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US 12,664,599 B2Granted
System and method for career development
AssigneeState Farm Mutual Automobile Insurance Company
InventorsRoss Wheeler, Jose Ivan Gutierrez, Lauren Mitchell, Anthony Welcome, Steve Amancha
Life of this patent
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Abstract
Apparatuses, systems, and methods are provided for career development are provided. The method comprises: (1) receiving, by one or more processors from a user device, an information element associated with a user; (2) generating, by the one or more processors via a chatbot, career development suggestions based upon the information element associated with the user; and/or (3) presenting, by the one or more processors to the user via the user device, the career development suggestions. The chatbot may implement a trained model.
Claims17
A computing system for generating accurate career development suggestions via a chatbot, comprising:
- one or more processors, and
- a non-transitory memory storing one or more instructions, the one or more instructions, when executed by the one or more processors, cause the one or more processors to:
- receive, from a user device, an information element associated with a user, the information element comprising a writing sample associated with the user;
- generate, via the chatbot, career development suggestions based upon the information element associated with the user, wherein generating the career development suggestions includes:
- evaluating, via the chatbot, the writing sample to generate a parameter indicative of a skill level of the user;
- based upon the information element associated with the user, generating, via the chatbot, one or more search parameters compliant for use by a particular database, wherein the one or more search parameters comprise the parameter indicative of the skill level of the user;
- transmitting, to the particular database, the one or more search parameters to cause the particular database to obtain a search result using the parameter;
- and
- generating the career development suggestions based upon the search result;
- and
- present, to the user via the user device, the career development suggestions,
- wherein the chatbot implements a trained model, wherein training the model includes:
- creating a first set of vectors associated with first training data;
- training the model in a first stage using the first set of vectors;
- creating a second set of vectors associated with second training data, wherein the second training data comprises information elements associated with real and/or hypothetical users, prompts for generating career suggestions, and career suggestions associated with the information elements and the prompts;
- and
- training the model in a second stage using the second set of vectors.
14 more elements
A computer-implemented method for generating accurate career development suggestions via a chatbot, comprising:
- receiving, by one or more processors from a user device, an information element associated with a user, the information element comprising a writing sample associated with the user;
- generating, by the one or more processors via the chatbot, career development suggestions based upon the information element associated with the user, wherein generating the career development suggestions includes:
- evaluating, via the chatbot, the writing sample to generate a parameter indicative of a skill level of the user;
- based upon the information element associated with the user, generating, via the chatbot, one or more search parameters compliant for use by a particular database, wherein the one or more search parameters comprise the parameter indicative of the skill level of the user;
- transmitting, to the particular database, the one or more search parameters to cause the particular database to obtain a search result using the parameter;
- and
- generating the career development suggestions based upon the search result;
- and
- presenting, by the one or more processors to the user via the user device, the career development suggestions,
- wherein the chatbot implements a trained model, wherein training the model includes:
- creating a first set of vectors associated with first training data;
- training the model in a first stage using the first set of vectors;
- creating a second set of vectors associated with second training data, wherein the second training data comprises information elements associated with real and/or hypothetical users, prompts for generating career suggestions, and career suggestions associated with the information elements and the prompts;
- and
- training the model in a second stage using the second set of vectors.
12 more elements
A non-transitory computer-readable storage medium storing computer-readable instructions for generating accurate career development suggestions via a chatbot, wherein the computer-readable instructions, when executed on one or more processors of a user device, cause the one or more processors to:
- receive, from a user device, an information element associated with a user, the information element comprises a writing sample associated with the user;
- generate, via the chatbot, career development suggestions based upon the information element associated with the user, wherein generating the career development suggestions includes:
- evaluating, via the chatbot, the writing sample to generate a parameter indicative of a skill level of the user;
- based upon the information element associated with the user, generating, via the chatbot, one or more search parameters compliant for use by a particular database, wherein the one or more search parameters comprise the parameter indicative of the skill level of the user;
- transmitting, to the particular database, the one or more search parameters to cause the particular database to obtain a search result using the parameter;
- and
- generating the career development suggestions based upon the search result;
- and
- present, to the user via the user device, the career development suggestions,
- wherein the chatbot implements a trained model, wherein training the model includes:
- creating a first set of vectors associated with first training data;
- training the model in a first stage using the first set of vectors;
- creating a second set of vectors associated with second training data, wherein the second training data comprises information elements associated with real and/or hypothetical users, prompts for generating career suggestions, and career suggestions associated with the information elements and the prompts;
- and
- training the model in a second stage using the second set of vectors.
12 more elements
Dependencies are inferred from the claim text.