Multi-signal learning system
Certain aspects of the present disclosure provide techniques for providing job skill recommendations for an electronic document. Certain aspects include obtaining work history statements, a current job title, and an experience level, querying curated skills datasets to return a first skill set, generating, with an artificial intelligence model, work history embeddings based on the work history statements, generating, with the artificial intelligence model, skill embeddings based on the curated skills datasets, determining a similarity score between the work history embeddings and the skill embeddings, selecting, for a second skill set, second job skills, identifying common skills between the first skill set and the second skill set, merging the first skill set and the second skill set to form a merged skill set, sorting the merged skill set into an ordered list and populating sections of the electronic document by selecting at least one skill from the ordered list.
1 . A method for providing job skill recommendations for an electronic document, comprising:
obtaining, for a first user, one or more work history statements, a current job title, and an experience level corresponding to the current job title, wherein the one or more work history statements comprise one or more job skills from prior work experience;
querying one or more curated skills datasets to return a first skill set comprising one or more first skills associated with the current job title and the experience level;
sorting the one or more first skills into a hierarchy based on an associated prevalence count of each of the one or more first skills with respect to a historical set of skills within a historical dataset;
generating, with an artificial intelligence model, work history embeddings and skill embeddings based on multi-dimensional data associated with the one or more work history statements and the one or more curated skills datasets, wherein each work history embedding of the work history embeddings and each skill embedding of the skill embeddings comprises a representation of a corresponding portion of the multi-dimensional data in a reduced-dimensional vector space for similarity-based comparison between the work history embeddings and the skill embeddings;
determining a similarity score between pairs of the work history embeddings and the skill embeddings;
selecting, for a second skill set, one or more second skills, from the one or more curated skills datasets, that correspond to the skill embeddings where the similarity score between each corresponding pair of the pairs of the work history embeddings and the skill embeddings is greater than a predefined threshold;
identifying, with a common skills component, one or more common skills between the first skill set and the second skill set;
merging the first skill set and the second skill set to form a merged skill set;
sorting, using a sort component, the merged skill set into an ordered list based on ordering one or more skills of the merged skill set according to one or more of the similarity score of a frequency score based on a number of occurrences of respective skills of the one or more skills within the historical set of skills within the historical dataset, whereby the one or more common skills are listed first in the ordered list, the one or more second skills are listed second, and the one or more first skills are listed third; and
populating one or more sections of the electronic document by selecting at least one skill from the ordered list.
2 . The method of claim 1 , wherein querying the one or more curated skills datasets to return the first skill set comprises:
filtering the one or more curated skills datasets to form a skills experience dataset comprising skills associated with the experience level;
determining one or more similar job titles based on the current job title;
filtering the skills experience dataset to form a refined skills dataset comprising skills associated with the one or more similar job titles and the current job title; and
generating the first skill set as a response to the query based on the refined skills dataset.
3 . The method of claim 2 , wherein determining the one or more similar job titles based on the current job title comprises:
computing a semantic score between the current job title and the one or more similar job titles; and
removing, from the one or more similar job titles, one or more job titles that correspond to the semantic score below a threshold score.
4 . The method of claim 1 , wherein:
the one or more curated skills datasets for generating the skill embeddings is a filtered skills dataset formed by filtering the one or more curated skills datasets to comprise skills associated with the current job title and one or more similar job titles based on the current job title; and
the one or more curated skills datasets for selecting the one or more second skills for the second skill set is the filtered skills dataset.
5 . The method of claim 1 , wherein determining the similarity score between the pairs of work history embeddings and the skill embeddings comprises calculating Cosine similarities between each pair of the pairs of the work history embeddings and the skill embeddings.
6 . The method of claim 1 , wherein the one or more curated skills datasets comprise skills obtained from historical data and curated according to a job title and an experience level of other users.
7 . The method of claim 6 , wherein the historical dataset comprises information from the other users having an engagement level greater than a predetermined level.
8 . The method of claim 7 , wherein the engagement level corresponds to a completion percent of a résumé and the predetermined level is 80%.
9 . A processing system for generating job skill recommendations for an electronic document, comprising:
one or more memories comprising computer-executable instructions; and
one or more processors configured to execute the computer-executable instructions causing the processing system to:
obtain, for a first user, one or more work history statements, a current job title, and an experience level corresponding to the current job title, wherein the one or more work history statements comprise one or more job skills from prior work experience;
query one or more curated skills datasets to return a first skill set comprising one or more first skills associated with the current job title and the experience level;
sort the one or more first skills into a hierarchy based on an associated prevalence count of each of the one or more first skills with respect to a historical set of skills within a historical dataset;
generate, with an artificial intelligence model, work history embeddings and skill embeddings based on multi-dimensional data associated with the one or more work history statements and the one or more curated skills datasets, wherein each work history embedding of the work history embeddings and each skill embedding of the skill embeddings comprises a representation of a corresponding portion of the multi-dimensional data in a reduced-dimensional vector space for similarity-based comparison between the work history embeddings and the skill embeddings;
determine a similarity score between pairs of the work history embeddings and the skill embeddings;
select, for a second skill set, one or more second skills, from the one or more curated skills datasets, that correspond to the skill embeddings where the similarity score between each corresponding pair of the pairs of the work history embeddings and the skill embeddings is greater than a predefined threshold;
identify, with a common skills component, one or more common skills between the first skill set and the second skill set;
merge the first skill set and the second skill set to form a merged skill set;
sort, using a sorting component, the merged skill set into an ordered list based on ordering one or more skills of the merged skill set according to one or more of the similarity score or a frequency score based on a number of occurrences of respective skills of the one or more skills within the historical set of skills within the historical dataset, whereby the one or more common skills are listed first in the ordered list, the one or more second skills are listed second, and the one or more first skills are listed third; and
populate one or more sections of the electronic document by selecting at least one skill from the ordered list.
10 . The processing system of claim 9 , wherein to query the one or more curated skills datasets to return the first skill set comprises causing the processing system to:
filter the one or more curated skills datasets to form a skills experience dataset comprising skills associated with the experience level;
determine one or more similar job titles based on the current job title;
filter the skills experience dataset to form a refined skills dataset comprising skills associated with the one or more similar job titles and the current job title; and
generate the first skill set as a response to the query based on the refined skills dataset.
11 . The processing system of claim 10 , wherein to determine the one or more similar job titles based on the current job title comprises causing the processing system to:
compute a semantic score between the current job title and the one or more similar job titles; and
remove, from the one or more similar job titles, one or more job titles that correspond to the semantic score below a threshold score.
12 . The processing system of claim 9 , wherein:
the one or more curated skills datasets for generating the skill embeddings is a filtered skills dataset formed by filtering the one or more curated skills datasets to comprise skills associated with the current job title and one or more similar job titles based on the current job title; and
the one or more curated skills datasets for selecting the one or more second skills for the second skill set is the filtered skills dataset.
13 . The processing system of claim 9 , wherein to determine the similarity score between the pairs of work history embeddings and the skill embeddings comprises calculating cosine similarities between each pair of the pairs of the work history embeddings and the skill embeddings.
14 . The processing system of claim 9 , wherein the one or more curated skills datasets comprise skills obtained from historical data and curated according to a job title and an experience level of other users.
15 . The processing system of claim 14 , wherein the historical dataset comprises information from the other users having an engagement level corresponding to a completion percent of a résumé that is greater than 80%.
16 . A method for providing job skill recommendations for an electronic document, comprising:
obtaining, for a first user, one or more work history statements, wherein the one or more work history statements comprise one or more job skills from prior work experience;
obtaining, for the first user, a first skill set based on a current job title and experience level corresponding to the current job title;
sorting the one or more first skills of the first skill set into a hierarchy based on an associated prevalence count of each of the one or more first skills with respect to a historical set of skills within a historical dataset;
determining a similarity score between pairs of work history embeddings based on the one or more work history statements and pairs of skill embeddings based on one or more curated skills datasets;
selecting, for a second skill set, one or more second skills, from the one or more curated skills datasets, that correspond to the pairs of skill embeddings or the pairs of work history embeddings where the similarity score is greater than a predefined threshold;
sorting the one or more second skills in the second skill set based on the similarity score to form an ordered second skill set;
identifying, with a common skills component, one or more common skills between the first skill set and the ordered second skill set;
merging the first skill set and the ordered second skill set to form a merged skill set;
sorting, using a sorting component, the merged skill set into an ordered list based on ordering one or more skills of the merged skill set according to one or more of the similarity score or a frequency score based on a number of occurrences of respective skills of the one or more skills within the historical set of skills within the historical dataset, wherein:
the one or more common skills are listed first, whereby repeated skills in each of the one or more common skills are removed,
the one or more second skills are listed second, wherein the one or more second skills are listed based on an order corresponding to the ordered second skill set, and
one or more first skills from the first skill set are listed third; and
populating one or more sections of the electronic document by selecting at least one skill from the ordered list.
17 . The method of claim 16 , wherein:
the one or more curated skills datasets is a filtered skills dataset formed by filtering the one or more curated skills datasets to comprise skills associated with the current job title and one or more similar job titles based on the current job title; and
the one or more curated skills datasets for selecting the one or more second skills for the second skill set is the filtered skills dataset.
18 . The method of claim 16 , wherein:
the one or more curated skills datasets comprise skills obtained from historical data and curated according to a job title and an experience level of other users; and
the historical dataset comprises information from the other users having an engagement level corresponding to a completion percent of a résumé that is greater than 80%.
19 . The method of claim 16 , wherein the one or more curated skills datasets is a filtered skills dataset formed by filtering the one or more curated skills datasets to comprise skills associated with the current job title and one or more similar job titles based on the current job title.
20 . The method of claim 16 , wherein determining the similarity score between the pairs of the work history embeddings or the pairs of skill embeddings comprises calculating Cosine similarities between the pairs of work history embeddings or the pairs of skill embeddings.