| CPC G06F 3/015 (2013.01) [G06F 3/0487 (2013.01); G06F 16/24568 (2019.01); G06F 16/9535 (2019.01)] | 19 Claims |

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1. A method, comprising:
establishing contact between a biosignal detector and a user;
receiving a first set of cognitive state data parameters associated with the biosignal detector;
receiving a second set of cognitive state data parameters from a third-party, the second set of cognitive state data parameters comprising a data structure type for cognitive state data and a timing rule for cognitive state data generation;
receiving a third set of cognitive state data parameters associated with the user;
automatically collecting, at the biosignal detector, a bioelectrical signal dataset from a plurality of head regions of the user as the user is engaged with a stimulus provided by the third-party;
using a first model, generating the cognitive state data for the user based on the bioelectrical signal dataset and the third set of cognitive state data parameters associated with the user, according to the first set of cognitive state data parameters and the second set of cognitive state data parameters;
collecting a set of training data, wherein collecting the set of training data comprises: for each training user of a set of training users, collecting training data while the training user is engaged with a training stimulus and while a biosignal detector contacts the training user, wherein the training data comprises a response to the training stimulus and cognitive state data for the training user;
using a second model, classifying the user as a user group of a set of user groups based on the cognitive state data for the user, wherein the second model is a machine learning model trained to predict user groups using the set of training data, wherein the set of user groups is generated by segmenting the set of training users into the set of user groups based on the set of training data; and
predicting a preference for the user based on the user group.
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