System and method for career development

1 . 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.

2 . The computing system of claim 1 , wherein the information element associated with the user is a profile of the user, and the one or more search parameters include a biographical entry, a past and/or current job title, a degree level, a major, an experience level, and/or a skill level.

3 . The computing system of claim 1 , wherein the chatbot is further trained with search parameters associated with profiles of the real and/or hypothetical users compliant for use by one or more databases.

4 . The computing system of claim 1 , wherein:

the information element associated with the user includes a first set of activities of the user, and

to generate the career development suggestions, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to:

identify a second set of activities, from the first set of activities, as a profile of the user; and

generate, via the chatbot, the career development suggestions based upon the second set of activities.

5 . The computing system of claim 4 , wherein:

the first set of activities of the user includes a browsing history of the user, one or more social media posts of the user, a location history of the user, and/or travel history of the user; and

the second set of activities of the user includes a browsing history on job posts, a browsing history on professional contents, social media posts associated with an employer, a colleague, and/or a client of the user, social media posts associated with a professional activity and/or a volunteer activity, a location history during working hours of the user, and/or travel history associated with a workplace of the user.

6 . The computing system of claim 1 , wherein the career development suggestions are career options recommended for the user, skill improvements recommended for the user, and/or online courses and/or programs recommended for the user.

7 . The computing system of claim 6 , wherein the chatbot is further trained with career options associated with the information elements of the real and/or hypothetical users, skill improvement recommendations associated with the information elements of the real and/or hypothetical users, and search parameters associated with the information elements of the real and/or hypothetical users compliant for use by databases including online courses and/or programs.

8 . The computing system of claim 1 , wherein creating the first set of vectors associated with the first training data includes:

extracting text from documents;

splitting the text into semantic clusters; and

encoding the semantic clusters as the first set of vectors, wherein a distance between the first set of vectors depends on a relevance between the semantic clusters corresponding to the first set of vectors.

9 . The computing system of claim 8 , wherein encoding the semantic clusters as input vectors is further via a machine learning (ML) model comprising a plurality of parameters, the ML model being trained with articles comprising a plurality of semantic clusters, the plurality of parameters being iteratively updated during training.

10 . The computing system of claim 8 , wherein at least one of the semantic clusters is one or more words, a portion of a word, or a character.

11 . The computing system of claim 1 , wherein the one or more search parameters are indicative of one or more characteristics of the user, and generating the one or more search parameters includes causing the chatbot to:

encode the information element to generate first one or more vectors indicative of content of the writing sample;

generate, based upon the first one or more vectors, second one or more vectors indicative of the skill level of the user; and

decode the second one or more vectors to generate the parameter indicative of the skill level.

12 . 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.

13 . The computer-implemented method of claim 12 , wherein the information element associated with the user is a profile of the user, and the one or more search parameters include a biographical entry, a past and/or current job title, a degree level, a major, an experience level, and/or a skill level.

14 . The computer-implemented method of claim 12 , wherein the chatbot is further trained with search parameters associated with profiles of the real and/or hypothetical users compliant for use by one or more databases.

15 . The computer-implemented method of claim 12 , wherein the career development suggestions are career options recommended for the user, skill improvements recommended for the user, and/or online courses and/or programs recommended for the user.

16 . The computer-implemented method of claim 15 , wherein the chatbot is further trained with career options associated with the information elements of the real and/or hypothetical users, skill improvement recommendations associated with the information elements of the real and/or hypothetical users, and search parameters associated with the information elements of the real and/or hypothetical users compliant for use by databases including online courses and/or programs.

17 . 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.