Systems and methods for skills inference using a datastore and models
AssigneeEmpath, Inc.
InventorsAdam Blum, Vladislav Khizanov
Life of this patent
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Abstract
A system comprising: a skills data store; an employee action data store; at least one hardware processor; and one or more software modules that are configured to, when executed by the at least one hardware processor, retrieve skills data and employee action data from the skills data store and employee action data store, train a classification model, wherein training a classification model comprises performing feature preprocessing, generating an LDA topic vector and TF/IDF Word2Vec similarity scoring, and use AutoML to train ML models, and infer employee skills and levels based on the classification model and employee action data.
Claims1
A system comprising:
- a skills data store;
- an employee action data store;
- at least one hardware processor;
- and
- one or more software modules that are configured to, when executed by the at least one hardware processor,
- retrieve skills data and employee action data from the skills data store and employee action data store,
- train a classification model, wherein training a classification model comprises performing feature preprocessing, generating an LDA topic vector and TF/IDF Word2Vec similarity scoring, and use AutoML to train ML models, and
- infer employee skills and levels based on the classification model and employee action data.
Dependencies are inferred from the claim text.