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.

Abstract: A set of transition characteristics can be identified. The set of transition characteristics can include continuities and discontinuities between data fields and data visualization channels among a plurality of data visualizations. A transition tuple for each of a plurality of pairs of the data visualizations can be determined and mapped to a matrix. The matrix can be transposed to generate vectors, each vector representing a type of transition characteristic, at least one of the vectors comprising a plurality of elements equaling a total number of the determined transition tuples. The distribution of the data fields and the data visualization channels across the data visualizations can be determined by performing statistical analysis on each of the vectors. A collection of the data visualizations can be determined based on the statistical analysis performed on each of the vectors, the collection of the data visualizations can include a subset of the data visualizations.

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: Techniques are provided herein for efficient representation of heterogeneous graphs in memory. In an embodiment, vertices and edges of the graph are segregated by type. Each property of a type of vertex or edge has values stored in a respective vector. Directed or undirected edges of a same type are stored in compressed sparse row (CSR) format. The CSR format is more or less repeated for edge traversal in either forward or reverse direction. An edge map translates edge offsets obtained from traversal in the reverse direction for use with data structures that expect edge offsets in the forward direction. Subsequent filtration and/or traversal by type or property of vertex or edge entails minimal data access and maximal data locality, thereby increasing efficient use of the graph.

Abstract: Aspects of the disclosure relate to preserving enterprise artifacts using digital twin technology and intelligent smart contracts. The computing platform may receive a stream of internal data and a stream of external data. The computing platform may compare the received internal data and the received external data to historic internal data and historic external data, respectively. The computing platform may identify inconsistencies between the received data and the historic data using a plurality of key performance indicators, and may determine a critical value for each key performance indicator. The computing platform may determine whether the key performance indicator threatens the security of the enterprise artifacts. If the computing platform determines that the key performance indicator threatens the security of the enterprise artifacts, then the computing platform may execute at least one enterprise artifact protection protocol to safeguard the enterprise artifacts.

Abstract: According to embodiments, a data stream including a plurality of time series data is received and metadata objects are extracted from the data stream. The metadata objects are associated with metrics time series (MTS) objects. The metadata objects and MTS objects are stored via separate in-memory data structures in a logical database. The in-memory data structures include information that correlates the metadata objects with the MTS objects. Any updates to the metadata objects will stay with the metadata objects and do not propagate to the MTS objects. A logical in-memory join may be performed to associate the metadata objects with the appropriate MTS object according to the in-memory data structures when a query for an MTS object is received.