Abstract: A computer-implemented method, a computer program product, and a computer system for determining skill adjacencies using a machine learning model. A computer calculates first similarity scores between first skill vectors obtained from one or more training datasets and second similarity scores between the first skill vectors and skill category vectors pre-calculated from job requisitions, using both a reference corpus word embedding model and a target corpus word embedding model. The computer generates features extracted from the first similarity scores and the second similarity scores. Based on the features, the computer trains a machine learning model for classifying combinations of skills as adjacent and non-adjacent. The machine learning model is used to determine skill adjacencies between skills extracted from the job requisitions and skills extracted from resumes.

Abstract: Methods, systems, and computer program products for designing conflict minimizing outreach strategies are provided herein. A computer-implemented method includes obtaining data from a job matching service corresponding to jobs listed on the job matching service and candidates; generating job clusters for the jobs based on clustering criteria; identifying, for each respective one of the job clusters, a set of candidates from among the candidates to reduce inter-cluster conflict; selecting, for each of the jobs in a given one of the job clusters, individual candidates from among the set of candidates corresponding to the given job cluster to reduce intra-cluster conflict with respect to the plurality of candidates; and outputting one or more optimized lists of the candidates for the jobs based on the identifying and the selecting.

Abstract: A computer-implemented method, a computer program product, and a computer system for determining skill adjacencies using a machine learning model. A computer calculates first similarity scores between first skill vectors obtained from one or more training datasets and second similarity scores between the first skill vectors and skill category vectors pre-calculated from job requisitions, using both a reference corpus word embedding model and a target corpus word embedding model. The computer generates features extracted from the first similarity scores and the second similarity scores. Based on the features, the computer trains a machine learning model for classifying combinations of skills as adjacent and non-adjacent. The machine learning model is used to determine skill adjacencies between skills extracted from the job requisitions and skills extracted from resumes.

Abstract: A method, system and computer program product for determining key professional skills and personality traits for a job is disclosed. A computer-implemented method is provided that comprises analyzing organization and industry data to identify one or more job-specific attributes associated with a job. A job-specific attributes profile for the job is generated comprising the one or more identified job-specific attributes. The job-specific attributes include one or more professional skills and personality traits that positively influence an outcome of the job.