IP Library › Granted Patent US 10,657,331
Granted Patent B2
US 10,657,331 · App. 15/266,209 · Granted May 19, 2020

Dynamic candidate expectation prediction

Inventors: Sivakumar Avkd (Visakhapatnam, IN); Ravi T. Vadlamani (Visakhapatnam, IN)
Assignee: International Business Machines Corporation
G06F40/40G06F40/20G06N20/00G06Q10/1053G06Q10/1057G06F40/205
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Quick Facts
Patent No.
US 10,657,331
App. No.
15/266,209
Granted
May 19, 2020
Kind
B2
Abstract

A computer system may receive a first set of bundled information. The computer system may have a processor and a memory storing one or more natural language processing modules. The computer system, using a natural language processing module, may ingest the first set of bundled information. The computer system may generate a first set and a second set of categories. The computer system may generate one or more models. The computer system may receive a set of input characteristics. The computer system may select a model based on the input characteristics. The computer system may rank one or more correlations using the selected model. The computer system may output a display of the one or more correlations on a graphical user interface.

Claims (93)

1. A computer search system comprising:

a memory that stores one or more natural language processing modules;

a network interface; and

a processor circuit in communication with the memory and the network interface, wherein the processor circuit is configured to:

receive a first set of bundled job-related information (FSBJRI) via the network interface;

ingest, using the one or more natural language processing modules, the FSBJRI;

determine, based on the FSBJRI, to combine data from one or more disparate information sources, wherein the one or more disparate information sources include a first information source and a second information source associated with the FSBJRI, and wherein the first information source is disparate from the second information source;

generate an operational information category and a candidate information category;

segregate the FSBJRI into the operational information category and the candidate information category to produce and store, in the memory, operational information and candidate information respectively;

generate one or more models by adding the segregated and stored operational information category and the candidate information category to a bipartite graph;

update one or more models based on the FSBJRI;

receive a set of candidate input characteristics of a job candidate for use in a candidate query via the network interface;

predict one or more outcomes, wherein predicting the one or more outcomes includes generating one or more inferences from the combined information from the one or more disparate information sources;

determine one or more correlations between the operational information and the candidate information;

select a model based on the candidate input characteristics;

rank the one or more correlations using the selected model;

output a display of the one or more correlations on a graphical user interface (GUI), wherein outputting the display of the one or more correlations on the GUI comprises generating an indicator that indicates the strength of the one or more correlations as they relate to the candidate input characteristics;

determine a past acceptance correlation between past candidate acceptance and the one or more models that have resulted in acceptance;

responsive to receipt of the set of candidate input characteristics, generate a tailored job-related package for presentation to a selected candidate based on the past acceptance correlation, wherein the generation comprises combining information from the operational information category and candidate information category and outputting the combined information to a user accessible media for viewing;

provide the tailored job-related information to the selected candidate as an electronic transmission via the network interface;

receive, via the network interface and responsive to the provision of the tailored job-related information, a selected candidate response selected from the group consisting of acceptance and rejection of the job-related package; and

update a ranking based on the selected candidate response;

wherein:

the FSBJRI is unstructured, and wherein the processor circuit is further configured to, for the generation of the operational information category and the candidate information category:

structure the operational information and candidate information in a bipartite graph; and

the processor circuit is further configured to, for the generation of the one or more models:

identify, using the bipartite graph, the one or more correlations between the operational information category and the candidate information category; and

generate a first model that includes at least one of the one or more correlations.

2. The system of claim 1 , wherein the candidate input characteristics are a second set of bundled job-related information (SSBJRI), and wherein the processor circuit is further configured to, for the receipt of the set of candidate input characteristics:

receive SSBJRI, wherein the SSBJRI includes a set of operational information categories and a set of candidate information categories; and

combine the SSBJRI with the FSBJRI.

3. The system of claim 1 , wherein the processor circuit is further configured to, for the selection of the model based on the candidate input characteristics:

generate, from the candidate input characteristics, a first additional set and a second additional set of categories; and

determine whether either the operational information category or the candidate information category matches at least one category of the first additional and second additional set of categories.

4. The system of claim 1 , wherein the processor circuit is further configured to, for the output of the display of the one or more correlations on the GUI:

generate a bar graph that indicates the strength of the one or more correlations as they relate to the candidate input characteristics.

5. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor of a computer search system to:

receive, via a network interface, a first set of bundled job-related information (FSBJRI), the computer system having a memory that stores one or more natural language processing modules, wherein the memory and the network interface are coupled with the processor;

ingest, using a natural language processing module, the FSBJRI;

determine, based on the FSBJRI, to combine data from one or more disparate information sources, wherein the one or more disparate information sources include a first information source and a second information source associated with the FSBJRI, and wherein the first information source is disparate from the second information source;

generate an operational information category and a candidate information category;

segregate the FSBJRI into the operational information category and the candidate information category to produce and store, in the memory, operational information and candidate information respectively;

generate one or more models by adding the segregated and stored operational information category and the candidate information category to a bipartite graph;

update one or more models based on the FSBJRI;

receive a set of candidate input characteristics of a job candidate for use in a candidate query via the network interface;

predict one or more outcomes, wherein predicting the one or more outcomes includes generating one or more inferences from the combined information from the one or more disparate information sources;

determine one or more correlations between the operational information and the candidate information;

select a model based on the candidate input characteristics;

rank the one or more correlations using the selected model; and

output a display of the one or more correlations on a graphical user interface (GUI), wherein outputting the display of the one or more correlations on the GUI comprises generating an indicator that indicates the strength of the one or more correlations as they relate to the candidate input characteristics;

determine a past acceptance correlation between past candidate acceptance and the one or more models that have resulted in acceptance;

responsive to receipt of the set of candidate input characteristics, generate a tailored job-related package for presentation to a selected candidate based on the past acceptance correlation, wherein the generation comprises combining information from the operational information category and candidate information category and outputting the combined information to a user accessible media for viewing;

provide the tailored job-related information to the selected candidate as an electronic transmission via the network interface;

receive, via the network interface and responsive to the provision of the tailored job-related information, a selected candidate response selected from the group consisting of acceptance and rejection of the job-related package; and

update a ranking based on the selected candidate response;

wherein:

the FSBJRI is unstructured, and wherein the processor circuit is further configured to, for the generation of the operational information category and the candidate information category:

structure the operational information and candidate information in a bipartite graph; and

the processor circuit is further configured to, for the generation of the one or more models:

identify, using the bipartite graph, the one or more correlations between the operational information category and the candidate information category; and

generate a first model that includes at least one of the one or more correlations.

6. The computer program product of claim 5 , wherein the input characteristics are a second set of bundled job-related information (SSBJRI), and wherein the instructions further cause the processor to, for the reception of the set of input characteristics:

receive the SSBJRI, wherein the SSBJRI includes a set of operational information categories and a set of candidate information categories; and

combine the SSBJRI with the FSBJRI.

7. The computer program product of claim 5 , wherein the instructions further cause the processor to, for the selection of the model based on the input characteristics:

generate, from the input characteristics, a first additional set and a second additional set of categories; and

determine whether at least one category of the operational information category and the candidate information category matches at least one category of the first additional and second additional set of categories.

8. The computer program product of claim 5 , wherein the instructions further cause the processor to, for the output of the display of the one or more correlations on the GUI:

generate a bar graph that indicates the strength of the one or more correlations as they relate to the candidate input characteristics.

9. A computer search system comprising:

a memory that stores one or more natural language processing modules; and

a network interface; and

a processor circuit in communication with the memory and the network interface, wherein the processor circuit is configured to:

receive a first set of bundled job-related information (FSBJRI) via the network interface;

ingest, using the one or more natural language processing modules, the FSBJRI;

determine, based on the FSBJRI, to combine data from one or more disparate information sources, wherein the one or more disparate information sources include a first information source and a second information source associated with the FSBJRI, and wherein the first information source is disparate from the second information source;

generate one or more models by adding the segregated and stored operational information category and the candidate information category to a bipartite graph;

update one or more models based on the FSBJRI;

receive a set of candidate input characteristics of a job candidate for use in a candidate query via the network interface;

determine one or more correlations between the operational information and the candidate information;

select a model based on the candidate input characteristics;

rank the one or more correlations using the selected model;

determine a past acceptance correlation between past candidate acceptance and the one or more models that have resulted in acceptance;

responsive to receipt of the set of candidate input characteristics, generate a tailored job-related package for presentation to a selected candidate based on the past acceptance correlation, wherein the generation comprises combining information from the operational information category and candidate information category and outputting the combined information to a user accessible media for viewing;

provide the tailored job-related information to the selected candidate as an electronic transmission via the network interface;

receive, via the network interface and responsive to the provision of the tailored job-related information, a selected candidate response selected from the group consisting of acceptance and rejection of the job-related package; and

update a ranking based on the selected candidate response;

wherein:

the FSBJRI is unstructured, and wherein the processor circuit is further configured to, for the generation of the operational information category and the candidate information category:

structure the operational information and candidate information in a bipartite graph; and

the processor circuit is further configured to, for the generation of the one or more models:

identify, using the bipartite graph, the one or more correlations between the operational information category and the candidate information category; and

generate a first model that includes at least one of the one or more correlations.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 15, 2016
From: AVKD, SIVAKUMAR; VADLAMANI, RAVI T.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 039755/0894 →
Continuity (1)
Related Publication 20180075018A1 · Mar 15, 2018