Abstract: Certain aspects of the present disclosure provide techniques for providing a routing system to a user of a product. An example technique includes receiving from a user of a product a query and a personal ID. Based on the personal ID of the user, the user's profile is retrieved which comprises user attribute data, a clickstream history of the user, and a product SKU of the product. Based on the query and the user profile, processed user data is generated. Additionally, agent profile data for each available agent is retrieved, and based on the user attribute data, the processed user data, and the agent profile data of each agent, a predicted quality score is generated for each agent. The agent with the highest predicted quality score is determined, and the user is routed to the agent with the highest predicted quality score.

Abstract: The disclosed embodiments provide a system that renders a view component in a user interface of an application on an electronic device. During operation, the system generates, from content describing a view for display in the user interface, a styling path that includes a position of the view component in a content hierarchy of the view. Next, the system selects, by a styling component executing on a processor in the electronic device, a style context for the view component from a collection of style contexts by matching at least a subset of the styling path to an identifier for the style context. The system then uses the style context to render the view component in the view.

Abstract: Disclosed are techniques for generating a personalized flow for a software delivery model. These techniques identify user information expressed in natural language for a specific user. One or more user clusters may be determined for the specific user based on at least one user vector representation of a form of the user information. One or more personalized information clusters may be identified for a user cluster of the one or more user clusters based at least in part on the at least one user vector representation. A personalized software application flow may be generated and presented to the specific user by using at least the one or more personalized information clusters for the specific user.

Abstract: A method for measuring financial health involves aggregating financial data from different data sources into a single financial data warehouse; extracting multiple customer financial characteristics from the financial data warehouse to build multiple financial profiles for a plurality of known customers; training a predictive machine learning model using the multiple financial profiles of multiple known customers to obtain a trained model; generating a grade mapping table using the trained model and a pre-defined business rule; applying the trained model to the financial data of a user to obtain a financial health score set; applying the grade mapping table to the financial data of the user to obtain a financial health grade set; and presenting the financial health grade set and the financial health score set to the user via a multimedia user interface.

Abstract: A method and system provides personalized assistance to users of a data management system. The method and system trains an analysis model with both a supervised machine learning process and an unsupervised machine learning process to identify relevant assistance topics based on a user query and the attributes of the user that provided the query. The method and system outputs personalized assistance to the user based on the analysis of the analysis model.

Abstract: Dynamic machine learning modeling within a special purpose hardware platform to determine platform abandonment risks for each user having exhibited a sequence of behaviors. The enclosed examples address a computer-centric and Internet-centric problem of a service provider system management to lower platform abandonment of users, and further increase product engagement.

Abstract: This disclosure relates to systems and methods for processing electronic payments for customer purchases. In some implementations, a mobile computing device receives a payment request identifying a sales transaction between a merchant and a customer. The payment request indicates a purchase amount owed by the customer to the merchant, and carries a set of instructions. The mobile computing device activates a card reader based at least in part on the set of instructions, receives customer authorization for electronic payment of the purchase amount, instructs the card reader to process a credit card for the purchase amount based on receiving the customer authorization, and receives confirmation of payment of the purchase amount from the card reader.

Abstract: After a host client establishes a multimedia stream with a guest client, host data is received from a host application. A state machine is updated using the host data. The host application executes on the host client. Guest data is received from a guest application. The state machine is updated using the guest data. The guest application executes on the guest client. Transaction data is propagated between the host application and the guest application. The transaction data is presented with the multimedia stream. The transaction data includes the host data and the guest data. Provider data is generated responsive to updating the state machine with the host data and the guest data. The provider data is sent to the guest client. The provider data is presented with the multimedia stream by the guest application on the guest client.

Abstract: This disclosure relates to systems and methods for processing electronic payments for customer purchases. In some implementations, a system receives a payment request from a merchant, and transmits payment information to a mobile computing device associated with the merchant. The payment information includes a transaction ID to identify the purchase, a purchase amount, and instructions that cause the mobile computing device to activate a card reader, present a notification of the purchase amount to the customer, receive an acceptance of the purchase amount from the customer, and authorize the card reader to process an electronic payment for the purchase amount. The system receives payment confirmation from the mobile computing device, and provides the parameter confirmation to the merchant.

Abstract: A method for executing a computerized query includes receiving a new query from a user device. The query includes natural language text. Based on a type of user, and using an alternative term generator, a selected data model is selected from among pre-determined data models. The selected data model is particular to the type of user. Each of the pre-determined data models includes a corresponding semantic graph data model that establishes semantic relationships between words. Query words in the natural language text are compared to the selected data model using the alternative term generator to find at least one alternative term. The alternative term has a semantic relationship to a query word in query words. The semantic relationship exceeds a first threshold value. The alternative term is substituted for a query word to form a revised query. The revised query is executed on a search engine using the alternative terms.

Abstract: Systems and methods may be used to generate and use intent predictions to enhance user experience. The intent predictions may describe the data required to resolve a user request included in a user input (e.g., question, search query, and the like) submitted by a user. The intent predictions may be generated using a machine learning model that comprises a model framework for extracting features and classifying user inputs into intent classes based on the extracted features. The intent predictions may be integrated into an information service to improve business metrics including contact rate, transfer rate, helpful rate, and net total promoter score.

Abstract: Certain aspects of the present disclosure provide techniques for providing assistance to users by integrating social computing system with conversational user interface. In some cases, a user interacting with a virtual assistant of a conversational user interface provides input that the virtual assistant is not able identify a matching intent. As a result, the virtual assistant can leverage the social computing system to generate a new question based on the user input and post the question to the social computing system. Users of the social computing system can provide an answer, which the virtual assistant provides to the user in the conversational user interface. The social computing system can also generate a new intent for the virtual assistant to increase efficiency of the virtual assistant.

Abstract: Systems and methods for verifying identifies of parties to a video conference call are disclosed. An example method includes storing a plurality of first facial encodings each associated with one or more images of a registered agent, receiving, during the video conference call, a second facial encoding associated with one or more images of a person participating in the video conference call, determining that a specified registered agent is scheduled as a party to the video conference call, comparing the second facial encoding to a selected first facial encoding associated with the specified registered agent, and determining, based at least in part on the comparing, whether or not the person is the specified registered agent.

Abstract: A method for storing object state on hash chains. A block of a hash chain is located with an accessor function. The block includes a field value of a field of an object. Version data is located using the block. The version data identifies a block version of the block. The block version is compared to a function version of the accessor function. The field value from the block is returned when the block version matches the function version. A version matched accessor function is called to return the field value when the block version does not match the function version.

Abstract: A method of training machine learning models (MLMs). An issue vector is generated using an issue MLM to generate a first output including first embedded natural language issue statements. An action vector is generated using an action MLM to generate a second output including related embedded natural language action statements. The issue and action MLMs are of a same type. An inner product of the first and second output is calculated, forming a third output. The third output is processed according to a sigmoid gate process to predict whether a given issue statement and corresponding action statement relate to a same call, resulting in a fourth output. A loss function is calculated from the fourth output by comparing the fourth output to a known result. The issue MLM and the action MLM are modified using the loss function to obtain a trained issue MLM and a trained action MLM.

Abstract: Systems and methods that may be used to provide multitenant key derivation and management using a unique protocol in which key derivation may be executed between the server that holds the root key and a client that holds the derivation data and obtains an encryption key. In one or more embodiments, the derivation data may be hashed. The disclosed protocol ensures that the server does not get access to or learn anything about the client's derived key, while the client does not get access to or learn anything about the server's root key.

Abstract: Systems and methods for generating recommended offers are disclosed. An example method may be performed by one or more processors of a recommendation system and include correlating attributes of users with attributes of offers based on historical data associated with the users and offers, training a machine learning model to predict a user's interest in an offer based on the correlating, obtaining current user data, obtaining current offer data, providing the current user data and the current offer data to the trained machine learning model, generating, using the trained machine learning model, a predicted level of interest that the current user has in each respective current offer of the number of current offers, identifying, among the number of current offers, at least one current offer having a predicted level of interest for the current user greater than a value, and generating one or more recommended offers for the current user.

Abstract: Disclosed herein are systems and methods for replicating data across deployments in a routing constrained environment. To replicate data, a processor may detect a modification that changes data for a source entity within a source environment hosting a source deployment of an application. The processor may then update a target environment hosting a target deployment of the application to mirror the modification within the source environment. To update the target environment, the processor may generate a mapping artifact that identifies the source entity having changed data and the target entity within the target environment receiving the changed data. The processor may then create a mapping infrastructure including one or more compute instances that replicate the changed data for the source entity in the target entity.

Abstract: Certain aspects of the present disclosure provide techniques for improving a user experience based on electronic records of transactions. Embodiments include training a classifier using training data comprising a set of historical transaction descriptions and a set of corresponding historical classifications that indicate whether or not each historical transaction description of the set of historical transaction descriptions is associated with a user location. Embodiments further include receiving a transaction record describing a transaction associated with a user. Embodiments further include using the classifier to determine a classification for the transaction. The classification indicates whether or not the transaction description is associated with a location of the user. Embodiments further include providing, based at least in part on the classification, a communication to the user that relates to the location of the user.