International Business Machines Corporation

Irina Rish

Clifford A Pickover

Guillermo A Cecchi

James R Kozloski

Dimitri Kanevsky

Genady Grabarnik

Sheng Ma

Sara H Basson

Laxmi Priya Parida

Dan He

Mark Alan Brodie

Edward Emile Kelley

Bhuvana Ramabhadran

Ajay K Royyuru

Ossama S Emam

Alina Beygelzimer

Natalia V Odintsova

Melissa Kristin Carroll

Rick A Hamilton, Ii

Shang Qing Guo

Peter Gustav Fairweather

David C Haws

Katya Scheinberg

Narges Bani Asadi

Zhen Liu

Jonathan Lenchner

Larisa Shwartz

Anton Viktorovich Riabov

Nianjun Zhou

Joseph L Hellerstein

Anand Ranganathan

Gerald James Tesauro

Irwin Boutboul

Jayram S Thathachar

Ricardo Vilalta

Herbert M Lee

Sushmita L Allam

Srinivas Gundugola

Gaurav Chandalia

Sahil Garg

Exemplary embodiments disclose a method, a computer program product, and a computer system for generating dialogue via hashing functions. Exemplary embodiments may include detecting dialogue between one or more participants, converting the dialogue to a hashcode, and determining one or more responses to the dialogue by applying one or more models to the hashcode, wherein the one or more models correlates one or more hashcodes with the one or more responses.

Dialogue generation via hashing functions

Embodiments are directed to a computer implemented business campaign development system. The system includes an electronic tool configured to hold data of a user, and an analyzer circuit configured to derive a cognitive trait of the user based at least in part on the data of the user. The system further includes a targeted business strategy development system configured to derive a targeted business strategy based at least in part on the cognitive trait of the user.

Targeted E-commerce business strategies based on affiliation networks derived from predictive cognitive traits

Targeted e-commerce business strategies based on affiliation networks derived from predictive cognitive traits

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.

Reducing graphical text analysis using physiological priors

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.

Facilitating a meeting using graphical text analysis

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.

Analyzer for behavioral analysis and parameterization of neural stimulation

Methods, systems and apparatus for modeling states of an entity are presented. For example, a method, implemented on a processor device, of modeling one or more states of an entity is presented. The method includes obtaining a training dataset for training a model by applying a stimulus to the entity, forming a set of model parameters, and using the set of model parameters to form the model, such that the model is configured to predict at least one of the one or more states of the entity. At least one model parameter of the set of model parameters changes with time as a result of dependency of the at least one model parameter on the stimulus and as a result of time-dependency of the stimulus. The steps of obtaining the training dataset, forming the set of model parameters and using the set of model parameters are implemented on the processor device.

Modeling states of an entity

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.

Securing a device using graphical analysis

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.

Moderating online discussion using graphical text analysis

A method, information processing system, and computer readable article of manufacture reinforce behavior in an individual. A behavior associated with an individual is monitored. A determination is made, based on the monitoring, that the behavior substantially matches a behavior in a set of behaviors. A set of interactive actions associated with the behavior are identified. At least one of the interactive actions in the set of interactive actions is selected. The at least one of the interactive actions that has been selected is performed. A response from the individual is monitored in response to the least one of the interactive actions being performed. An indicator is associated with the at least one of the interactive actions based on the reaction from the individual. The indicator indicates a relative degree of success in obtaining a desired response from the individual.

Adaptive system for real-time behavioral coaching and command intermediation

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.

Predicting individual or crowd behavior based on graphical text analysis of point recordings of audible expressions

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Rye Brook, NY, United States of America

Irina Rish