Patent ID: 11934978
Assignee: EMPATH, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system comprising:
a skills data store comprising skill descriptions for a plurality of employees associated with a plurality of companies;
an employee action data store comprising employee action data for the plurality of employees;
at least one hardware processor; and
one or more software modules are configured to, when executed by the at least one hardware processor, for each of the plurality of companies and the plurality of employees associated therewith:
retrieve the skill descriptors and employee action data from the skills data store and employee action data store,
convert the skill descriptors and employee action data to topic vectors,
compare the employee action data to the skill descriptors using the topic vectors,
generate a maximum and average semantic similarity scores based on topic vector differences between the skill descriptors and employee action data;

based on the maximum and average semantic similarity scores associated with each of the plurality of companies, generate a classification model based on the maximum and average semantic similarity scores;
train the classification models based on known accurate employee to skill mappings, wherein training a classification models comprises performing acronym/synonym expansion, stemming/lemmatization, vectorizing text in order to generate an LDA topic vector model and TF/IDF Word2Vec similarity scoring model, and cosine similarity feature preprocessing,
infer employee skills and levels, for the plurality of employees, based on the classification model and employee action data;
present employees with related inferred employee skills generated using the classification model and receive confirmation or denials;
update and assess the classification model based on the confirmations or denials;
use the classification model to infer employee skills and levels for the plurality of employees as new employee action data is received over time;
track the accuracy of the classification model over time as new employee action data is received; and
automatically retrain the classification model when the tracking indicates that the classification model accuracy has degraded below a threshold.