Abstract: Document analysis systems and methods for the generation of a content-by-example log that expresses withheld documents in terms of a set of disclosed documents are disclosed. Additionally, document analysis systems and methods for the analysis of such a content-by-example log to determine withheld documents of interest without access to those withheld documents are disclosed.

Abstract: The present invention extends to methods, systems, and computer program products for data retrieval and validation for asset onboarding and deriving asset characteristics. A first set of data associated with an asset is collected. Identifiers associated with the first set of data are created. A second set of data associated with the asset is collected based on the identifiers. The first set of data set and the second set of data are compared based on the identifiers. The first set of data is validated based on the comparison. An artificial intelligence module is trained as part of a continuous training cycle in view of validation findings. Concurrently with artificial intelligence module training, one or more characteristics of the asset are derived from the first set of data.

Abstract: A multi-stage process for homomorphic end-to-end data compression and encryption is claimed. The first stage analyzes input data, applies transformations to increase compressibility and security, produces conditioned data and error streams, transforms data into a dyadic distribution, creates a transformation matrix, performs Huffman coding, and combines Huffman-encoded data with a secondary transformation stream. A second stage further processes the compressed and encrypted output, either repeating the first stage's steps or using an autoencoder for additional compression. The system supports multiple compression stages, each building on the previous one. Decompression reverses these stages while maintaining homomorphic encryption throughout. This approach enables secure data transmission, storage, and analysis in bandwidth-constrained environments, adapting to various data types and compression levels while preserving data quality and security.

Abstract: Storing compressed data objects by decompressing a first data object, identifying, differences between the first and second data objects, creating a new version of the second data object according to the differences, the first data object, and a reference object, and storing the first data object and the new version of the second data object.

Abstract: A set of computing nodes that compose a container orchestration computing cluster are identified. A set of taints that are associated with the set of computing nodes are identified, wherein each taint in the set of taints prohibits scheduling of a container group, which is defined by a container group specification that does not meet a condition defined by the taint, on a computing node associated with the taint. A first container group specification that meets the condition defined by each taint is generated, wherein the first container group specification identifies a container image. The container group, via the first container group specification, is caused to be deployed on each computing node in the set of computing nodes that has an associated taint.

Abstract: Systems, methods, and computer readable media for identifying entities as legal entities are provided. These techniques may include accessing a corpus of documents and applying a persona prediction machine learning algorithm to classify entities associated with the corpus of documents. The persona prediction machine learning algorithm may include two layers. A first layer includes applying a signature block classifier that analyzes signature blocks of the entities. A second layer includes applying an entity classifier that analyzes a plurality of documents and/or network graphs associated with the entities. An entity database is updated to indicate the output of the persona prediction machine learning algorithm based on the signature block classifier and/or the entity classifier.

Abstract: A secure transfer system for digital aircraft data includes a data producer system configured to generate a data capsule at each data production and a data consumer system. The consumer system is configured to retrieve each capsule to extract an identifier, a refresh indicator, a functional data packet, and an integrity control result. It is configured to check the integrity of the data in the capsule by establishing a new integrity check result from the identifier, the refresh indicator, and the functional data packet retrieved from the capsule and comparing the new integrity check result to the integrity check result of the capsule. The data capsule is in an integrity state when the new integrity check result matches the integrity check result retrieved from the capsule.

Abstract: A multi-cluster computing system which includes a query result caching system is presented. The multi-cluster computing system may include a data processing service and client devices communicatively coupled over a network. The data processing service may include a control layer and a data layer. The control layer may be configured to receive and process requests from the client devices and manage resources in the data layer. The data layer may be configured to include instances of clusters of computing resources for executing jobs. The data layer may include a data storage system, which further includes a remote query result cache Store. The query result cache store may include a cloud storage query result cache which stores data associated with results of previously executed requests. As such, when a cluster encounters a previously executed request, the cluster may efficiently retrieve the cached result of the request from the in-memory query result cache or the cloud storage query result cache.

Abstract: A method for assessing quality of genomic regions studied for inclusion in standardized clinical formats includes receiving data sets to be applied to a plurality of gene panels. The method also includes applying, by a processor executing instructions, standardized quality control metrics to the data sets to be applied to the plurality of gene panels; filtering, by the processor executing the instructions, each of the data sets to be applied to the plurality of gene panels to sets of variants and formatting the sets of variants in a clinical format, and outputting the sets of variants resulting from the filtering to a downstream application.

Abstract: A data storage management system is enhanced to accommodate, and moreover to optimize, the storing and retention of deduplicated secondary copies at write-once read-many (WORM) enabled storage platforms. Enhancements include without limitation: user interface (UI) options to enable WORM functionality for secondary storage, whether used for deduplicated or non-deduplicated secondary copies; enhancements to secondary copy (e.g., deduplication copy, backup) operations; and pruning changes. The storage manager is generally responsible for managing the creation, tracking, and deletion of secondary copies, with and without deduplication. Media agents that store secondary copies to and prune them from the WORM-enabled storage platforms also are enhanced for communicating and interoperating with both bucket-level and object-level WORM-enabled storage platforms to implement the features disclosed herein.

Abstract: This disclosure relates to, among other things, scalable data processing, storage, and/or management systems and methods. In various embodiments, sequence number schemes associated with ingested data records may allow for improved management of data stored in one or more layers (e.g., hot and/or cold data storage layers) using data merging, deletion, and/or compaction techniques. In certain embodiments, certain data records stored in one or more segment files associated with a partition may be merged into compacted segment files, thereby reducing storage overhead associated with storing prior records that have been updated and/or deleted records. In further embodiments, data record tombstones may be employed in connection with the management of deleted records.

Abstract: In order to provide a case search method and a case search system for providing a case of an analysis device, preprocessing, etc., associated with a sample that a user, etc., wishes to analyze, with respect to an analysis case for a presented case, a search unit 29 interprets the semantic content contained in a search string input by a user, and retrieves, based on the interpretation result, an analysis case relating to a sample which coincides with or is similar to the presented sample, out of analysis cases stored in advance in databases A, B, and outputs the retrieved case.

Abstract: Apparatuses and methods relate generally to adaptation. In an apparatus, a document processing system is programmed with document services. A network interface receives user requests for the document services. A machine learning model has nodes and edges and allows the nodes to communicate with one another. A data process node evaluates compression and decompression responsive to first states from the nodes. A processor usage node evaluates processor unit usage of the processor units responsive to second states from the nodes. A storage usage node evaluates storage usage of the data storage responsive to third states from the nodes. A memory usage node evaluates latency response of the system memory responsive to fourth states from the nodes. The machine learning model combines regression models and a distributed gradient-boosting framework to interactively process the states to analyze user requested data to reduce the latency response of the document processing system.

Abstract: A file-level snapshot access service provides direct access to individual files included in a snapshot for virtual volume of a block-storage service without requiring a volume to be re-created from the snapshot, attached to a computing device, or mounted in a file system. For example, a user/client may directly retrieve individual files from specified snapshots via a user interface/API of the file-level snapshot access service. Additionally, the file-level snapshot access service is configured to provide a listing of files included in a given snapshot. In some embodiments, a file-level snapshot access service may provide direct access to individual files included in snapshots generated for other types of storage systems, such as an object-based storage system.

Abstract: The invention relates to a method for storing data (114, 115, 116) in a data storage device (104), wherein the method comprises: receiving (202) raw data (112) or access addresses for the raw data by a data processing and search system—DPS system (102); parsing (204) the raw data by a plurality of different parsers in order to ascertain data objects each having one or more data values, and an object ID of each of the data objects, wherein one semantic concept is assigned to each of at least some of the data values; automatically importing (206) the parsing results by the DPS system; automatically storing (208) all of the parsing results in the form of redundancy-free data value lists (114, 115, 116) in the data storage device by the DPS system, wherein the redundancy-free lists comprise: one or more concept lists (116), wherein each of the concept lists represents a particular semantic concept, and a non-redundant list selectively includes those of the imported data values to which the semantic concept of

Abstract: The present disclosure relates generally to storing computer models, and more specifically to a platform for achieving replicability of a computer model (e.g., a trained machine-learning algorithm) by storing and providing access to data associated with the computer model using an immutable and decentralized ledger system (e.g., a blockchain ledger) and a distributed database. An exemplary computer-enabled method for storing a computer model, the method comprises: receiving data associated with the computer model; generating one or more asset files based on the data associated with the computer model; generating one or more hash values corresponding to the one or more asset files; generating one or more of location trackers corresponding to the one or more asset files; generating a ledger entry comprising the one or more hash values and the one or more location trackers; and adding the ledger entry to a blockchain ledger.

Abstract: A distributed database system for handling transactions from multiple client systems. A database node receives a request to execute a transaction from a first client, involving a record modification. This record has an associated check-and-set (CAS) value that changes with modifications. The record is sent to the first client, which identifies the CAS value. Similarly, a second client sends a request for another transaction, receives the record, and identifies the CAS value. One of these clients attempts to stage a mutation based on their transaction. This includes sending the previously received CAS value. The system checks for a CAS value mismatch, indicating a conflicting mutation from another transaction. If a mismatch is detected, the transaction attempt is aborted to prevent conflicts. Otherwise, the mutation is staged, and the CAS value is updated.

Abstract: Solutions for data unification include: receiving a data record, the data record comprising a plurality of data fields; selecting, from among the plurality of data fields, a subset of the data fields, the subset of the data fields being fewer in number than the plurality of data fields, wherein selecting the subset of the data fields comprises: applying a first rule to select at least a first one of the data fields within the data record for inclusion in the subset of the data fields; using content of the subset of the data fields, generating a stable identifier (stableID) for the data record; and inserting the stableID into a primary key data field of the data record.

Abstract: In certain aspects of the disclosure, a computer-implemented method includes collecting, via an artificial intelligence module, a first set of data associated with an asset and creating identifiers associated with the first set of data. The method includes collecting a second set of data associated with the asset based on the identifiers and comparing the first set of data and the second set of data based on the identifiers. The method includes determining validation of the first set of data based on the comparison and generating a result of approval or rejection based on the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for suppressing search results to personally objectionable content. One of the methods includes receiving an identifier of a resource that has image content. A first classifier classifies the image content as including objectionable content or not including objectionable content. A second classifier classifies the image content as including professionally produced content or not including professionally produced content. Whenever the image content is classified as including objectionable content and as not including professionally produced content, the resource is designated as having personally objectionable content.