Abstract: Embodiments of the present invention are directed to identifying related data, in particular, data associated with different source types. In embodiments, a first source type related to a second source type associated with a search query is identified. Field set pairs are identified from a first data set associated with the first source type and a second data set associated with the second source type. Each field set pair can include one field set associated with the first source type and another field set associated with the second source type. For each field set pair, an extent of similarity is determined between the corresponding field sets. Based on the extent of similarities between the corresponding field sets, at least one pair of related field sets is identified. An indication of the at least one pair of related field sets is provided, for example, for presentation to a user.

Abstract: Systems and methods are provided for managing data associated with a point-in-time architecture (PTA) databases. An exemplary method includes: receiving first data from a first PTA database and second data from a second PTA database; validating one or more parameters associated with the first data and the second data; comparing the first data and the second data with one or more reference data; predicting one or more events based on the comparing; generating a data report indicating the first data and the second data leads to the predicted one or more events; performing, based on the data report, surveillance of the first data and the second data during a surveillance period and using a surveillance protocol; receiving an update to at least one of the first data, the second data, or the one or more reference data; and updating at least one of the predicted one or more events.

Abstract: In one aspect, the present disclosure relates to a system for improved transactional mainframes, the system comprising a processor, a database, an application programming interface (API) module, and a transaction import module. The API module can be configured to: receive transaction data comprising a transaction type, a user identifier, one or more transaction card identifiers, and one or more fields associated with the transaction card identifiers; validate the transaction data using one or more of the stored validation rules associated with the one or more transaction card identifiers; generate one or more transaction cards; and store the transaction data and transaction cards to the database. The transaction import module can be configured to submit the transaction cards to the mainframe, view the status of submitted records, and enable retrying of transaction cards that failed to process.

Abstract: Provided are a system and method that use machine learning to identify documents to be excluded from a report or included in a report of a software application. In one example, the method may include receiving document data of a set of documents assigned to a report, executing the machine learning model on the received document data which identifies a document assigned to the set of documents that is to be excluded from the report, displaying, via a user interface, a set of line items corresponding to the set of documents, respectively, activating a user interface element of the identified document within a line item of the identified document, and in response to detecting a selection of the activated user interface element via the user interface, accepting the exclusion of the identified document from the report and move the identified document to a different report.

Abstract: Systems, computer-implemented methods, applications, and user interfaces for providing triggers in a system of record are disclosed. For example, a computer-implemented method may include: maintaining a trigger where the trigger comprises condition(s), operation(s), and/or a one-to-many operator associating a first data object with multiple second data objects in organizational data associated with an organization, where the trigger can be defined based on the one-to-many operator, and where the operation(s) and/or the one-to-many operator are based on a custom computer language; evaluating the condition(s) associated with the trigger based on an occurrence of an event associated with the first data object and/or one or more of the multiple second data objects; determining that the condition(s) associated with the trigger are satisfied causing the activation of the trigger; and/or executing the operation(s) associated with the custom computer language based on the activation of the trigger.

Abstract: Aspects of the invention include computer systems, computer-implemented methods, and computer program products configured to perform message correlation extraction for mainframe operation. A non-limiting example computer-implemented method includes receiving a first message log entry having a message identifier and message field data. The first message log entry is pre-processed to determine the message identifier and to tokenize the message field data. A second message log entry is identified based on at least one of the message identifier and the tokenized message field data. The method further includes determining that the second message log entry is correlated with the first message log entry and providing an output comprising the message correlation between the first message log entry and the second message log entry.

Abstract: A system processes data stream language expressions that combine result data streams from multiple data stream language sub-expressions. The system determines a set of fixed dimensions based on static analysis of the data stream language sub-expression. The system determines a union set representing a union of the sets of fixed dimensions. The system determines at execution time of the data stream language expression, a plurality of sets of data streams. Each set of data stream corresponds to a data stream language sub-expression from the plurality of data stream language expressions. The system correlates data streams across the plurality of sets of data streams based on the union set. The system determines result data streams for the data stream language expression by combining data values of correlated data streams.

Abstract: The third-party company may provide a user interface to a customer to submit a customer support request regarding a first company. The third-party company may receive a customer identifier from the first device and may request prediction data from the first company using the customer identifier. The third-party company may process the prediction data to predict a customer support request of the customer and generate user interface data corresponding to the predicted customer support request. The user interface data may be transmitted to the user interface before a customer support request from the customer is received.

Abstract: A system for assisting a customer is provided. The system comprises a database comprising multimedia files, wherein one or more tags are associated with one or more of the multimedia files. The system further comprises a virtual agent server 100 configured to receive input from a first user (customer) and a second user (customer service representative). Further, the virtual agent server 100 processes the received input to understand a context of the input. Subsequently, the virtual agent server 100 identifies one or more multimedia files based on the context and the tags associated with the multimedia files. Subsequently, the virtual agent server 100 shares at least one of the identified multimedia files with at least one of the first user and the second user to enable better understanding between the first user and the second user.

Abstract: A computer-implemented method of associating digital tags with digital files comprises storing a plurality of digital files having embedded therein content data and metadata including tags; receiving, via a user interface device of a client device, a first tag label containing alphanumeric text created and inputted by a user of the client device; modifying, using a controller device, a selected first one of the tags of the metadata in a first of the digital files to include the first tag label; receiving, via the user interface device or another user interface device, an instruction to search for all of the digital files having at least the first tag label; responsive to receiving the instruction, automatically searching for all of the digital files having at least the first tag label; and displaying, on a video display device associated with the client device, a first indication of the first tag label.

Abstract: The disclosed systems and methods provide non-native functionality to a distributed network for distributed ledger token verification and event permissioning. The disclosed technology receives a transfer event request from a first node associated with a first token storage, where the transfer event request corresponds to movement of a requested token amount that is associated with at least one token. In response, the transfer event request is inserted into a pending transfer log that is configured to queue pending transfer event requests. A determination is made regarding a first permission based on the currently queued pending transfer event requests, and as a result, the transfer event request is transmitted to the distributed network based on the first permission, where such transfer causes the requested movement of the requested token amount.

Abstract: The disclosed systems and methods provide non-native functionality to a distributed network for events management on a blockchain via locking queued distributed network tokens. The disclosed technology receives a transfer event request from a first node associated with a first token storage, where the transfer event request corresponds to movement of a requested token amount that is associated with at least one token. A pending transfer event log that queues pending transfer event requests is accessed and modified by adding the transfer event request to the queue of pending transfer event requests. This causes the at least one token associated with the transfer event request to be locked, thereby preventing its association with other transfer events. The transfer event request is then transmitted to the distributed network, whereby the distributed network executes the movement of the at least one token.

Abstract: Compression profiles may be searched for trained neural networks. An iterative compression profile search may be performed response to a search request. Different prospective compression profiles may be generated for trained neural networks according to a search policy. Performance of compressed versions of the trained neural networks according to the compression profiles may be tracked. The search policy may be updated according to an evaluation of the performance of the compression profiles for the compressed versions of the trained neural networks using compression performance criteria. When a search criteria is satisfied, a result for the compression profile search may be provided.

Abstract: A backup of a database is determined to be performed. A backup of at least a portion of contents of a storage volume that includes data of the database is performed. The backup includes a step of creating a new metadata tree root node. Creating the new metadata tree root node includes copying from another metadata tree root node of a tree data structure corresponding to a previous backup instance, one or more references to one or more lower tier metadata tree nodes associated with the tree data structure corresponding to the previous backup instance.

Abstract: Disclosed is an intelligent remote monitoring method for fire-fighting, including: S1, pre-loading a protocol parsing configuration file in JSON format; S2, acquiring fire-fighting status information and operation status information of fire-fighting IoT equipment to obtain a data frame of a binary protocol; S3, parsing the data frame according to the configuration file to obtain a JSON data object, and pushing the parsed data of the fire-fighting IoT equipment to a routing layer through data push technology including kafka technology and storing in a fire-fighting database; S4: presetting different application modules according to different application services, and determining a routing direction of the data of the fire-fighting IoT equipment according to rules including a device type and a device status, and routing the data of the corresponding fire-fighting IoT equipment to the corresponding application module through the routing layer for triggering processing of events including alarms and faults, so as

Abstract: A verifying entity of a decentralized system is configured to receive information associated with at least one ledger entry of a distributed ledger of the decentralized system, to verify at least a portion of one or more computations associated with the received information, to generate evidence of at least one error in the at least a portion of the one or more computations associated with the received information, and to associate the generated evidence with a public key of the verifying entity. The decentralized system may comprise a proof of space based mining system, and the at least one ledger entry of the distributed ledger may comprise at least one proof of space for the proof of space based mining system.

Abstract: In accordance with an embodiment, described herein are systems and methods for supporting slowly changing dimensions and metadata versioning in a multidimensional database, comprising. A system can comprise a computer that includes one or more microprocessors, and a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one hierarchical structure of data dimensions. A data dimension can slowly change over time. When such changes occur, metadata associated with the data dimension can be updated. Advantageously, a current snapshot of the data structure can allow searching of previous changes to the slowly changing dimension based upon the metadata.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for ranking query completions based on activity session data. One of the methods includes receiving a query prefix from a user. A reference parameter for the user is obtained. One or more likely queries that are likely to co-occur with the reference parameter in user activity sessions are identified, wherein each likely query has an associated prediction score. A ranking of the one or more likely queries is provided in response to receiving the query prefix.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to automatically compute features from a data stream. In some implementations, a method includes receiving a data stream comprising a plurality of data fields. The method further includes storing at least three copies of data in the data stream in a database, wherein each copy is stored on a corresponding hardware storage device. The method further includes performing, one or more rollup operations on a first copy of the data to compute one or more aggregate features and storing the one or more aggregate features on each of the hardware storage devices. The method further includes receiving a request for a particular aggregate feature and providing the particular aggregate feature in response to the request.

Abstract: Pipeline-based techniques for system configuration management are provided. For example, a method comprises, in a pipeline-based system comprising a set of one or more pipelines, for a given one of the set of one or more pipelines, collecting a set of one or more configuration datasets respectively associated with a set of one or more elements of an information processing system, wherein each of the configuration datasets of the collected set of one or more configuration datasets is specific to the respective element of the information processing system from which it is collected; executing a set of one or more configuration checks on the set of one or more configuration datasets; receiving a set of one or more output results from the executed one or more configuration checks; and generating at least one report from the one or more output results.