Abstract: Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically modifying the distributed program execution in various manners, such as based on monitored status information. The dynamic modifying of the distributed program execution may include adding and/or removing computing nodes from a cluster that is executing the program, modifying the amount of computing resources that are available for the distributed program execution, terminating or temporarily suspending execution of the program (e.g., if an insufficient quantity of computing nodes of the cluster are available to perform execution), etc.

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: Systems and methods for mapping an electronic document to a particular transaction category are disclosed. An example method may be performed by one or more processors of a categorization system and include receiving, from a user via an interface, an electronic document associated with a transaction between the user and a particular establishment, receiving, from the user via the interface, an image of the particular establishment, identifying in the image, using an image recognition engine, at least one of a sign or a symbol representative of the particular establishment, extracting, using an analytics module, location information from at least one of the image or a mobile device, determining, using the analytics module, a name of the particular establishment based on at least one of the location information or the at least one sign or symbol, and mapping the electronic document to a particular transaction category based on the determined name.

Abstract: A method and system facilitates importation and categorization of financial documents in a financial system. The method and system include receiving source data and externally generated metadata associated with a financial document, such as a receipt of purchase. The method and system further include analyzing the metadata and categorizing the financial document based on the metadata.

Abstract: External events are correlated with patterns of characteristics in virtual assets. Upon detection of a pattern in a different asset that matches a pattern corresponding to an event, that detection is treated as a trigger event, with resulting responsive action(s) and other process operations. Security threats are managed in a similar manner, with first security threats being added to a collection of security threats. When a virtual asset detects a change in operating characteristics, a request is provided for the collection of current security threats, and the collection of security threats is provided responsive to the request.

Abstract: Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.

Abstract: A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.

Abstract: A method and system provides a tax refund confidence indicator to a user of a tax return preparation system, according to one embodiment. The method and system include receiving user current tax related data from a user and receiving historical tax related data associated with previously prepared tax returns. The method and system further includes generating estimated tax refund data and confidence score data indicative of the reliability of the estimated tax refund data. The method and system include providing the estimated tax refund data and the confidence score data to the user.

Abstract: Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically modifying the distributed program execution in various manners, such as based on monitored status information. The dynamic modifying of the distributed program execution may include adding and/or removing computing nodes from a cluster that is executing the program, modifying the amount of computing resources that are available for the distributed program execution, terminating or temporarily suspending execution of the program (e.g., if an insufficient quantity of computing nodes of the cluster are available to perform execution), etc.

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: Computer-implemented systems, methods and articles for preparing and/or submitting a plurality of different types of compliance forms for submission to a regulatory agency. The system includes a computing device, a data store, and a compliance form software program executable by the computing device. The compliance program includes a universal calculation engine, logic agent and user interface manager which are configured to process a respective domain model configured for each type of compliance form. Each domain model includes a calculation graph, a completeness model comprising decision table(s) and/or completeness graph(s), user interface assets and filing rules configured specifically for a particular type of compliance form. The rules and regulations for each type of compliance form are embodied in the declaratory data structures of the respective calculation graph and completeness graph for each domain model.

Abstract: A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.

Abstract: A method for providing application content including obtaining, by a declarative content engine executing on a computer processor, an initial application content from a content repository and expressing the initial application content in a declarative programming language to obtain declarative content and transmitting the declarative content to a user experience player (UXP). The UXP processes the declarative content to obtain the initial application content, binds the initial application content to first platform-specific templates and first platform-specific navigation patterns, and renders the initial application content in a first platform-specific user display format.

Abstract: A method and system include identifying a virtual asset creation template associated with virtual assets to be verified. A test virtual asset is generated using the virtual asset creation template and deployed in a testing environment. The test virtual asset is then analyzed in the testing environment to identify any vulnerabilities. If a vulnerability is identified in the designated test virtual asset, a remedy to the vulnerability is applied to the virtual asset creation template which is used to create a virtual asset in a production environment. The method and system further include monitoring the production environment virtual asset for potential security threats, with a virtual asset agent, and determining a severity of identified security threats. and potentially creating a new virtual asset with the virtual asset agent and decommissioning the current virtual asset as a result.

Abstract: A system for calculating an estimated result for an electronic tax return to be prepared before a user begins to prepare the electronic tax return using an electronic tax return preparation program includes a server computer having a predictive model, and a user computer having a browser program. The user computer and the browser program are operatively coupled to the server computer and the predictive model by a network. The server computer is configured to obtain a first taxpayer datum associated with a taxpayer and execute the predictive model, which generates a predicted taxpayer datum for the taxpayer based on the first taxpayer datum. The server computer is configured to calculate the estimated result using the predicted taxpayer datum. The user computer is configured to display the estimated result to the user before the user begins to prepare the electronic tax return using the electronic tax return preparation program.

Abstract: A method and system provides access control encryption for a file system. A resource management module manages access to data on a storage container and hosts a virtual file system including files representing the data on the storage container. An access control and encryption module encrypts each of the files with a respective file encryption key. The access control module generates a plurality of application containers each associated with a respective user and that include respective lists of files that the respective user is authorized to access. The access control and encryption module generates decrypts the files and allows access to files based on the lists of files in the application containers.

Abstract: A set of techniques is described for monitoring and analyzing crashes and other malfunctions in a multi-tenant computing environment (e.g. cloud computing environment). The computing environment may host many applications that are executed on different computing resource combinations. The combinations may include varying types and versions of hardware or software resources. A monitoring service is deployed to gather statistical data about the failures occurring in the computing environment. The statistical data is then analyzed to identify abnormally high failure patterns. The failure patterns may be associated with particular computing resource combinations being used to execute particular types of applications. Based on these failure patterns, suggestions can be issued to a user to execute the application using a different computing resource combination.

Abstract: Techniques are described for facilitating performance of tasks involving human review of media data (e.g., images, audio clips, video clips, etc.), such as to identify one or more targets of interest. The media data review may be performed for various reasons, such as to assist in locating one or more target objects in a large geographical area (e.g., one or more missing people or vehicles) based on human review of large quantities of images that each correspond to a small subset of the geographical area. When one or more of the reviewed media data pieces are identified as being relevant, information about those identified media data pieces may be used in various ways. Furthermore, in at least some situations, the media data review may be part of a charitable effort that uses human volunteers to review the media data without monetary payment or other compensation.

Abstract: Intelligent content delivery enables content to be delivered to different devices in formats appropriate for those devices based on the capabilities of those devices. A user might access the same piece of content on two different devices, and can automatically receive a higher quality format on a device capable of playing that higher quality format. The user can purchase rights to content in any format, such that as new formats emerge or the user upgrades to devices with enhanced capabilities, the user can receive the improved formats automatically without having to repurchase the content. Further, the user can pause and resume content between devices even when those devices utilize different formats, and can access content on devices not otherwise associated with the user, receiving content in formats that are appropriate for those unknown devices even if the user has not previously accessed content in those formats.

Abstract: Emotional state data is used to tailor the user experience of an interactive software system, by monitoring and obtaining data about a user's emotional state. Invoice data is further used, and organized in a particular manner for presentation to the user based on a predicted future emotional state of the user. Emotional state data is analyzed and used to dynamically modify the user's experience by selecting user experience components and invoice presentation characteristics based on the analysis of the user's emotional state data. Different types of user experience components can be utilized to adjust the user experience to adapt to the user's new emotional state, prevent the user from entering an undesirable emotional state, and/or encourage the user to enter into a desirable emotional state.