Abstract: A system for determining a likelihood that a pre-determined customer will enter a selected customer support center (CSC) is provided. The system includes a customer-tracking system for determining whether the customer is within a predetermined distance of the CSC. The tracking system is set to a tracking state in response to receiving a customer tracking opt-in selection. The system also includes a biometric monitoring system that monitors, using an electronic device in close proximity to the customer, when the customer is determined to be within the pre-determined distance of the CSC. The biometric monitoring system monitors the customer's biometric functions to determine the likelihood of the customer entering the CSC. When a determination of the likelihood of the customer physically entering the CSC is higher than a threshold level, the system may provide the likelihood, as further influenced by the customer sentiment condition, of the customer entering the CSC.

Abstract: Apparatus and methods for dynamically controlling application of a graphic processing unit (“GPU”) based on the current processing needs is described. A number of objects in each image may be detected. A machine learning model may be utilized to detect and classify objects in each image. Based on the number of detected objects, the GPU could be switched on to provide increased image processing performance. Dynamically turning the GPU on/off may reduce power consumption. When the GPU is turned off, a central processing unit (“CPU”) may be used to perform image processing.

Abstract: A system for leveraging a tokening system to authenticate a traveler while maintaining anonymity of the traveler is provided. The system may include a secure central server configured to store identification data associated with a plurality of users. The system may also include a mobile token application for providing a token identifier representing a user's identification data. The mobile token application may be activated by the central server on a mobile device of the user registered with the central server and stored in a secure storage on the mobile device of the user. The system may also include a travel service provider. The travel service provider may be configured to enable reserving a travel reservation file. The travel service provider may be enabled to retrieve a token identifier from the user's mobile device as representing the identification of the user and verify the token identifier with the central server.

Abstract: A system for leveraging a tokening system to authenticate a traveler while maintaining anonymity of the traveler is provided. The system may include a secure central server configured to store identification data associated with a plurality of users. The system may also include a mobile token application for providing a token identifier representing a user's identification data. The mobile token application may be activated by the central server on a mobile device of the user registered with the central server and stored in a secure storage on the mobile device of the user. The system may also include a travel service provider. The travel service provider may be configured to enable reserving a travel reservation file. The travel service provider may be enabled to retrieve a token identifier from the user's mobile device as representing the identification of the user and verify the token identifier with the central server.

Abstract: A system for leveraging a tokening system to authenticate a traveler while maintaining anonymity of the traveler is provided. The system may include a secure central server configured to store identification data associated with a plurality of users. The system may also include a mobile token application for providing a token identifier representing a user's identification data. The mobile token application may be activated by the central server on a mobile device of the user registered with the central server and stored in a secure storage on the mobile device of the user. The system may also include a travel service provider. The travel service provider may be configured to enable reserving a travel reservation file. The travel service provider may be enabled to retrieve a token identifier from the user's mobile device as representing the identification of the user and verify the token identifier with the central server.

Abstract: A system for leveraging a tokening system to authenticate a traveler while maintaining anonymity of the traveler is provided. The system may include a secure central server configured to store identification data associated with a plurality of users. The system may also include a mobile token application for providing a token identifier representing a user's identification data. The mobile token application may be activated by the central server on a mobile device of the user registered with the central server and stored in a secure storage on the mobile device of the user. The system may also include a travel service provider. The travel service provider may be configured to enable reserving a travel reservation file. The travel service provider may be enabled to retrieve a token identifier from the user's mobile device as representing the identification of the user and verify the token identifier with the central server.

Abstract: A system for determining a likelihood that a pre-determined customer will enter a selected customer support center (CSC) is provided. The system includes a customer-tracking system for determining whether the customer is within a predetermined distance of the CSC. The tracking system is set to a tracking state in response to receiving a customer tracking opt-in selection. The system also includes a biometric monitoring system that monitors, using an electronic device in close proximity to the customer, when the customer is determined to be within the pre-determined distance of the CSC. The biometric monitoring system monitors the customer's biometric functions to determine the likelihood of the customer entering the CSC. When a determination of the likelihood of the customer physically entering the CSC is higher than a threshold level, the system may provide the likelihood, as further influenced by the customer sentiment condition, of the customer entering the CSC.

Abstract: A system for leveraging artificial intelligence-bot (AI-bot) information derived from information included in or associated with a customer support request (“CSR”) is provided. The system may include a receiver configured to receive the CSR. The CSR may include a date of the CSR, a time of receipt of the CSR, a location of a communication device that was used to communicate the CSR. The CSR may also include a device identification number associated with the communication device and a message. A processor may be configured to retrieve a current profile for the CSR. The current profile may be based on the historical sentiment value. The processor may retrieve, from an AI-bot library, a historical profile. The historic profile may preferably be the best fit in the AI-bot library to the current profile. The processor may be further configured to route the customer request based on the historical profile.

Abstract: A system that leverages social media account history and/or third party data source information to improve the accuracy of a sentiment analysis performed on a customer support request (“CSR”) is provided. A receiver receives logins. Each login initiates a customer support request that includes a date/time of the CSR, a location of computer that was used to generate the CSR, a username associated with the CSR and a message. The system retrieves the third party data associated with a user. The processor harvests artifacts including sentiment information relevant to the CSR. The processor calculates a sentiment value based on the artifacts, the message, and historical information. The processor routes the CSR based on at least two of the date, time, username, location, and the sentiment value. The routing destination is selected from levels defined in a vertical stratification of the entity and corresponds that level to information contained within the message.

Abstract: A system for leveraging an Application Programming Interface (API) feed to improve the accuracy of a sentiment analysis performed on a customer support request is provided. The system includes a receiver that receives a plurality of logins to the API feed. Each of the logins initiates a customer support request. The customer support request includes a date of the customer support request, a time of the customer support request, a location of computer that was used to generate the customer support request, a username associated with the customer support request and a message. The system also includes a processor that harvests from the API feed a first and second plurality of artifacts. Each artifact includes sentiment information relevant to the customer support request. The processor calculates a sentiment value, based, at least in part, on the first plurality of artifacts, the second plurality of artifacts, the message, and historical information associated with the user.

Abstract: A method for identifying and mitigating a negative sentiment trend derived from sentiment analysis is provided. The analysis is based on aggregating a plurality of biometric information artifacts obtained from consumers in a consumer center. The method includes harvesting the artifacts from the plurality of consumers, identifying a biometric information trend. The biometric trend includes a verbal communications trend recorded from among the plurality of consumers. The verbal communications are captured using microphone(s). The method may also include periodically updating the harvesting to update the biometric information trend. The method may also include determining, over the pre-determined amount of time, that the biometric information trend is a negative biometric information trend. In response to the determining the method may trigger, based at least in part on a slope of the negative biometric information trend, a mitigating response to the negative biometric information trend.

Abstract: Methods for augmenting a positive sentiment trend or mitigating a negative trend are provided. Sentiment trend may be derived from a sentiment analysis. Sentiment analysis may be based on aggregating communications between a first individual, group or entity and a second individual, group or entity. Sentiment analysis may include mining social media to recover a plurality of artifacts. Each of the artifacts may include a transmitting entity and a receiving entity. Methods may include identifying a transmitting entity of the artifact; identifying a receiving entity; and adding the sentiment score to an aggregated sentiment score. Aggregated sentiment score may be associated with a communication link. The sentiment score may repeatedly generate, over a pre-determined amount of time, an aggregated sentiment score for the communication link; identify a positive trend in the aggregated sentiment score; and trigger an augmenting response to the positive trend.

Abstract: Systems for leveraging voice information derived from a telephone request for customer support (“RCS”) are provided. The leveraging improves the accuracy of a sentiment analysis performed on a customer support request. The system includes a receiver configured to receive logins. Each login initiates a request. The request includes a date; a time of initiation; a location of a communication device that was used to communicate the request; a device identification number; a message derived from the request; and voice information. The system includes a processor configured to calculate a historical sentiment value, based, at least in part, on artifacts retrieved from historical information associated with the user. The processor obtains a voice sentiment value from the voice information. The processor calculates a total sentiment value based on the historical sentiment value and the voice sentiment value, and then routes the request based on the total sentiment value and the message.

Abstract: An actionable functionality simulation tool includes an HTML module and a controller module. The HTML module includes a first directive that has a value tied to a first model property. The first directive is configured to show or hide an actionable popup on a webpage. The HTML module also includes a second directive that is configured to bind an actionable button of the actionable popup to a particular action to be performed. The controller module includes a first function call configured to set the value of the first model property to true in order to toggle the display of the actionable popup on the webpage. The controller module also includes a second function call configured to bind logic to the particular action of the second directive.

Abstract: Methods, systems, and apparatuses for dynamic workflow control based on database logic are described herein. In some arrangements, a workflow control server may configure a workflow engine based on one or more data tables stored in a workflow database which may comprise a logical arrangement of workflow steps, actions, and transitions. The workflow control server may perform one or more workflow actions corresponding to a workflow step based on one or more triggers provided by a participant computing device. Responsive to performing the one or more workflow actions, the workflow control server may execute the workflow engine to perform a workflow transition between workflow steps.

Abstract: An actionable functionality simulation tool includes an HTML module and a controller module. The HTML module includes a first directive that has a value tied to a first model property. The first directive is configured to show or hide an actionable popup on a webpage. The HTML module also includes a second directive that is configured to bind an actionable button of the actionable popup to a particular action to be performed. The controller module includes a first function call configured to set the value of the first model property to true in order to toggle the display of the actionable popup on the webpage. The controller module also includes a second function call configured to bind logic to the particular action of the second directive.