Calculating a degree of match for a plurality of career options

Patent metadata

Field	Value
Publication number	US-2020294166-A1
Application number	US-201916353794-A
Country	US
Kind code	A1
Filing date	Mar 14, 2019
Priority date	Mar 14, 2019
Publication date	Sep 17, 2020
Grant date	—

Abstract

A computer-implemented method provides career options and comprising classifying, by an academic classification module, each of a plurality of academic subjects into a plurality of topics and classifying, by a career classification module, each of a plurality of career options as comprising a plurality of topics. The method comprises determining, by a grading module, for a student, a grade associated with each topic for each subject and calculating, by a prediction module, a degree of match for each career option for the student, the degree of match based on each topic which comprises the career option weighted according to the grade associated therewith.

First claim

What is claimed is:

1 . A computer-implemented method for providing career options, the method comprising:
provisioning, by an academic classification module, each of a plurality of academic subjects into a plurality of topics; provisioning, by a career classification module, each of a plurality of career options as comprising a plurality of topics; determining, by a grading module, for a student, a grade associated with each topic for each subject; and calculating, by a prediction module, a degree of match for each career option for the student, the degree of match based on each topic which comprises the career option weighted according to the grade associated therewith.

2 . The method according to claim 1 , further comprising:
providing, by the prediction module, at least one recommended career option based on the degree of match.

3 . The method according to claim 1 , wherein:
each of the plurality of topics comprising each career option has a significance weighting associated therewith; and the method comprises calculating, by the prediction module, the degree of match for each career option based on both the grade associated with each topic and the significance weighting associated with each topic.

4 . The method according to claim 1 , further comprising:
characterizing, by the career classification module, each career option with at least one characterization metric; receiving a user input from the student indicative of career characterization preferences; and calculating, by the prediction module, the degree of match for each career option based additionally on a degree of correspondence between the characterization metric and the career characterization preferences.

5 . The method according to claim 1 , further comprising:
characterizing, by the career classification module, each career option with at least one social metric; receiving an input indicative of social preferences of the student; and calculating, by the prediction module, the degree of match for each career option based additionally on a degree of correspondence between the social metric and the social preferences.

6 . The method according to claim 1 , further comprising:
characterizing, by the career classification module, each career option with at least one metric related to basic personal and medical data and/or immediate family career information; receiving an input indicative of basic personal and medical data and/or immediate family career information of the student; and calculating, by the prediction module, the degree of match for each career option based additionally on a degree of correspondence between basic personal and medical data and/or immediate family career information.

7 . The method according to claim 1 , further comprising:
classifying, by the career classification module, a degree of obsolescence risk which faces each career option; and indicating, by the prediction module, the degree of obsolescence risk which faces each career option.

8 . The method according to claim 7 , further comprising revising, by the prediction module, the degree of match for each career option based on the degree of obsolescence risk.

9 . The method according to claim 1 , further comprising:
receiving, from the student, data indicative of a chosen career; comparing, by the prediction module, the chosen career against the career options; and updating, by the career classification module, the career options based on the comparison with the data indicative of the chosen career.

10 . A computer system for providing career options, the computer system comprising:
a computer processor; and a computer readable storage medium having stored thereon program instructions executable by the computer processor to direct the operation of the processor, wherein the computer processor, when executing the program instructions, comprises:
an academic classification module configured to provision each of a plurality of academic subjects into a plurality of topics;
a career classification module configured to provision each of a plurality of career options as comprising a plurality of topics;
a grading module configured to determine, for a student, a grade associated with each topic for each subject; and
a prediction module configured to calculate a degree of match for each career option for the student, the degree of match based on each topic which comprises the career option weighted according to the grade associated therewith.

11 . The computer system according to claim 10 , wherein the prediction module is configured to provide at least one recommended career option based on the degree of match.

12 . The computer system according to claim 10 , wherein:
each of the plurality of topics comprising each career option has a significance weighting associated therewith; and the prediction module is configured to calculate the degree of match for each career option based on both the grade associated with each topic and the significance weighting associated with each topic.

13 . The computer system according to claim 10 , wherein:
the career classification module is configured to characterize each career option with at least one characterization metric; and the prediction module is configured to calculate the degree of match for each career option based additionally on a degree of correspondence between the characterization metric and career characterization preferences indicated by a user input from the student.

14 . The computer system according to claim 10 , wherein:
the career classification module is configured to characterize each career option with at least one social metric; and the prediction module is configured to calculate the degree of match for each career option based additionally on a degree of correspondence between the social metric and social preferences of the student.

15 . The computer system according to claim 10 , wherein:
the career classification module is configured to characterize each career option with at least one metric related to basic personal and medical data and/or immediate family career information; and the prediction module is configured to calculate the degree of match for each career option based additionally on a degree of correspondence between the metric related to basic personal and medical data and/or immediate family career information and basic personal and medical data and/or immediate family career information of the student.

16 . The computer system according to claim 10 , wherein:
the career classification module is configured to classify a degree of obsolescence risk which faces each career option; and the prediction module is configured to indicate the degree of obsolescence risk which faces each career option.

17 . The computer system according to claim 10 , wherein the prediction module is configured to revive the degree of match for each career option based on the degree of obsolescence risk.

18 . The computer system according to claim 10 , wherein:
the prediction module is configured to compare data indicative of a chosen career of the student with career options; and the career classification module is configured to update the career options based on the comparison with the data indicative of the chosen career.

19 . A computer program product for providing career options, the computer program product comprising:
a computer-readable medium having stored thereon:
first program instructions executable by a computer processor to cause the

Assignees

• IBM

Inventors

• Vos Etienne Eben
• Magadla Matokollo
• Nchabeleng Mathibele Willy

Classifications

• G06N20/00

  Machine learning · CPC title

• G06N3/006

  based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] · CPC title

• G06Q50/205 Primary

  Education administration or guidance · CPC title

• G06N5/02

  Knowledge representation; Symbolic representation · CPC title