Account manager virtual assistant using machine learning techniques
A method for machine learning-based account manager virtual assistant message processing includes receiving a message of a user, preprocessing the message to generate a normalized data set, analyzing the normalized data using a classification machine learning model, analyzing the normalized data using a deep learning machine learning model, generating a response based on the output of the first and second machine learning models, and transmitting the response to the user. An account manager virtual assistant computing system includes a processor and a memory storing instructions that cause the account manager virtual assistant system to receive a message from a user, process the message using a first machine learning model, process the message using a second machine learning model, when the message is a request for quote, generate a response and transmit the response to the user.
1. A computer-implemented method for automating tasks using machine learning-based account manager virtual assistant message processing, executed by at least one processor, comprising:
receiving, via an electronic network, a free-form electronic message of a user,
preprocessing the electronic message to generate a normalized extracted data set,
analyzing the normalized extracted data using a trained classification machine learning model to generate a classification data set,
analyzing the normalized extracted data using a trained information extraction machine learning model to generate an information extraction data set,
wherein the trained information extraction machine learning model is a deep learning model trained using a matrix of values corresponding to a curated training data set of normalized messages
and wherein each respective normalized message is associated with a plurality of labels, each indicating the presence, in the normalized message, of a respective item and a respective quantity,
generating, based on the information extraction data set and the classification data set, a response; and
transmitting, via an electronic network, the response to the user in a response electronic message.
2. The computer-implemented method of claim 1 wherein preprocessing the electronic message to generate a normalized extracted data set includes determining whether the user is a customer or an account manager.
3. The computer-implemented method of claim 2 , wherein transmitting the response to the user includes transmitting the response to an account manager associated with an account of the customer.
4. The computer-implemented method of claim 3 , further comprising:
receiving, from the account manager, an indication that the response is complete, and
transmitting the response to a customer associated with the response.
5. The computer-implemented method of claim 1 wherein the electronic message from the user is an email.
6. The computer-implemented method of claim 1 wherein the training of the trained information extraction machine learning model includes tokenizing the electronic message character-by-character.
7. The computer-implemented method of claim 1 wherein the classification machine learning model is a random forest classifier.
8. The computer-implemented method of claim 1 wherein training the classification machine learning model includes analyzing a training data set including one or more electronic message, each electronic message including a label, an original message text, a normalized message text, and an indication of quotation language.
9. The computer-implemented method of claim 1 further comprising:
retrieving, when the classification data set indicates that the electronic message includes a request for quote, item information corresponding to at least one item in the information extraction data set.
10. The computer-implemented method of claim 1 further comprising:
when the classification data set indicates that the electronic message does not include a request for quote,
mapping a customer identifier to a customer email address.