Abstract: Embodiments relate to facilitating a meeting. A method for reducing an amount of communications to analyze in order to determine a cognitive state of an entity is provided. The method determines a first likelihood of an entity to have a particular cognitive state based on a set of physiological measures of the entity. The method receives communications from the entity. The method generates a graph of communications of the entity. The method performs a graphical text analysis on the graph to determine a second likelihood of the entity to have the particular cognitive state. The method determines whether the entity has the particular cognitive state based on the first likelihood and the second likelihood.

Abstract: Embodiments are directed to a computer system for securing an electronic device. The system includes at least one processor configured to receive at least one communication from an entity seeking to access the device. The at least one processor is further configured to generate a graph of the at least one communication from the entity seeking access to the device. The at least one processor is further configured to determine a difference between a cognitive trait of the entity seeking access to the device, and a cognitive identity of an entity authorized to access the device. The at least one processor is further configured to, based at least in part on a determination that the difference is greater than a threshold, deploy a security measure of the device.

Abstract: Embodiments are directed to a computer system for securing an electronic device. The system includes at least one processor configured to receive at least one communication from an entity seeking to access the device. The at least one processor is further configured to generate a graph of the at least one communication from the entity seeking access to the device. The at least one processor is further configured to determine a difference between a cognitive trait of the entity seeking access to the device, and a cognitive identity of an entity authorized to access the device. The at least one processor is further configured to, based at least in part on a determination that the difference is greater than a threshold, deploy a security measure of the device.

Abstract: Embodiments relate to facilitating communications between customers and customer service representatives. A method for facilitating communications between customers and customer service representatives is provided. The method generates a graph of expressions of a customer. The method generates a graph of expressions of each customer service representative of a plurality of customer service representatives. The method performs a graphical text analysis on the graph for the customer to identify an interaction style of the customer. The method performs a graphical text analysis on the graph for each customer service representative to identify an interaction style of the customer service representative. The method selects a customer service representative from the plurality of the customer service representatives based on the interaction style of the customer and the interaction styles of the plurality of the customer service representative.

Abstract: Embodiments relate to facilitating communications between customers and customer service representatives. A method for facilitating communications between customers and customer service representatives is provided. The method generates a graph of expressions of a customer. The method generates a graph of expressions of each customer service representative of a plurality of customer service representatives. The method performs a graphical text analysis on the graph for the customer to identify an interaction style of the customer. The method performs a graphical text analysis on the graph for each customer service representative to identify an interaction style of the customer service representative. The method selects a customer service representative from the plurality of the customer service representatives based on the interaction style of the customer and the interaction styles of the plurality of the customer service representative.

Abstract: Embodiments are directed to a computer implemented neural stimulation system having a first module configured to derive neural data from muscle contractions or movements of a subject. The system further includes a second module configured to derive a neural state assessment of the subject based at least in part on the neural data. The system further includes a third module configured to derive at least one neural stimulation parameter based at least in part on the neural state assessment. The system further includes a fourth module configured to deliver neural stimulations to the subject based at least in part on the at least one neural stimulation parameter.

Abstract: Embodiments relate to moderating an online discussion. A method for moderating an online discussion between a plurality of participants is provided. The method receives expressions from a participant during an online discussion. The method generates a graph of expressions of the participant. The method performs a graphical text analysis on the graph to determine a likelihood of the participant to have a problematic behavior. The method performs a moderating action responsive to the likelihood exceeding a threshold likelihood.

Abstract: Embodiments are directed to a computer implemented neural stimulation system having a first module configured to derive neural data from muscle contractions or movements of a subject. The system further includes a second module configured to derive a neural state assessment of the subject based at least in part on the neural data. The system further includes a third module configured to derive at least one neural stimulation parameter based at least in part on the neural state assessment. The system further includes a fourth module configured to deliver neural stimulations to the subject based at least in part on the at least one neural stimulation parameter.

Abstract: Embodiments relate to moderating an online discussion. A method for moderating an online discussion between a plurality of participants is provided. The method receives expressions from a participant during an online discussion. The method generates a graph of expressions of the participant. The method performs a graphical text analysis on the graph to determine a likelihood of the participant to have a problematic behavior. The method performs a moderating action responsive to the likelihood exceeding a threshold likelihood.

Abstract: Various embodiments select features from a feature space. In one embodiment, a set of training samples and a set of test samples are received. A first centered Gram matrix of a given dimension is determined for each of a set of feature vectors that include at least one of the set of training samples and at least one of the set of test samples. A second centered Gram matrix of the given dimension is determined for a target value vector that includes target values from the set of training samples. A set of columns and rows associated with the at least one of the test samples in the second centered Gram matrix is set to 0. A subset of features is selected from a set of features based on the first and second centered Gram matrices.

Abstract: Speech traits of an entity imbue an artificial intelligence system with idiomatic traits of persons from a particular category. Electronic units of speech are collected from an electronic stream of speech that is generated by a first entity. Tokens from the electronic stream of speech are identified, where each token identifies a particular electronic unit of speech from the electronic stream of speech, and where identification of the tokens is semantic-free. Nodes in a first speech graph are populated with the tokens to develop a first speech graph having a first shape. The first shape is matched to a second shape of a second speech graph from a second entity in a known category. The first entity is assigned to the known category, and synthetic speech generated by an artificial intelligence system is modified based on the first entity being assigned to the known category.

Abstract: A method to send an alert for nonproductivity associated with a conversation is provided. The method may include recording a plurality of communication outputs of at least two users engaged in a remote message exchange or a remote conversation. The method may also include creating a plurality of text tokens based on the recorded plurality of communication outputs. The method may include analyzing, by a graphical text analyzer, the created plurality of text tokens to determine whether the plurality of text tokens has fallen below a threshold. The method may further include sending an alert to the plurality of users involved in the conversation if it is determined that the plurality of text tokens has fallen below the threshold.

Abstract: Various embodiments select features from a feature space. In one embodiment, a set of training samples and a set of test samples are received. A first centered Gram matrix of a given dimension is determined for each of a set of feature vectors that include at least one of the set of training samples and at least one of the set of test samples. A second centered Gram matrix of the given dimension is determined for a target value vector that includes target values from the set of training samples. A set of columns and rows associated with the at least one of the test samples in the second centered Gram matrix is set to 0. A subset of features is selected from a set of features based on the first and second centered Gram matrices.

Abstract: Techniques for providing a prompt for real-time cognitive assistance. A method includes analyzing input from at least one environmental sensor to identify context information pertaining to a user situation, identifying a likely subsequent cognitive task of the user in the user situation based on the context information and use of a learned model, determining an action with respect to information to be suggested to the user via a corresponding prompt, wherein the determining is based on the likely subsequent cognitive task, the context information and information learned from at least one previous user situation, computing a confidence value to represent a level of certainty in the action, and providing the prompt to the user if the action has a confidence value greater than a threshold value corresponding to the action.

Abstract: Embodiments relate to determining a crowd behavior. A method of determining a crowd behavior is provided. The method collects, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make. The method generates a graph of the audible expressions as the audible expressions are collected from the individuals. The method determines a crowd behavior by performing a graphical text analysis on the graph. The method outputs an indication of the crowd behavior to trigger a crowd control measure.

Abstract: Embodiments relate to determining a crowd behavior. A method of determining a crowd behavior is provided. The method collects, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make. The method generates a graph of the audible expressions as the audible expressions are collected from the individuals. The method determines a crowd behavior by performing a graphical text analysis on the graph. The method outputs an indication of the crowd behavior to trigger a crowd control measure.

Abstract: Embodiments relate to facilitating a meeting. A method for facilitating a meeting of a group of participants is provided. The method generates a graph of words from speeches of the participants as the words are received from the participants. The method partitions the group of participants into a plurality of subgroups of participants. The method performs a graphical text analysis on the graph to identify a cognitive state for each participant and a cognitive state for each subgroup of participants. The method informs at least one of the participants about the identified cognitive state of a participant or a subgroup of participants.

Abstract: Embodiments relate to facilitating a meeting. A method for facilitating a meeting of a group of participants is provided. The method generates a graph of words from speeches of the participants as the words are received from the participants. The method partitions the group of participants into a plurality of subgroups of participants. The method performs a graphical text analysis on the graph to identify a cognitive state for each participant and a cognitive state for each subgroup of participants. The method informs at least one of the participants about the identified cognitive state of a participant or a subgroup of participants.

Abstract: A method, system, and/or computer program product uses speech traits of an entity to predict a future state of the entity. Units of speech are collected from a stream of speech that is generated by a first entity. Tokens from the stream of speech are identified, where each token identifies a particular unit of speech from the stream of speech, and where identification of the tokens is semantic-free. Nodes in a first speech graph are populated with the tokens, and a first shape of the first speech graph is identified. The first shape is matched to a second shape, where the second shape is of a second speech graph from a second entity in a known category. The first entity is assigned to the known category, and a future state of the first entity is predicted based on the first entity being assigned to the known category.

Abstract: A system and an article of manufacture for providing a prompt for real-time cognitive assistance include analyzing input from at least one environmental sensor to identify context information pertaining to a user situation, identifying a likely subsequent cognitive task of the user in the user situation based on the context information and use of a learned model, determining an action with respect to information to be suggested to the user via a corresponding prompt, wherein the determining is based on the likely subsequent cognitive task, the context information and information learned from at least to one previous user situation, computing a confidence value to represent a level of certainty in the action, and providing the prompt to the user if the action has a confidence value greater than a threshold value corresponding to the action.