Abstract: A computer-implemented method comprising: receiving, with a computer, first and second datasets; performing, with the computer, column discovery on the first and second datasets using a first trained machine-learning model to produce a column map that indexes one or more columns in the first dataset to one or more columns in the second dataset; performing, with the computer, row discovery on the first and second datasets using a second trained machine-learning model, a trained approximate nearest neighbor index, and the column discovery to produce a row map that indexes one or more rows in the first dataset to one or more rows in the second dataset; combining, with the computer, the first and second datasets using the column map and the row map to form a combined dataset; and performing one or more actions with the combined dataset.

Abstract: Technologies for storing and accessing data from persisted data objects of an object-oriented system are provided. The disclosed techniques include a system that receives, a first request to perform an operation on data of data objects, where the data objects are capable of being persisted in a database. The system generates a second request by translating the first request from a first programming language to a second programming language. The system uses an object relational mapping data structure, which maps data object attributes to database properties, to map the second request parameters to corresponding database operation parameters. The system generates one or more database requests based on the corresponding database operation parameters and causes the one or more database requests to be executed on the database. The disclosed techniques describe creating and running a RESTful microservice to persist JSON objects in a relational database.

Abstract: A computing platform may be configurable to receive a request from a video conferencing application while a video conference is in session, the request including an indication of a selection of one or more participants in a video conference session. The computing platform may also be configurable to implement a query of a database system, the query being configured to retrieve user object data, and generate a result object based, at least in part, on the retrieved one or more user data objects, the result object being configured to display information about the at least one participant. The computing platform may be configurable to provide the result object to a client device to display a graphical user interface (GUI) window including the information about the at least one participant, the GUI window comprising a user interface element to provide access to at least one function associated with a computing platform.

Abstract: An information handling system acquires data chunks for a duration of at least one time slice, determines an overwrite frequency for the duration of the time slice of each of the data chunks, clusters the data chunks according to the overwrite frequency, and determines an overwrite frequency label for each cluster of the data chunks. The system may also determine a read frequency for the duration of the time slice of each of the data chunks, cluster the data chunks based on the read frequency, and determine a read frequency label for each of the cluster of the data chunks. The system may also construct a sorted tree based on the overwrite frequency label, the read frequency label, and a virtual logical block address of each of the data chunks.

Abstract: Methods and systems for curating data by a data manager are disclosed. Data may be curated from various data sources before being provided to downstream consumers that may rely on the trustworthiness of the curated data in order to provide desired computer-implemented services. During the data curation process, data curation resources are used to improve the trustworthiness and/or value of the collected data. However, data curation resources (e.g., data curators, computing resources) may be limited and/or insufficient to perform the data curation process as desired, which may result in unusable and/or uncurated (e.g., untrustworthy) data. Thus, the data may be screened for ambiguous values. A potential replacement value for each ambiguous value may be provided to the data source and the data source may indicate whether the potential replacement value should be used in the data pipeline as a final replacement value for the ambiguous value.

Abstract: Case management systems and techniques are disclosed. In various embodiments, for each of a plurality of case nodes comprising a case model a trait definition comprising a corresponding set of traits associated with that case node is received. The respective trait definitions are used to bind each set of traits to the case node with which the set of traits is associated in case instances created based on the case model.

Abstract: A method for storing or transmitting information may include determining at least one subdivision of at least one logical hierarchical data space. The at least one logical hierarchical data space may have a plurality of subdivisions. The method may further include creating at least one data block. The method may further include writing the at least one tuple to the at least one data block. The at least one tuple may be associated with the subdivision of the at least one logical hierarchical data space. The method may further include associating the at least one data block with the at least one subdivision of the at least one logical hierarchical data space.

Abstract: Systems and methods for the quantification of sample set quality is provided. In some embodiments, a sample dataset and a sample vector set are received. A rule-based screening of the sample dataset is applied to generate a heuristic quality score. Additionally, a sample vector set is generated from the sample dataset. The difference between the sample vector set and the example vector set is calculated to generate a degree of difference quality score. The heuristic quality score and the degree of difference quality score are normalized and then combined into a quality metric. Calculating the difference between the sample vector set and the example vector set is by framing the distance as a p-value in a hypothesis test, compared against a threshold.

Abstract: Embodiments relate to a method for training an index selection agent for iteratively determining an index set I to be used when running queries against a database, the method being implemented in a computer system. Preferably, the index selection agent is based on Reinforcement Learning.

Abstract: In some embodiments, systems, methods, and apparatuses are provided herein useful for managing a plurality of concurrent and nearly concurrent data requests within a computer system. The systems have a main data storage for storing source data, and a high speed, and/or remote data storage for storing computed data. In some embodiments, a combination of data filters and distributed mutex processes are used to eliminate or limit duplicate reads and writes into the high speed data storage units by ensuring only a single service module gets a lock to do the read and update of the cache; and makes it possible for keys to expire and be removed from the data filter. The systems and methods herein have various applications including retail sales environments where the requested data is related to product sales, product availability and the like.

Abstract: A method for processing commodity information includes: obtaining commodity information of a commodity, in which the commodity information includes a target commodity configuration and a configuration value; obtaining a composite structure of matching conditions associated with the commodity, in which the composite structure is a tree structure of matching conditions with respect to commodity configurations, non-leaf nodes of the tree structure are in an AND-OR relationship, leaf nodes of the tree structure store Boolean expressions, each Boolean expression includes a commodity configuration, a matching value and a matching operator; obtaining a target expression having an AND-OR relationship by traversing the matching conditions in the composite structure; and obtaining a matching result by performing a matching process based on the target expression, the target commodity configuration and the configuration value of the commodity.

Abstract: Systems, methods, and computer-readable media are disclosed herein that generate a ternary tree data structure that includes multiple categories (e.g., terminologies) using dynamic array modifications that facilitate sharing of one or more nodes across categories. A plurality of different categories may be added and stored within a single ternary tree data structure such that each categories may be separately queried using the single ternary data structure.

Abstract: Systems and methods for recommendation of cohort sample sets is provided. In some embodiments, a set of dataset requirements is received as a required vector set. The historical vector sets are queried. Each vector set corresponds to a known dataset. The difference between the required vector set and each of the historical vector sets is calculated by framing the distance as a p-value in a hypothesis test, compared against a threshold. The historical vector set with the least difference to the required vector set is identified. The least difference is calculated as a count of differing classes or as a numerically weighted summation of differing classes.

Abstract: An encoding method for a key Trie includes generating a plurality of meta data by applying encoding to a portion of non-leaf nodes of the key Trie, and storing an encoding result of the key Trie into a storage device, wherein the encoding result includes the plurality of meta data corresponding to the portion of non-leaf nodes, respectively.

Abstract: A computer-implemented method of context-based constraint modification is disclosed. The method comprises receiving a data sharing request in a distributed database system to share a data model between databases. The method further comprises adjusting a data sharing constraint applicable to the data sharing request based on data related to previous data sharing processes, the data sharing constraint being related to data transmission or validation, access control, or conflict resolution. The method additional comprises determining that the data sharing request requires data merging; reading a data file containing a shareable version of at least a portion of the data model subject to the data sharing constraint; and merging the shareable version with a current data model for a database of the databases.

Abstract: A method of implementing a graphical user interface to collect information from a user is provided. The method includes (i) dynamically displaying, by the graphical user interface, K>1 groupings of M>1 documents from a catalog of documents in an embedding space, wherein a distance between each pair of the documents in the embedding space corresponds to a predetermined measure of dissimilarity between the pair of documents, and the K groupings are formed using K-medoid clustering analysis, (ii) receiving a user selection of one grouping of the K groupings, (iii) dynamically displaying a predetermined number P>0 documents of the cluster which corresponds to the selected grouping, (iv) receiving user feedback with respect to one of the Pk documents of the selected grouping, (v) and dynamically displaying an identified subsequent document from the selected grouping in dependence on the set of liked documents and the set of disliked documents.

Abstract: A test query of a database is performed in response to determining that a performance associated with a user database query of the database does not satisfy a first performance threshold. In response to a determination that the performance of the test query satisfies a second performance threshold, a database buffer cache of the database is resized. Resizing the database buffer cache includes: determining a metric based at least in part on a storage size of the database and an index size of the database, and resizing the database buffer cache of the database based on the metric and a size of the database buffer cache.

Abstract: One embodiment provides a method for identifying similar objects by performing document attribute comparisons, the method including: receiving a reference document, wherein the reference document corresponds to an object and comprises a plurality of attributes of the object; receiving a request for a similarity comparison, wherein the request provides an indication of similarity attributes to be used in the similarity comparison; comparing the reference document to each of a plurality of documents corresponding to other objects; generating a document similarity score for each of the plurality of documents, wherein the document similarity score is generated based upon an aggregation of similarity attribute scores calculated for each of the similarity attributes; and providing at least one of the plurality of documents with an indication of a similarity. Other aspects are described and claimed.

Abstract: Methods and systems for data management include representing, organizing, and accessing very large data sets. Embodiments describe supporting data sets of various size based on attributed data slices (ADSs) to enable reduced memory requirements, query decomposition and parallel execution, and constant execution times for concurrent queries. The ADSs can include data buckets comprising items that are grouped by an attribute key. Attribute groups can be further sorted (e.g., in ascending order) based on the attribute key. According to some embodiments, the essential structure of an ADS provides additional functionality while preserving the behavior expected of an ADS through the use of an Extension Block containing attribute location data.

Abstract: Some disclosed embodiments are directed to methods and systems for performing pair-wise delta compression. For example, systems obtain a set of files to be compressed into a single compressed file. The system identifies different attributes related to the set of files. For each file in the set of files, the system predicts an optimized set of candidate compression files and calculates a delta between each file in the optimized set and the target file corresponding to the optimized set. After identifying the smallest delta, the system compresses the selected pair of files associated with the smallest delta in order to generate the single compressed file for the set of files.