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: 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.

Abstract: Runtime computer software product management system including a computer database, an access control system and a composite model including an integrated entitlement-service state model with first state data specifying access to a subscription of a computer software product of a host and second state data specifying permissible actions involving the subscription based at least in part upon the first state data. The access control system is in communication with the computer database and generates grants for an accountant and client based on the entitlement-service state model and receives a request from the computer software product for the client to access the product. The access control system determines a grant status based at least in part upon the first grant status and the second grant status and responds to the request with the determined grant status which governs client access to the computer software product.

Abstract: A method and system generates extended patterns from base patterns with an automatic pattern generation engine. The method and system tests the extended patterns with an automatic pattern testing engine. The patterns correspond to configurations for implementing cloud-based applications. The patterns are extendable to make additional extended patterns. Extended patterns carry the characteristics of the patterns from which they were extended. Updating a base pattern with new security measures causes a cascade effect that updates all extended patterns that descend from the base pattern.

Abstract: A method includes establishing a network connection with a source computing device and an application services computing device, receiving, via the network connection, a source event stream at the application services computing device, and extracting a sample of the source event stream. The method further includes partitioning the sample of the source event stream into fields, identifying a field data type of a field of the multiple fields in the sample, identifying a distribution of values of the field in the sample, and extrapolating, from the sample of the source event stream, extrapolated functions for the fields. Extrapolating an extrapolated function is dependent on the field data type and the distribution of the field. The method further includes transforming, based on the plurality of extrapolated functions in the configuration file, the source event stream to obtain a transformed event stream, and analyzing, by a target machine learning model, the transformed event stream.

Abstract: The disclosed embodiments provide a system that manages synchronization between a profile store and a source of truth that is used to update the profile store. During operation, the system obtains a request to compare a first set of attributes from a profile for an entity in the profile store with a source of truth. During a period for delaying processing of the request, the system reduces a load on the source of truth by ignoring additional requests to compare the profile with the source of truth. After the period has passed, the system obtains a first set of attributes from the profile and a second set of attributes for the entity from the source of truth. The system then compares the first and second sets of attributes to detect and correct mismatches between the first and second sets of attributes.

Abstract: One embodiment of the present invention provides a system for automatically modifying computer parameters as an incentive for complying with data policies. During operation, the system receives, at a computing system, a data policy definition, wherein the data policy definition comprises: one or more metrics associated with data usage, and one or more desired vectors associated with the one or more metrics. Next, the system receives, at the computing system, usage statistics for data, wherein the usage statistics comprise the one or more metrics for one or more clients. The system then analyzes the usage statistics to determine, at the computing system, a first score indicating how a first client in the one or more clients is performing compared to the one or more desired vectors for the one or more metrics. Finally, the system automatically modifies a parameter of the computing system associated with the first client based on the first score.

Abstract: Artificial intelligence, big data, and crowd sourcing techniques are utilized to efficiently and effectively determine permissions that should be granted to a party within an organization. In one example, the permissions granted to a party within an organization are determined using one or more algorithms to identify, weight, and correlate historical and current permissions to party attributes for parties within the organization and/or for similar parties in similar organizations. In one example, the activity of the party within the organization is then monitored and the permissions granted the party are automatically modified as needed to allow the party to perform their tasks in the organization as the party's responsibilities within the organization evolve.

Abstract: Embodiments presented herein provide a partner authentication (PA) system that coordinates a network-based authorization process for an application. The PA system exchanges a series of messages with the application seeking an access token for a protected resource, an authorization server associated with the resource, and an agent executing on a device accessed by a user who wants the application to access the resource. The PA system and the agent communicate with the authorization server on behalf of the application throughout the authorization process. The PA system receives an access token and a refresh token from the server on behalf of the application and sends a partner authorization (PA) token to the application. When the application seeks access to the resource that is available to authorized parties via the resource server, the application sends the PA token to the PA system and receives the access token in return.

Abstract: Various aspects described herein are directed to methods and systems that preprocess an electronic document or some data therein and conceal sensitive data in the electronic document by applying steganography to the data associated with one or more fonts. A steganography map is generated or updated to include steganography information about applying steganography to the data. Cryptography may be applied to the steganography map; and the electronic document may be transformed into a different document format.

Abstract: Disclosed are techniques for classifying inquiries in real-time or nearly real-time. These techniques identify or generate a data model that receives and determine one or more classes for the inquiry in real-time or nearly real-time at least by applying a hierarchical set of rules in the data model to the inquiry. A hierarchical class data structure at least by storing and indexing the one or more classes based in part or in whole upon a hierarchical structure of the one or more classes in a non-transitory computer memory.

Abstract: Big data analysis methods and machine learning based models are used to provide offer recommendations to consumers that are probabilistically determined to be relevant to a given consumer. Machine learning based matching of user attributes and offer attributes is first performed to identify potentially relevant offers for a given consumer. A de-duplication process is then used to identify and eliminate any offers represented in the offer data that the consumer has already seen, has historically shown no interest in, has already accepted, that are directed to product or service types the user/consumer already owns, for which the user does not qualify, or that are otherwise deemed to be irrelevant to the consumer.

Abstract: An execution platform comprising a workflow engine and an application engine is provided. A workflow definition associated with an application is received. The workflow definition is used to run an application workflow to perform an action with respect to the application, at least in part by causing an executable binary to be run by the application engine.