Hybrid in-domain and out-of-domain document processing for non-vocabulary tokens of electronic documents
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United States of America Patent
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Nov 8, 2022
Grant Date -
May 27, 2021
app pub date -
Jan 13, 2020
filing date -
Nov 27, 2019
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Abstract
Techniques are described herein for training and evaluating machine learning (ML) models for document processing computing applications based on in-domain and out-of-domain characteristics. In some embodiments, an ML system is configured to form feature vectors by mapping unknown tokens to known tokens within a domain based, at least in part, on out-of-domain characteristics. In other embodiments, the ML system is configured to map the unknown tokens to an aggregate vector representation based on the out-of-domain characteristics. The ML system may use the feature vectors to train ML models and/or estimate unknown labels for the new documents.
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