Oracle International Corporation

Mengqing Guo

Jun Qian

Tao Sheng

Praneet Pabolu

Karan Dua

Jeaff Wang

Yazhe Hu

The system generates templates to be used for use in synthetic document generation. Generating a template includes selecting entities to be included in the template and/or selecting characteristics of entities in the template. The system may execute randomization functions to determine which entities, of a candidate set of entities, are to be included in a template. The randomization functions may accept, as input, probabilities associated with the entities to compute the inclusion or exclusion of entities in the template. Different entities may be associated with different corresponding probabilities. The system may execute randomization functions to determine characteristics of entities that are included in a template. The characteristics may be selected from a specific candidate set of characteristics or a range of characteristic values.

Generating templates for use in synthetic document generation processes

Techniques for multi-stage training of a machine learning model to extract key-value pairs from documents are disclosed. A system trains a machine learning model using a set of training data including unlabeled documents of various document categories. The initial stage identifies relationships among tokens, or words, numbers, and punctuation, in documents. The system re-trains the machine learning model using a set of training data which includes a particular category of documents while excluding other categories of documents. The second training stage is a supervised machine learning stage in which the training data is labeled to identify key-value pairs in the documents. In the initial training stage, the system sets parameters of the machine learning model to an initial state. In the second stage, the system modifies the parameters of the machine learning model based on the characteristics of the training data set including the documents of the particular category.

Multi-stage machine learning model training for key-value extraction

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Redmond, WA, United States of America

Mengqing Guo