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.

Abstract: A computer-implemented system includes identifying a target hierarchical taxonomy comprising a plurality of distinct hierarchical taxonomy categories; extracting a plurality of distinct taxonomy tokens from the plurality of distinct hierarchical taxonomy categories; computing a taxonomy vector corpus based on the plurality of distinct taxonomy tokens; computing a plurality of distinct taxonomy clusters based on an input of the taxonomy vector corpus; constructing a hierarchical taxonomy classifier based on the plurality of distinct taxonomy clusters; converting a volume of unlabeled structured datasets to a plurality of distinct corpora of taxonomy-labeled structured datasets based on the hierarchical taxonomy classifier; and outputting at least one corpus of taxonomy-labeled structured datasets of the plurality of distinct corpora of taxonomy-labeled structured datasets based on an input of a data classification query.

Abstract: A method includes obtaining matches between target records in a target dataset and a reference records in a reference dataset, each match of the matches comprising a corresponding confidence level of the match, categorizing the target records into review level categories according to the corresponding confidence level, and presenting a graphical user interface (GUI). The GUI includes a first section for a first review level category showing a first subset of the target records assigned to the first review level category, the first subset comprising target records related, in the GUI, to at least one matching reference record. The GUI includes a second section for a second review level category, wherein the second section shows a second subset of the target records assigned to the second review level category, the second subset comprising target records related, in the GUI, to at least one matching reference record.

Abstract: Retrieval of relevant vectors produced by representation learning can critically influence the efficiency in Natural Language Processing (NLP) tasks. Presented herein are systems and methods for searching vectors via a typical nonmetric matching function: inner product. Embodiments, which construct an approximate Inner Product Delaunay Graph (IPDG) for top-1 Maximum Inner Product Search (MIPS), transform retrieving the most suitable latent vectors into a graph search problem with great benefits of efficiency. Experiments on data representations learned for different machine learning tasks verify the outperforming effectiveness and efficiency of IPDG embodiments.

Abstract: Methods and systems described herein may include processing a change data capture stream in parallel and optimizing the write operations contained in the change data capture stream such that the write operations may be written to a change table in parallel. Processing the change data capture stream may include decoding the transaction data contained in the change data capture stream in parallel. After the transaction data in the change data capture stream has been decoded, the transaction data may be analyzed to identify write operations that write to the same row. Write operations that write to the same row may be merged into a single write operation. The merging of write operations may be performed until each write operation writes to a different row. The write operations may then be written to the change table in parallel.

Abstract: Described are systems, methods, and techniques for collecting, analyzing, processing, and storing time series data and for evaluating and dynamically estimating a resolution of one or more streams of data points and updating an output resolution. Responsive to receiving a stream of data points, a data resolution can be derived and an output resolution can be set to a first value. When a change to the data resolution is detected, the output resolution can be changed, modifying a frequency at which output data points are generated and/or transmitted. In some instances, a detector can be implemented to trigger an alert responsive to ingested data points corresponding with triggering parameters. An output resolution for the detector can be dynamically modified based on dynamically detecting a change to the data resolution of the stream of data.

Abstract: There are provided methods and devices for use with industrial control systems. For example, there is provided a method that can include acquiring data from a sensor associated with an industrial machine. The method can include determining, while acquiring the data, whether at least one condition is satisfied in the data. Furthermore, the method can include logging the data as a function of time and logging information associated with the at least one condition as a function of time, in response to the at least one condition being satisfied. The method can also querying the logged information, subsequent to logging the data, to identify subsets of the data for which the at least one condition is satisfied.

Abstract: A data processing method, platform, and an electronic device are disclosed. The method includes: extracting original data into a message engine based on a preset standardized data interface, the original data including terminal data and system data generated by an application system. The method further includes: reading the original data from the message engine; storing the original data in a distributed file system to form a fact table; storing the fact table in a columnar database; obtaining target column data required for generating a target chart from the columnar database; and generating the target chart according to the target column data.

Abstract: A computer-implemented method, computer system, and computer program product for managing a database are disclosed. Features thereof include selecting data lines for analytics, each data line including original data, and adding, to each of the selected data lines, a set of additional bytes to represent metadata about a corresponding one of the data lines. The features further include receiving a request to receive a first data line, and reading a first set of additional bytes corresponding to the first data line.

Abstract: Apparatus and associated methods relate to mitigating data-stream dropout in a serial data-stream. A time-sequence of messages of the serial data-stream is received, each containing a data packet communicating an action. Validity of each of the time-sequence of messages received is determined. After receiving each valid message, a plurality of future actions is created based at least in part on the valid message received. The plurality of future actions corresponds to a plurality of future data packets of the time-sequence of messages. After receiving each valid message, the action communicated in the valid message received is performed. After receiving each invalid messages, a next one of the set of sequential future actions created is instead used in place of any action communicated in the data packet of the invalid message received.

Abstract: Systems and methods described herein enable effective and accurate modeling of a set of existing data profiles, perform categorization of the data profiles in an explainable way such that actions can be taken on the information to have predictable results. The systems and methods further facilitate means to categorize small text components, trained over dependent and independent model sets, to enable a cleaner and more explicit representation of information rich short-strings, in order to facilitate a more meaningful representation of the data profiles.

Abstract: Data content governance for presentation layer synchronization for a version controlled underlying data model includes defining a data model for underlying data in a database, specifying a presentation layer for the defined data model and identifying selected elements of the data model necessary to meet data requirements of the specified presentation layer. Then, the identified selected elements of the data model are serialized and both the specified presentation layer and the serialized elements are versioned in respect to the specified presentation layer. Thereafter, when the data model becomes modified, the specified presentation layer is modified to accommodate the modified data model. In response to the modification, a different selection of elements of the data model necessary to meet data requirements of the modified presentation layer are re-identified and serialized, with the modified presentation layer and the serialized re-identified different selection of elements becoming re-versioned.

Abstract: A computer-implemented method reduces the number of character set conversions in a distributed data virtualization system. The method includes receiving, from a first application, a first request for a set of data, including a requested codepage, stored in a first data source of a plurality of data sources. The method includes obtaining, by a connector, from the first data source, a first codepage associated with the first data source, which identifies a character set associated with the set of data. The method also includes adding a virtual coded character set identifier (VCCSID) in a first catalog entry of a catalog, wherein the first VCCSID is added to a nickname column of the catalog. The method includes obtaining and sending the set of data to the data application while allowing maximum of one codepage conversion.

Abstract: A system includes reception of a request to display a first dashboard, transmission of a request for a first dashboard data file associated with the first dashboard from a server system, reception of the first dashboard data file associated with the first dashboard from the server system, issuance a first plurality of queries of the first dashboard data file to the server system, reception of result sets in response to the first plurality of queries, building of results based on the result sets and the model data, rendering of one or more data visualizations based on the results, and presentation of the one or more data visualizations on the display.

Abstract: Example embodiments relate generally to systems and methods for continuous data protection (CDP) and more specifically to an input and output (I/O) filtering framework and log management system to seek a near-zero recovery point objective (RPO).

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.