Abstract: Method, system, device, and non-transitory computer-readable medium for classifying a vehicle trip.

Abstract: Monitoring transaction activity for system requests for a set of entities authorized to request services of a system is described. Entities with high feature values for respective features of the set of activity based features are identified to produce a set of outlier entities. The outlier entities are filtered from the set of entities. A set of clusters are created from the filtered set of entities based on the set of activity based features so that each entity in the filtered set of entities is assigned to a cluster. Values for the set of activity based features are established for each cluster. A risk is assigned for each cluster based on the values of one or more of the set of activity based features. Each of the filtered set of entities are monitored based on the risk assigned to the respective clusters to which the respective entities belong.

Abstract: The disclosed embodiments can be used to automate the acquisition and management of user consents for one or more campaigns, thus reducing the possibility of unintended violations of consent requirements as compared with existing systems. In accordance with the disclosed embodiments, each user consent may be associated with at least three different values. The consent management system may be configured to filter consent values for various users and send user-consent requests to certain users based on their filtered user-consent values. In some disclosed embodiments, a user may provide consent to allow communications of the user's information to certain “connected parties.” The connected parties, moreover, may need to separately provide user consent(s) as necessary to effectuate communications for a campaign in compliance with one or more laws, rules, or regulations.

Abstract: The present disclosure relates to a system, method, and computer program for adjusting operations of a customer service application based on metrics generated as a result of substantially real-time monitoring of entity states within the customer service application. The system receives entity events from a plurality of services associated with the customer service application. It tracks states of entities in substantially real time within the customer service application based on the events and the state machine logic for the customer service application, including identifying any entities in an anomalous state. For each non-anomalous state transition, one or more state transition measurements are calculated. The system generates metrics for the customer service application based on the state transition measurements for entities in a non-anomalous state and adjusts the operations of the customer service application in substantially real time based on the metrics.

Abstract: Systems and methods for data corroboration and forecasting in which a sever generates structured customer feedback data from unstructured customer verbatim data and uses unsupervised machine learning modeling techniques to identify similar word clusters within the structured customer feedback data, classifies the identified word clusters into multiple categories of customer issues, and detects one or more trending customer issues within the multiple categories. The server may also retrieve web/mobile application usage analytics data and system logs data and use unsupervised machine learning modeling techniques to corroborate customer web/mobile navigation and service issues associated with the structured customer feedback data.

Abstract: Embodiments described herein are generally directed to use of a chatbot to identify a customer-specified product support issue and provide appropriate troubleshooting guidance. According to an example, free text input describing an issue associated with a product line of a vendor is received from a user via a chatbot. A vector representation of the issue is created by tokenizing and vectorizing the free text input using a word association model corresponding to the product line. It is determined whether the issue matches at least one category within multiple issue categories for the product line by performing similarity scoring between the vector representation and multiple vectors created based on top words per issue category of the multiple issue categories. Responsive to an affirmative determination, an automated, interactive, conversational troubleshooting dialog is initiated with the user via the chatbot and guided based on a decision tree for the at least one category.

Abstract: A system and/or method can be provided for improving applicant diversity by giving institutions selectable and adjustable application windows, thereby providing a number of benefits including an enriched learning environment. A similar system or method may be used to manage the availability of application windows in general to ensure that a diversity of applicant groups have an opportunity to apply.

Abstract: A micro-application framework includes instantiating, on a client computer, a user interface configured with a hosting application operable to execute one or more micro-applications. During runtime of the user interface, a request for a CRM function is received. A request is sent for a micro-application that corresponds to the requested CRM function. The user interface receives from a server hosting the micro-application a data package that includes the micro-application corresponding to the requested CRM function. The executable code in the data package is executed in the hosting application via the execution environment. One or more interactive areas are rendered that are configured to display information pertaining to the requested CRM function.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: The present technology pertains to keeping track of a purchase status of a product and delivering pre-purchase product experiences prior to the purchase of the product and a post-purchase product experience after the purchase of the product. The present technology provides for a device to identify a product and to request a purchase experience that is both informative and useful based on the purchase status of the product.

Abstract: Gradated access to services based on identity verification (IDV) is described herein. In an example, a computing device can receive identifying information of a user and can select, from a plurality of IDV paths and based at least in part on the identifying information of the user, an IDV path for verifying an identity of the user using one or more factors. Based at least in part on the one or more factors, the computing device can determine a score indicative of whether the identifying information provided by the user accurately identifies the user. The score can be used for the benefit of one or more service providers to verify an identity of the user and/or determine gradated access to one or more services of the one or more service providers.

Abstract: A method comprises receiving a request to generate a customized dataset comprising data stored onto a blockchain; retrieving user work history data associated with a user from one or more block instances of the blockchain; in response to presenting the user work history data on a display of the second computing device, receiving a selection of a subset of the user work history data from the second computing device; generating a blockchain address corresponding to one or more hash values of a subset of the one or more block instances associated with the selection of the subset of the user work history data; and transmitting the blockchain address to the second computing device.

Abstract: A system, method and computer program product for continuous monitoring based on biometric information, includes an employee database storing employee information, including an employee name photograph; a notification server transmitting an incoming event, including an employee verification request, including a name of an employee name and a photograph of the employee to be verified; and a verification server couple to the notification server and accessing the employee database, based on the incoming event received from the notification server. The verification server determining if the name of the employee to be verified matches a name in the employee database, and if so, determining if the photograph of the employee to be verified biometrically matches a photograph corresponding to the matching name in the employee database, and if so, transmitting a positive verification result notification including multijurisdictional arrest and conviction data to a customer device via the notification server.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by determining the current activities of users based on location sensor information from the users' computing devices and generating customized media content items based on their activities. The media content can be generated for a variety of topics and shared with other users. For example, media content (e.g., images or video) can be generated and displayed on a user's computing device, as well as transmitted to other users via electronic communications, such as short message service (SMS) or multimedia service (MMS) texts and emails.

Abstract: A system and/or method can be provided for optimizing data-sharing in a multi-institutional application system using, where appropriate, semi-blind data-viewing in a semi-cooperative context. A method for evaluating agent quality, individual student success probability, and sharing these evaluations among a plurality of applicants to a plurality of academic programs while retaining the confidentiality of individual applicants is shown. Multiple parameters both immediate and historic are used to evaluate agent quality and individual student success probability.

Abstract: A system and/or method can be provided for improving applicant diversity by giving institutions selectable and adjustable application windows, thereby providing a number of benefits including an enriched learning environment. A similar system or method may be used to manage the availability of application windows in general to ensure that a diversity of applicant groups have an opportunity to apply.

Abstract: An apparatus comprising a communications interface configured to communicate over one or more networks, at least one processor and at least one memory including program code is provided. The at least one memory and the program code configured to, with the processor, cause the apparatus to at least receive, via the communications interface, an interparty transaction request. The interparty transaction request corresponds to an interparty transaction and identifying a first party and a second party. The apparatus generates a smart contract based on the interparty transaction request; stores a data entry indicating the generation of the smart contract to a distributed ledger; executes the smart contract to cause settlement of the interparty transaction between the first party and the second party; and stores a data entry indicating the settlement of the interparty transaction to the distributed ledger.

Abstract: The presently disclosed subject matter includes an apparatus with a processor and a memory storing code which, when executed by the processor, causes the processor to receive a data profile associated with a candidate resource, the data profile includes a set of attributes of the candidate resource which are relevant for assessing the candidate resource's suitability to satisfy a particular resource demand. The apparatus extracts an n-dimensional feature vector from the received data profile, the n-dimensional feature vector capturing aspects of the candidate resource's attributes and process said n-dimensional feature vector with a first ensemble machine learning model to generate a first suitability factor. Likewise, the apparatus process said n-dimensional feature vector with a second ensemble machine learning model to generate a second suitability factor. The apparatus determines whether to allocate the candidate resource to the particular resource demand using said first and second suitability factors.

Abstract: Machine learning-based approaches are used to automatically establish customer support sessions and/or assign customer support requests to customer support agents or other appropriate resources. For example, during a customer support session between a customer and a customer support agent, a trained model can process session data obtained during the session to determine prediction information (e.g., a next message prediction score, a predicted time for receiving a next message, a capacity score, etc.) The prediction information can be compared to an appropriate threshold to determine whether to establish a customer support session and/or assign a customer support request to the agent, even though the agent may otherwise be considered at capacity. In the situation it is determined to establish a session and/or assign a request to the agent, a session can be established and/or a request can be assigned to the agent based on scheduling or other information.

Abstract: A computing system accesses crime incident data from two or more organization systems. The crime incident data includes a first set of inputs associated with a plurality of crime incident groupings and a second set of inputs associated with incident data for incidents associated with each of the two or more organization systems. The computing system preprocesses the crime incident data to remove incidents that include suspect identifiers not present in at least two or more organization system. The computing system analyzes the preprocessed crime incident data to identify links between incidents across two or more organization systems using a trained crime linking model. The computing system generates a link between a first incident at a first organization system of the two or more organization systems and a second incident at a second organization system based on the analyzing.