Systems and methods to rank job candidates based on machine learning model
First Claim
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1. A computer-implemented method comprising:
- determining, by a computing system, a training set for a machine learning model, wherein the training set includes employees of an organization who are users of a social networking system;
determining, by the computing system, a feature set associated with each member of the training set, wherein features in the feature set and their associated values are provided by the social networking system;
training, by the computing system, the machine learning model based on feature sets associated with members in the training set;
receiving, by the computing system, an indication provided by an employee of an organization through a user interface to identify job candidates for the organization;
determining, by the computing system, a plurality of connections of the employee of the organization on the social networking system;
determining, by the computing system, using the machine learning model, a score reflecting a probability that each of the plurality of connections of the employee is qualified for employment with the organization; and
ranking, by the computing system, the plurality of connections based on the score determined for each connection.
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Abstract
Systems, methods, and non-transitory computer readable media are configured to determine a training set to train a machine learning model. A feature set for the model is determined. The model is trained based on the training set and the feature set to determine a score reflecting a probability that each user in an evaluation set of users is qualified for employment with an organization. A ranking of users in the evaluation set is provided based on the score determined for each user.
10 Citations
20 Claims
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1. A computer-implemented method comprising:
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determining, by a computing system, a training set for a machine learning model, wherein the training set includes employees of an organization who are users of a social networking system; determining, by the computing system, a feature set associated with each member of the training set, wherein features in the feature set and their associated values are provided by the social networking system; training, by the computing system, the machine learning model based on feature sets associated with members in the training set; receiving, by the computing system, an indication provided by an employee of an organization through a user interface to identify job candidates for the organization; determining, by the computing system, a plurality of connections of the employee of the organization on the social networking system; determining, by the computing system, using the machine learning model, a score reflecting a probability that each of the plurality of connections of the employee is qualified for employment with the organization; and ranking, by the computing system, the plurality of connections based on the score determined for each connection. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system comprising:
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at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the system to perform; determining a training set for a machine learning model, wherein the training set includes employees of an organization who are users of a social networking system; determining a feature set associated with each member of the training set wherein features in the feature set and their associated values are provided by the social networking system; training the machine learning model based on feature sets associated with members in the training set; receiving an indication provided by an employee of an organization through a user interface to identify job candidates for the organization; determining a plurality of connections of the employee of the organization on the social networking system; determining, using the machine learning model, a score reflecting a probability that each of the plurality of connections of the employee is qualified for employment with the organization; and ranking the plurality of connections based on the score determined for each connection. - View Dependent Claims (14, 15, 16)
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17. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:
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determining a training set for a machine learning model, wherein the training set includes employees of an organization who are users of a social networking system; determining a feature set associated with each member of the training set wherein features in the feature set and their associated values are provided by the social networking system; training the machine learning model based on feature sets associated with members in the training set; receiving an indication provided by an employee of an organization through a user interface to identify job candidates for the organization; determining a plurality of connections of the employee of the organization on the social networking system; determining, using the machine learning model, a score reflecting a probability that each of the plurality of connections of the employee is qualified for employment with the organization; and ranking the plurality of connections based on the score determined for each connection. - View Dependent Claims (18, 19, 20)
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Specification