Dot Incorporation

Opensesame Inc.

Ganesh Iyer

Roman Samarev

Sanjeev Ukhalkar

Predicting psychometric attributes and relevant skills for a first job position includes generation of predictor models based on test data of tests users. The test data includes resumes of the test users, job descriptions of job positions of the test users, historical data of the test users, and answers provided by the test users to psychometric questions. The predictor models are then used to predict the psychometric attributes and the relevant skills based on target data, which is a first job description of the first job position.

Prediction of psychometric attributes relevant for job positions

A method and a system for predicting business outcomes by analyzing voice data of users are provided. The method includes generation of predictor models based on test data of test users. The test data includes historical data of the test users, voice samples of the test users, and answers provided by the test users to psychometric questions. The predictor models are then used to predict psychometric features and business outcomes based on target data of a target user. The target data includes voice samples of the target user, historical data of the target user, and answers provided by the target user to the psychometric questions.

Prediction of business outcomes by analyzing voice samples of users

Predicting business outcomes for a target user includes generation of predictor models based on test data of tests users. The test data includes historical data of the test users, resumes of the test users, and answers provided by the test users to psychometric questions. The predictor models are then used to predict psychometric features and business outcomes based on target data of the target user. The target data includes a resume of the target user, historical data of the target user, and answers provided by the target user to the psychometric questions.

Prediction of business outcomes by analyzing resumes of users

A method and a system for predicting business outcomes by analyzing image interests of users are provided. The method includes generation of predictor models based on sample data of tests users. The sample data includes historical data of the test users, images that are of interest to the test users, and answers provided by the test users to psychometric questions. The predictor models are then used to predict psychometric features and business outcomes for a target user based on target data of the target user. The target data includes images that are of interest to the target user, historical data of the target user, and answers provided by the target user to the psychometric questions.

Prediction of business outcomes by analyzing image interests of users

A method and a system for predicting business outcomes for a target user are provided. The method includes generation of a plurality of images such that each image includes a set of colored-blocks arranged in rows and columns and a unique pattern formed by a subset of colored-blocks in the corresponding set of colored-blocks. Each unique pattern is associated with at least one psychometric feature. The plurality of images are presented to the target user for selection. The method further includes receiving a set of images selected by the target user from the plurality of images and analyzing each image to derive psychometric features of the target user. One or more business outcomes are predicted for the target user based on the derived psychometric features and one or more predictor models.

A system and a process are disclosed to analyze images and predict personality to enhance business outcomes by analyzing colors predominant in images selected, posted, or liked by a person, determining color values for the predominant colors in the images, weighting the color values, and, based on the weighted color values, deriving one or more personality attributes according to a particular psychological orientation.

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San Jose, CA, United States of America

Ganesh Iyer