System and method for predicting personality traits using disc profiling and big five personality techniques
AssigneeWipro Limited
InventorAbhishek Gunjan
Life of this patent
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Abstract
The present disclosure relates to systems, methods, and non-transitory computer-readable media for human personality prediction by analyzing information collected from different sources such as social media, call detail record (CDR), email etc. using DISC (dominance, inducement, submission, and compliance) profiling and Big Five personality techniques (openness, conscientiousness, extraversion, agreeableness, and neuroticism). Embodiments in accordance with the present disclosure are further capable of using a self-learning model which learns from user response to the prediction.
Claims20
A method for predicting a personality of at least one human subject, the method comprising:
- receiving data associated with the at least one human subject from one or more sources;
- clustering the data based on one or more topics of interest of the at least one human subject using one or more topic modeling algorithms;
- predicting at least one high level personality trait associated with the at least one human subject by analyzing the clustered data, the at least one high level personality trait being one of one or more high level personality traits defined by a first model;
- and
- predicting at least one personality profile by classifying the at least one high level personality trait into one or more granular level personality traits defined by a second model, the classifying being based on clustered data,
- wherein at least one of the receiving data, the clustering the data, the predicting at least one first personality, and the predicting at least one second personality is performed by a processor.
A system for predicting a personality of at least one human subject, the system comprising:
- one or more hardware processors;
- and
- a computer-readable medium storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
- receiving data associated with the at least one human subject from one or more sources;
- clustering the data based on one or more topics of interest of the at least one human subject using one or more topic modeling algorithms;
- predicting at least one high level personality trait associated with the at least one human subject by analyzing the clustered data, the at least one high level personality trait being one of the one or more high level personality traits defined by a first model;
- and
- predicting at least one personality profile by classifying the at least one high level personality trait into one or more granular level personality traits defined by a second model, the classifying being based on clustered data.
A non-transitory computer-readable medium storing instructions for predicting a personality of at least one human subject that, when executed by a processor, cause the processor to perform operations comprising:
- receiving data associated with the at least one human subject from one or more sources;
- clustering the data based on one or more topics of interest of the at least one human subject using one or more topic modeling algorithms;
- predicting at least one high level personality trait associated with the at least one human subject by analyzing the clustered data, the at least one high level personality trait being one of the one or more high level personality traits defined by a first model;
- and
- predicting at least one personality profile by classifying the at least one high level personality trait into one or more granular level personality traits defined by a second model, the classifying being based on clustered data.
Dependencies are inferred from the claim text.