Abstract: A method for search construct validation is described. The method includes determining a construct of a search query recognized on a search engine of a third party webpage and related constructs represented in a plurality of search results generated based on the search query. The method includes mapping the determined construct to the related constructs represented in the plurality of search results generated based on the search query. The method includes generating a knowledge graph illustrating the mapping between the determined construct and the related constructs and a hierarchy and a strength of a conceptual relationship between the determined construct and the related constructs. The method includes displaying, via an interactive user interface, an interactive graph illustrating the mapping between the determined construct and the plurality of related constructs and the hierarchy and the strength of the conceptual relationship between the determined construct and the plurality of related constructs.

Abstract: Systems and methods for determining whether a user employs System 1 type thinking or System 2 type thinking when engaged in a task are disclosed. The systems and methods include determining one or more properties of the task based on information regarding the task received from a database storing information regarding the task, determining one or more properties of the user with respect to the task, determining a state of the user based on one or more physiological sensors configured to sense one or more characteristics of the user, and determining that the user employs System 1 type thinking or System 2 type thinking when engaged in the task based on the determined one or more properties of the task, the determined one or more properties of the user, and the determined state of the user.

Abstract: Systems and methods for generating predicted preferences are disclosed. The method includes implementing, with a computing device having a processor and a non-transitory computer-readable memory, a conjoint architecture comprising: an autoencoder trained to transform input data including one or more choices and one or more features into a latent representation, and a choice classification network trained to predict one or more predicted preferences from the latent representation extracted by the autoencoder. The method further includes outputting, from the choice classification network, the one or more predicted preferences.

Abstract: A method for search construct validation is described. The method includes determining a construct of a search query recognized on a search engine of a third party webpage and related constructs represented in a plurality of search results generated based on the search query. The method includes mapping the determined construct to the related constructs represented in the plurality of search results generated based on the search query. The method includes generating a knowledge graph illustrating the mapping between the determined construct and the related constructs and a hierarchy and a strength of a conceptual relationship between the determined construct and the related constructs. The method includes displaying, via an interactive user interface, an interactive graph illustrating the mapping between the determined construct and the plurality of related constructs and the hierarchy and the strength of the conceptual relationship between the determined construct and the plurality of related constructs.

Abstract: A method for statistical data clarification is described. The method includes determining a relevance of statistical data according to a textual context of a statistical data detected within a document viewed by a user. The method also includes establishing a frame of reference for the statistical data according to the textual context and a determined relevance of the statistical data detected within the document viewed by the user. The method further includes generating, according to the frame of reference, at least one analogy that corresponds to the statistical data. The method also includes displaying the at least one analogy to the user to assist the user in understanding and using the statistical data.

Abstract: A method for goal progression and visualization is described. The method includes generating a graph-like structure according to user specified goals along with their associated timeframes and desired outcomes. The method also includes converting the graph-like structure into a topological landscape of hills and valleys representing the user specified goals along with the associated timeframes and desired outcomes. The method further includes displaying the topological landscape of hills and valleys representing the user specified goals along with the associated timeframes and desired outcomes.

Abstract: A method to generate a digital avatar simulating a human for behavioral empathy and understanding is described. The method includes training a neural network to generate the digital avatar to simulate the human according to a vector of human attributes and generate responses in response to interactions with a user based on the vector of human attributes. The method also includes interacting, by the user, with the digital avatar, in which the digital avatar initially having a similar background and attributes as the user. The method further includes modifying, over time, the attributes of the digital avatar to represent a target background and a target set of attributes different from the user.

Abstract: A system includes a processor configured to build a model of human behavior that can be assigned to a simulated human, where the model is trained on a dataset of interactions between humans, and parameters of the model can be adjusted. The processor is further configured to build a model of a task to be engaged in by a plurality of simulated humans, simulate interactions between the plurality of simulated humans, and display behavior of the simulated humans and information about the interactions between the simulated humans during simulated interactions.

Abstract: A system includes a processor configured to determine analogies between information associated with a new topic to be learned and information associated with existing knowledge of a user, identify terms associated with the new topic that appear similar to terms associated with the existing knowledge, and propose questions for the user to explore based on the new topic and the existing knowledge.

Abstract: A method for an augmented reality goal assistant is described. The method includes detecting an object associated with a behavioral goal of a user. The method also includes altering an appearance of the object based on the behavioral goal of the user. The method further includes displaying the altered appearance of a detected object on an augmented reality headset, such that the altered appearance of the detected object is modified based on the behavioral goal of the user.

Abstract: A system and method for configuring a device includes using a machine learning model to generate a user behavior model based on user behavior data. The user behavior data may include time series data collected from user interactions with a first device, and the machine learning model may include a classification model configured to classify the user behavior data into the one or more classifications. A mapping may be created by training a machine learning model, using user behavior models from a plurality of users and device settings from the plurality of users, to identify one or more relationships between device settings and classifications of the user behavior data. The system and method configures one or more settings of a second device based on the user behavior model and the mapping.

Abstract: A method includes fitting a ML trained model to data features, the fitting generates complete data feature-set outputs that are associated with a first set of accuracy values, iteratively fitting, after an iterative removal of each data feature from the data feature-set, the ML trained model to subsets of the plurality of data features to determine respective reduced feature-set outputs, each subset lacks a different data feature of the plurality of data features, determining one or more of the reduced feature-set outputs as corresponding to a second set of accuracy values, designating the iteratively removed data features as accuracy-modifying data features, generating a first linear model, generating a second linear model based on one of the accuracy-modifying data features having a weight that is highest relative to respective different weights of the remaining ones of the accuracy-modifying data features, and identifying the second linear model as a generative model.

Abstract: A method implemented by a processor of a device, the method including determining one or more user values, determining a prompt requiring a decision, and receiving a user selection to one or more choice options related to the one or more user values and pertaining to the prompt requiring a decision. The method further includes comparing the user selection to a risk-neutral utility function and assessing a risk of a potential decision based on the comparison.

Abstract: Electronic devices and methods for displaying information on electronic displays of electronic devices based on learned user behavior are disclosed. In one embodiment, an electronic device includes an electronic display, a processor, and a non-transitory computer-readable medium storing instructions that, when executed by the processor, causes the processor to cause for display on the electronic display a selected representation of information among a plurality of representations based at least in part on learned behavior of a user.

Abstract: Systems and methods for selecting a channel of communication based on a type of thinking employed by a user for a task are disclosed. The systems and methods include determining that a user is employing System 1 type thinking or System 2 type thinking for the task based on one or more properties of the task, one or more properties of the user, and a state of the user based on physiological response data from one or more physiological sensors monitoring the user, and implementing a channel of communication to utilize for the task that corresponds to a determined type of thinking the user is employing for the task.

Abstract: Systems and methods for determining whether a user employs System 1 type thinking or System 2 type thinking when engaged in a task are disclosed. The systems and methods include determining one or more properties of the task based on information regarding the task received from a database storing information regarding the task, determining one or more properties of the user with respect to the task, determining a state of the user based on one or more physiological sensors configured to sense one or more characteristics of the user, and determining that the user employs System 1 type thinking or System 2 type thinking when engaged in the task based on the determined one or more properties of the task, the determined one or more properties of the user, and the determined state of the user.

Abstract: A method for generating and outputting a prompt for performing a task in a designated time segment is provided. The method includes obtaining, from a plurality of sensors, context data associated of the user related to time segments, categorizing each of the time segments into one of a plurality of thought states based on the context data, mapping a task from a task dataset associated with the user into one of the plurality of thought states, and generating a prompt for performing the task during a designated time segment of the time segments, the designated time segment corresponding to the one of the plurality of thought states to which the task is mapped.

Abstract: Systems and methods for content framing monitoring and intervention are disclosed. In one example, a method includes receiving, at a computing device, first text conveying first information, performing natural language processing of the first text, determining a first framing of the first information based on the natural language processing of the first text, determining second text conveying the first information with a second framing, different from the first framing, and outputting the second text on an electronic display.