Abstract: An architecture and techniques are presented for defining and generating meta machine data, which can enable use of the meta machine data to control or improve machine data pipeline operations. Input from existing security or privacy documents or other documents or modalities can be used to determine a format of the meta machine data. For example, the meta machine data can comprise a data pipeline configuration data structure configured to store configuration information of a data pipeline that communicates the machine data, a data quality metrics data structure configured to store data quality information of a consuming application that consumes the machine data, and a data governance data structure configured to indicate administrative governance information with respect to the machine data.

Abstract: A system and method to manage a data graph including data associated with a user system. The system and method receive multiple input document streams from multiple different data sources. A first document is identified from one of the multiple input document streams, the first document having a first schema including data associated with the user system. The first document is transformed from the first schema to a second schema to generate a first transformed document including at least a portion of the data. The portion of the data of the transformed first document is merged into the data graph stored in a graph database.

Abstract: Computer implemented methods, systems, and computer program products include program code executing on a processor(s) identifies in a query from a requestor, a predicate(s) comprising a partial access of large object (LOB) data from a LOB. The processor(s) caches a location of the partial access of the LOB data in a buffer, labeling the location with predicates. The processor(s) determines, based on comparing a pre-set access count to a count of accesses for the location that the location is a frequently accessed location and stabilizes the location in an index. The processor(s) determines that the location meets a length threshold and a frequency threshold and saves the LOB data requested in the partial access of the LOB data inline with a base row.

Abstract: A computing system generates a feature for a machine learning model by receiving identification of character data. The character data is stored in a database comprising multiple documents. One or more documents of the multiple documents pertain to a respective entity of multiple entities. The computing system generates structured data from the character data by generating multiple structured data terms; and storing the multiple structured data terms in respective data elements of multiple memory blocks in memory of the computing system. The computing system generates the feature for the machine learning model based on one or more of: at least two structured data terms in different memory blocks of the multiple memory blocks; and data manipulation of a structured data term in a memory block of the multiple memory blocks.

Abstract: Apparatuses, methods, and systems for filtering entities within a database based on rules of a user-defined segment definition. One method includes creating data tables for storing user-defined segment definitions in the database, the data tables including the user-defined segment definitions and criteria, receiving new user-defined segment definitions, transforming the new user-defined segment definitions, storing the transformed new user-defined segment definitions in the database, composing a user-defined query based on the transformed new user-defined segment definitions as stored in the database, wherein the user-defined query contains logic that interprets the filter definition tuples as native operations provided by the database, and running the composed user-defined query against the data tables to determine which of the entities qualify for membership in new segments based on each of the new user-defined segment definitions as determined by the logic contained in the composed user-defined query.

Abstract: A system and method for maintaining data quality, including: periodically updating, at a first computing apparatus, a source data table maintained at a second computing apparatus at a first time interval; periodically updating, in an iterative or recursive manner at the first computing apparatus, a batch data table maintained at the second computing apparatus at a second time interval; obtaining, at the second computing apparatus from an information system, one or more data tables, metadata, and one or more transaction tables; determining, at the second computing apparatus, whether a refresh timestamp or a modification timestamp is within a predetermined time period from a timestamp of the one or more transaction tables; when it is within the predetermined time period, updating a data visualization application for reviewing the timestamp negative result, wherein the data visualization application comprises a graphical user interface that is accessible using a third computing apparatus.

Abstract: Systems and methods are described for implementation by a streaming data processing system of a processing pipeline that obtains data items from one or more data sources. The one or more data sources may include multiple partitions of a topic or multiple topics. The one or more data sources are defined by a data pattern, a group of tenants, or a process. The implementation of the processing pipeline can include identifying the one or more data sources to obtain data items. The processing pipeline can include a plurality of processing tasks to obtain the data items. The streaming data processing system can utilize a workload coordinator to dynamically assign particular data sources to particular processing tasks. The implementation of the processing pipeline can further include executing the plurality of processing tasks to cause processing tasks to obtain data items from assigned data sources and process the data items.

Abstract: A computer-implemented method for receiving, at a database, an analytics request associated with a selected data line from a database and reading a set of additional bytes from the database corresponding to the selected data line. The method may further include parsing and formatting the set of additional bytes read from the database to generate, at the database, an analytics reply to the analytics request, where each of a plurality of data lines in the database represents a search query and where the analytics data comprises a number of search query requests on a subject matter and a number of search query requests for private data.

Abstract: The present disclosure provides a data display method, device, computer apparatus and system, wherein the method comprises: receiving search information in response to a trigger operation on a search tag, wherein the search information corresponds to at least one first book attribute dimension, and the first book attribute dimension is associated with at least one second book attribute dimension; acquiring a search associative word based on the search information, wherein the search associative word includes a first associative word and a second associative word, the first associative word is determined according to the search information and the first book attribute dimension, and the second associative word is determined according to the second book attribute dimension; displaying the search associative words in an other interface area than the search tag.

Abstract: A method for computationally scoring the trustworthiness of source data begins with a subset of the raw source data. Fields and related fields are identified, profiled, and results aggregated. In addition, the subset of raw source data is input to an entity resolution system, with results summarized and aggregated. The output of these two streams of processes are used to compute a scorecard. In addition, a sandbox of the entity resolution system's data graph is constructed, the sandbox is modified with the source data, and the difference between the baseline sandbox and modified sandbox is computed. Changes to entities are computed for all entities as well as for most sought-after entities, and the results are summarized and aggregated into the overall scorecard.

Abstract: A system for securely and efficiently obtaining data from a process plant and processing that data for consumption by one or more external applications or systems includes receiving event data from various data sources in or associated with a plant via various different data formats and data communication structures at a centralized server or gateway, striping off the communication format structure from the data, placing the data, including metadata associated with the data, into an event stream, and making the data in the event stream available to a processing infrastructure that processes that data in a comprehensive and robust manner for easy consumption by external data mining, data visualization and data analytic systems or applications.

Abstract: Systems and methods for database record synchronization are disclosed herein. An example apparatus includes at least one memory; machine readable instructions; and processor circuitry to execute the machine readable instructions to perform a comparison between a first record and a second record, the first record associated with a first database and the second record associated with a second database different than the first database, the first record including a base record and a supplemental record and the second record including a base record and a supplemental record; determine a sequence in which to modify the second record based on the comparison; and cause transmission of a first message and a second message to the second database based on the sequence to modify the second record.

Abstract: A document source identification system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to cause the system to receive uploaded document(s) having at least one extractable data entry. The system may categorize the document, and extract at least one data entry from the document. The system may normalize each extracted data entry and execute a deterministic ID search to determine that the normalized data entry matches zero, one, or more than one account data entries associated with user accounts. Responsive to an exact match, the system may link the uploaded document to a user account associated with the matching data entry. Responsive to zero or multiple matches, the system may execute a probabilistic ID search identifying a highest ranked user account data entry and link the document to a user account associated with the highest ranked user account data entry.

Abstract: In some implementations, a device may receive, from a data stream, a set of data points arranged in a dimensional data space. The device may compare the set of data points to identify one or more clusters using values of a distance parameter for data points included in the set of data points, wherein the values of distance parameter includes different values of the distance parameter for different data points. The device may transmit an indication of the one or more clusters to cause a device to display information associated with the one or more clusters. The device may receive, from the device, feedback information associated with at least one data point, wherein the feedback information indicates that at least one data point is associated with an error. The device may modify a value of the distance parameter associated with the at least one data point to a modified value.

Abstract: A data lake for enterprise security is created from an asynchronous stream of security events by deduplicating objects and creating metadata related to downstream security functions. Deduplication of objects may be efficiently performed with a bloom filter as objects are ingested into the data lake. The objects may also be augmented with metadata arranged in schemas to facilitate monitoring and use within the data lake.

Abstract: Aspects disclosed provide system and methods for providing reliability measures to outputs of large language models (LLMs). The system and methods do this by integrating Large Language Models (LLMs) in a multi-label classification setting, utilizing the Conformal Prediction (CP) framework. This approach ensures that the predictions made by the LLM are accompanied by mathematically guaranteed error bounds, enhancing the LLMs reliability and trustworthiness.

Abstract: A secret equi-join device uses as inputs a first concealed table that is concealed information of a first table having a plurality of keys and a second concealed table that is concealed information of a second table having a plurality of keys, obtains a first concealed additional table that is concealed information of a first additional table which is obtained by adding a subkey column to the first table, obtains by secure computation a second concealed additional table that is concealed information of a second additional table which is obtained by adding a subkey column further to a third table obtained by copying each record in the second table a plurality of times and adding the copied records, and obtains a concealed joined table that is concealed information of a joined table which is obtained by equi-joining the first additional table and the second additional table.

Abstract: In an embodiment, a transaction dataset is analyzed to identify a set of transaction events, each transaction event from the set of transaction events associated with a transaction event type. The set of transaction events is analyzed to identify a plurality of sets of grouped transaction events, each set of grouped transaction events from the plurality of sets of grouped transaction events associated with a subset of transaction events from the set of transaction events. To identify a plurality of sets of variants, each set of grouped transaction events from the plurality of sets of grouped transaction events including an identifier of a variant for that set of grouped transaction events and from the plurality of sets of variants is analyzed, each set of variants from the plurality of sets of variants differing from each remaining set of variants from the plurality of sets of variants.

Abstract: Embodiments of the present invention allow a Source database and a Target database to be compared, with source-only, target-only, and difference objects presented on a graphical user interface in a manner that visually shows the characterization of each displayed object and each displayed object is user-selectable via the graphical user interface to obtain information about the object and differences between the source database and the target database with respect to the object. Some exemplary embodiments are discussed herein with reference to databases such as the Standard Database (SDB) for Intergraph Smart™ Reference Data product from Intergraph Corporation and are referred to generally as the “SDB Merge Tool,” although the disclosed concepts can be applied more generally to other types of databases.

Abstract: The present invention relates to a method and apparatus for re-registering pre-registered identity information in a new identity recognition system. A method of re-registering identity feature information in an identity recognition system according to an embodiment of the present disclosure may include: identifying one or more first identity feature information calculated by the first feature calculation device and stored in a database; generating one or more latent space information by inputting the one or more first identity feature information into a specific model for latent space estimation; generating one or more second identity feature information by inputting the one or more latent space information into a second feature calculation device; and storing the one or more second identity feature information in a new database.