Abstract: Certain aspects of the present disclosure provide techniques for encrypting fields in a profile. One example method generally includes adding a profile associated with a user to a profile snapshot queue and receiving an update to the profile from the user. The method further includes encrypting updated fields of the profile with private keys and encrypting the private keys with a public key of a first consumer of a plurality of consumers to generate encrypted keys. The method further includes storing the encrypted keys in a header of the update and adding the update to a live update queue. The method further includes receiving a request by the first consumer to access the profile, transmitting the profile from the profile snapshot queue to the first consumer and transmitting the update from the live update queue to the first consumer.

Abstract: A computer analytic system for allocating resources of an electronic tax return preparation system, the system includes an information module configured to collect taxpayer data of a user, the taxpayer data including an indicator of an increased likelihood that the user will abandon the electronic tax return preparation program. The system also includes a memory module configured to store the collected taxpayer data. The system further includes a retention module configured to analyze the collected taxpayer data and generate a resource allocation recommendation based on the collected taxpayer data.

Abstract: A system and method for information extraction character level features. The system and method may be used for data extraction for various types of content including a receipt or a tax form.

Abstract: Systems and methods here may be used for pre-processing images, including using a computer for receiving a pixelated image of a paper document of an original size, downscaling the received pixelated image, employing a neural network algorithm to the downscaled image to identify four corners of the paper document in the received pixelated image, re-enlarging the downscaled image to the original size, identifying each of four corners of the paper document in the pixelated image, determining a quadrilateral composed of lines that intersect at four angles at the four corners of the paper document in the pixelated image, defining a projective plane of the pixelated image, and determining an inverse transformation of the pixelated image to transform the projective plane quadrilateral into a right angled rectangle.

Abstract: A system and method for extracting data from a piece of content using spatial information about the piece of content. The system and method may use a conditional random fields process or a bidirectional long short term memory and conditional random fields process to extract structured data using the spatial information.

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: A method for organizing an application workflow for users that may transmit, to a user device, a first content for a first field of multiple fields. The method may receive, in response to transmitting the first content and from the user device, user data for the first field. The method may obtain a dynamic set of fields selected from the fields, where a portion of the fields are excluded from the dynamic set of fields based on the user data. The method may select, according to a priority of the fields, a second field from the dynamic set of fields. The method may transmit, to the user device, a second content for the second field.

Abstract: A method includes receiving, at a test identification service, a request to test a first service in an enterprise environment, identifying a service call of the first service, and identifying, using an endpoint of the service call, a second service called by the first service, the second service executing in the enterprise environment. The method further includes identifying a subset of tests from a test registry service including multiple tests, the subset of tests being configured to test the second service, and testing, using the subset of tests, the second service in the enterprise environment.

Abstract: A method may include obtaining, from a user, an initial expression including an operator and an input extracted from a data source. The operator may be applied to the input. The method may further include obtaining, using a contextual mapping data structure, a contextualized expression including the input and the data source. The contextual mapping data structure may include a context corresponding to the user. The method may further include generating a result by evaluating the contextualized expression, obtaining, using a rule table, a validation rule corresponding to the contextualized expression, and triggering an alert in response to applying the validation rule to the result.

Abstract: API gateways are updated utilizing canary release deployment in which a message broker delivers update messages to the API gateways first using a point-to-point messaging model and then a publish-and-subscribe messaging model. All the API gateways are capable of receiving point-to-point messages and publish-and-subscribe messages. First, a canary API gateway receives an update message from a message queue of the message broker and deploys the associated update on the canary API gateway. If deployment of the update is successful, then non-canary API gateways receive the update message from a message topic of the message broker and deploy the associated update on the non-canary API gateways.

Abstract: Disclosed methods and systems provide domain-specific type ahead suggestions for search query terms with a customer self-service system for a tax return preparation system, according to one embodiment. Type ahead suggestions include suggestions for completing a single search query term and/or suggestions for completing a search query having multiple search query terms. The customer self-service system receives one or more search query terms in a search text box, searches for potential search queries that are likely to complete the one or more search query terms, and provides a selected one of the potential search queries in the search text box as a type ahead suggestion, adjacent to the received one or more search query terms, according to one embodiment. The customer self-service system selects one of the potential search queries based on the received search query terms, the user's profile, and/or the user's tax data, according to one embodiment.

Abstract: This disclosure relates to customizing deployment of an application to a user interface of a client device. An exemplary method generally includes training a model based on historical context information of a plurality of users by identifying correlations between the historical context information and a plurality of widgets and storing the correlations in the model. The method further includes receiving context information from the client device. The method further includes determining a user intent based on the context information using the model. The method further includes selecting one or more widgets to include in a custom user interface definition based, at least in part, on the user intent. The method further includes transmitting, to the user interface of the client device, the custom user interface definition.

Abstract: A method may include extracting first entities from a first portion of an unstructured data source associated with a user, obtaining, based on the first entities, a contract model including elements and a contract type, generating, by applying the contract model to the first entities, a proposed contract including a contract score and, for each element, element values. Each element value may include an element value score. The method may further include identifying a structured data source associated with the user, obtaining, from the structured data source, structured data corresponding to the first entities, correlating the structured data with an element value of the proposed contract, and modifying, by applying the contract model to the structured data, the element value score of the element value.

Abstract: Forecasts are provided based on dynamic model selection for different sets of time series. A model comprises a transformation and a prediction algorithm. Given a time series, a transformation is selected for the time series and a prediction algorithm is selected to make a forecast based on the transformed time series. Sets of time series are distinguished from each other based on diverse sparsities, temporal scales and other time series attributes. A model is dynamically selected based on time series attributes to increase forecasting accuracy and decrease forecasting computation time. The dynamic model selection is based on the creation of a meta-model from historical sets of historical time series.

Abstract: A method and system groups user accounts in a financial management system based on the similarities of the financial transactions associated with the accounts. The method and system groups merchants involved in the financial transactions based on how financial transactions involving the merchants are sorted into groups of merchants. The method and system group users based on how the users sort financial transactions into their accounts. The method and system assist users to sort future financial transactions based on the groups of accounts, the groups of merchants, and the groups of users.

Abstract: An application determines an emotional state of a user based on evaluating facial recognition data of the user captured from the user interacting with the application. The application receives a request from the user to initiate a support call. The request identifies the emotional state of the user. The application predicts, from a set of outcomes of support calls processed by support agents interacting with users having different emotional states, an emotional state that increases a likelihood of achieving a specified outcome for the support call based on the emotional state of the user. The application identifies an available support agent having the predicted emotional state, and assigns the user to interact with the identified support agent for the support call.

Abstract: A method and system generate sample data set for efficiently and accurately testing a new calculation for preparing a portion of an electronic document for users of an electronic document preparation system. The method and system receive the new calculation and gather historical use data related to previously prepared electronic documents for a large number of historical users. The method and system group the historical users into groups based on which sections of a previous version of electronic document preparation software were executed for each historical user in preparing electronic documents for the historical users. The groups are then sampled by selecting a small number of historical users from each group.

Abstract: A call center records a voice conversation between a call center agent and a customer. A call recording of the voice conversation is transcribed. When a customer provides a call center agent with sensitive information, the sensitive information is detected from the transcribed voice conversation. Upon detection of the sensitive information, the sensitive information is redacted from the call recording. Alternatively, when sensitive information is detected, a notification is provided to the call center agent to pause and resume the recording.

Abstract: A method to predict a delay involves receiving an open invoice sent by a company to a customer, extracting, using a programmable interface, a set of company data, a set of customer data, and a set of invoice data from a management application (MA) and the open invoice; refining, using a set of algorithms, the set of company data, the set of customer data, and the set of invoice data into a set of invoice attributes, a set of company features, and a set of customer features; predicting a delay in processing the open invoice using a trained model analyzing the set of company features and the set of customer features; updating, at an expiration of a predetermined timespan, the MA to add the delay to a due date of the open invoice by including the set of company features; and updating, at the expiration of the predetermined timespan, the MA to add the delay in processing the open invoice by including the set of customer features.