of the suggested labels is applied to the first attribute.

Abstract: The present invention discloses an intravenous cytomegalovirus human immune globulin and a manufacturing method thereof, wherein the technical problem to be solved is to improve the purity, yield, and safety of the product. The intravenous cytomegalovirus human immune globulin of the present invention has a specific activity of no less than 2.5 PEI-U/mg, an anti-CMV titer of no less than 100 PEI-U/ml, a purity of greater than 98.2%, and a protein content of 51˜55 mg/ml.