Intelligent generation of job profiles

A computing device comprising:

• one or more non-transitory machine-readable mediums configured to store instructions;
• and
• one or more processors configured to execute the instructions stored on the one or more non-transitory machine-readable mediums, wherein execution of the instructions causes the one or more processors to carry out a process comprising:
• building a machine learning (ML) model by:
• generating a modeling dataset from a text corpus and a sentiment corpus using a natural language process, wherein the modeling dataset comprises a plurality of training samples, each training sample including feature values derived from the text corpus and the sentiment corpus and a corresponding job-profile text sequence;
• implementing through a recurrent neural network a unidirectional long short-term memory model;
• and
• training the unidirectional long short-term memory model to generate job profile text using a plurality of training samples, the plurality of training samples generated from the modeling dataset;
• receiving activity data corresponding to activities of an employee over a period of time;
• deriving from the activity data context and information by organizing the activity data into an activity graph and generating, from the activity graph, the context and information, the context and information comprising an intent derived using a first bidirectional long short-term memory model and a sentiment derived using a second bidirectional long short-term memory model, wherein the first and second bidirectional long short-term memory models process sequences of tokens in both forward and backward directions using the activity graph to derive the intent and the sentiment, thereby improving a contextual representation of the activity data used by the machine learning model;
• associating the context and information to a job position;
• storing the context and information within a personal knowledge repository;
• and
• responsive to a request to generate a job profile for the job position:
• retrieving, from the repository, the context and information associated with the job position;
• inputting the context and information to the ML model-to-generate;
• and
• generating from the ML model a job profile text.

A computer-implemented method for generating job-profile text using a trained neural network, the method comprising:

• building, by a computing device, a machine-learning (ML) model implemented as a recurrent neural network comprising a unidirectional long short-term memory (LSTM) layer and configured to generate job-profile text, the building comprising:
• generating, using natural language processing, a modeling dataset from a text corpus and a sentiment corpus;
• and
• training the recurrent neural network using training samples from the modeling dataset;
• receiving, by the computing device, activity data corresponding to activities of an employee over a period of time;
• deriving, by the computing device, context and information from the activity data, the deriving comprising organizing the activity data into an activity graph and generating, from the activity graph, feature values including an intent value derived using a first bidirectional LSTM model and a sentiment value derived using a second bidirectional LSTM model, wherein the first and second bidirectional long short-term memory models process sequences of tokens in both forward and backward directions using the activity graph to derive the intent and the sentiment, thereby improving a contextual representation of the activity data used by the machine learning model;
• associating, by the computing device, the context and information with a job position;
• storing, by the computing device, the context and information in a personal knowledge repository implemented using non-transitory computer-readable storage and maintained in association with the job position;
• and
• in response to receiving, by the computing device, a request to generate a job profile for the job position:
• retrieving, from the personal knowledge repository, the context and information associated with the job position;
• providing the context and information as input to the trained recurrent neural network;
• and
• generating, by the trained recurrent neural network, job-profile text for the job position based on the context and information.