SKILL-BASED TITLE PREDICTION MODEL
First Claim
1. A system comprising:
- a computer-readable medium having instructions stored thereon, which, when executed by a processor, cause the system to;
for each of a plurality of different titles in a social network structure, map the title into a first vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure;
store the first vector for each of the plurality of different titles in a deep representation data structure;
for each of a plurality of different skills in a social network structure, map the skill into a second vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure;
store the second vector for each of the plurality of different skills in the deep representation data structure;
apply one or more objective functions to at least one combination of first vectors and second vectors in the deep representation data structure, causing an objective function output for each of the at least one combination;
perform an optimization test on each of the at least one combination using a corresponding objective function output for each of the at least one combination;
determine, for each of the at least one combination of two or more of the vectors, whether the combination passed the optimization test; and
for any combination that did not pass the optimization test, alter one or more coordinates for the vectors in the combination so that the vectors in the combination become closer together within an n-dimensional space.
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Accused Products
Abstract
In an example embodiment, for each of a plurality of different titles in a social network structure, the title is mapped into a first vector having n coordinates, while kills are mapped into a second vector having n coordinates. The first and second vectors are stored in a deep representation data structure. One or more objective functions are applied to at least one combination of two or more of the vectors in the deep representation data structure. Then, an optimization test on each of the at least one combination is performed using a corresponding objective function output for each of the at least one combination of two or more of the vectors, and, for any combination that did not pass the optimization test, one or more coordinates for the vectors in the combination are altered so that the vectors in the combination become closer together within an n-dimensional space.
12 Citations
20 Claims
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1. A system comprising:
a computer-readable medium having instructions stored thereon, which, when executed by a processor, cause the system to; for each of a plurality of different titles in a social network structure, map the title into a first vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; store the first vector for each of the plurality of different titles in a deep representation data structure; for each of a plurality of different skills in a social network structure, map the skill into a second vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; store the second vector for each of the plurality of different skills in the deep representation data structure; apply one or more objective functions to at least one combination of first vectors and second vectors in the deep representation data structure, causing an objective function output for each of the at least one combination; perform an optimization test on each of the at least one combination using a corresponding objective function output for each of the at least one combination; determine, for each of the at least one combination of two or more of the vectors, whether the combination passed the optimization test; and for any combination that did not pass the optimization test, alter one or more coordinates for the vectors in the combination so that the vectors in the combination become closer together within an n-dimensional space. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer-implemented method, comprising:
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for each of a plurality of different titles in a social network structure, mapping the title into a first vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; storing the first vector for each of the plurality of different titles in a deep representation data structure; for each of a plurality of different skills in a social network structure, mapping the skill into a second vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; storing the second vector for each of the plurality of different skills in the deep representation data structure; applying one or more objective functions to at least one combination of first vectors and second vectors in the deep representation data structure, causing an objective function output for each of the at least one combination; performing an optimization test on each of the at least one combination using a corresponding objective function output for each of the at least one combination; determining, for each of the at least one combination of two or more of the vectors, whether the combination passed the optimization test; and for any combination that did not pass the optimization test, altering one or more coordinates for the vectors in the combination so that the vectors in the combination become closer together within an n-dimensional space. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations comprising:
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for each of a plurality of different titles in a social network structure, mapping the title into a first vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; storing the first vector for each of the plurality of different titles in a deep representation data structure; for each of a plurality of different skills in a social network structure, mapping the skill into a second vector having n coordinates, wherein a value for each of the n coordinates is selected randomly from a preset range, wherein each title is a standardized value for a title in the social network structure; storing the second vector for each of the plurality of different skills in the deep representation data structure; applying one or more objective functions to at least one combination of first vectors and second vectors in the deep representation data structure, causing an objective function output for each of the at least one combination; performing an optimization test on each of the at least one combination using a corresponding objective function output for each of the at least one combination; determining, for each of the at least one combination of two or more of the vectors, whether the combination passed the optimization test; and for any combination that did not pass the optimization test, altering one or more coordinates for the vectors in the combination so that the vectors in the combination become closer together within an n-dimensional space. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification