Abstract: Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value.

Abstract: A system and method for distributed node-based data compaction. The system uses machine learning on data chunks to generate codebooks which compact the data to be stored, processed, or sent with a smaller data profile than uncompacted data. The system uses a data compaction in an existing blockchain fork or implemented in a new blockchain protocol from which nodes that wish to or need to use the blockchain can do so with a reduced storage requirement. The system uses network data compaction across all nodes to increase the speed of and decrease the size of a blockchain's data packets. The system uses data compaction firmware to increase the efficiency at which mining rigs can computationally validate new blocks on the blockchain. The system can be implemented using any combination of the three data compaction services to meet the needs of the desired blockchain technology.

Abstract: A method, apparatus, non-transitory computer readable medium, and system for media processing include obtaining a text prompt describing content, generating, using a multi-modal encoder, a text embedding based on the text prompt, and obtaining an image depicting the content based on the text embedding. The multi-modal encoder is trained to encode image descriptions based on a similarity between a caption of a training image and a paraphrase of the caption.

Abstract: A pipeline performs automated generation of database queries for a database and corresponding questions comprising natural language text. The pipeline generates database query templates based at least partly on a schema of the database and populates the query templates based on values identified from the records sampled from the database to generate valid database queries. The pipeline then generates abstract representations of each of the generated database queries and, for each abstracted database query, prompts a language model to generate a corresponding question in natural language. The pipeline prompts another language model to evaluate similarity of each abstracted database query and corresponding natural language question. The natural language questions and database queries associated with the corresponding abstractions that are sufficiently similar are provided for use.

Abstract: A computer-implemented method of registering digital assets (DA) for lifecycle events, notarizations, responses, including: receiving data for the DA (parties identification (PA), asset type metadata); receiving transaction to create DA with data; obtaining asset type template (ATT) determining availability, if available: generating DA record (DAR) and contents from ATT; obtaining notary recipe (NR) template (NRT) for contents; determining if the NRT available and if not creating an NR; or generating/assigning NR to data of DAR; and if available, proceeding, to creating DAR, data specification and assigning to DAR; or obtaining/creating/assigning, NRT for data specification; and assigning PA for digital signatures and double notary criteria to NR; granting signature authority (SA) for DAR to system asset proxy account (SAPA); assigning the SA to DAR; storing DAR; assembling, assigning DA nonfungible token (NFT) data record (DR), to NFT blockchain; verifying SAPA for SA for DA; creating event transaction for S

Abstract: Embodiments of this application disclose a video content retrieval method performed by a computer device. The method includes: obtaining a query text; performing feature extraction processing on the query text through a video content retrieval model, to obtain a plurality of text content features at different feature granularities; calculating, based on the text content feature of each feature granularity, a similarity corresponding to the query and a candidate video content retrieval result at the corresponding feature granularity; and determining, based on the similarities at different feature granularities, a video content retrieval result corresponding to the query text. The solution may improve model training for the content retrieval model and improve content retrieval precision of the content retrieval model.

Abstract: According to various embodiments, techniques for providing a subsurface master record for a subsurface data record are presented. The techniques include: determining at least one subsurface data record for mastering; obtaining a respective subsurface master record that matches the at least one subsurface data record; and merging the at least one subsurface data record with the respective subsurface master record. The techniques may also include updating each subsurface data record of the at least one subsurface data record with an indication of a relationship between the each subsurface data record and the respective subsurface master record.

Abstract: Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

Abstract: A process management method and a related electronic device are provided. According to the method, process data in a volatile memory can be migrated to a non-volatile memory in real time in a running process of a system. When the system is asleep, data in a memory does not need to be packaged and backed up. When the system is woken up or restarted, data does not need to be parsed and reconstructed, to implement quick sleeping and waking up of the system. In addition, even if the system is restarted due to an unexpected power failure, a loss of key data in the memory can be avoided, and a speed of waking up or restarting the system can also be improved.

Abstract: A facility is described for automatically selecting document properties to be included in an index on a corpus of documents. In some cases, the facility performs this automatic selection by subjecting the documents of the corpus to an inference model. In some cases, the facility performs this automatic selection by submitting to a large language model a prompt automatically constructed to include, for each of one or more example documents, (1) the example document's contents, and (2) a list of properties of the sample document that should be indexed.

Abstract: A system and method generate a dynamic and query adaptive Bloom filter for optimal joining of tables such as large tables in distributed data processing systems. A Bloom filter is dynamically constructed and tuned based on historical query patterns including frequency and selectivity. Metrics are collected from execution of an Adaptive Query Execution (AQE) based execution plan and execution of a Bloom filter-based execution plan generated from the constructed and tuned Bloom filter. A score measuring performance of the execution plans is generated from the metrics of each of the execution plans. The execution plan with a greater score is selected to optimally join the tables. The method implements the system.

Abstract: A system can, based on a retrieval-augmented generation (RAG) process ingesting data, query a search system to identify at least one first portion of the data that has at least one third generation identifier that is greater than second generation identifiers in a checkpoint; create second chunks from the at least one first portion of the data; in response to second chunks being duplicates of first chunks, based on hash values, store first identifiers of the second chunks; remove the stored chunk identifiers from second identifiers of chunks that correspond to chunks that existed in a RAG system prior to the ingesting, to produce stale chunk identifiers; remove, from the RAG system, third chunks that are identified by the stale chunk identifiers, and, in response to the second chunks being determined to be unique relative to the first chunks, store the second chunks in the RAG system.

Abstract: Methods, systems, and devices for data management are described. A first application in a destination computing environment of a data management system (DMS) may determine that a bulk-push criterion is satisfied for a second application in a source computing environment of the DMS. The first application may transmit, to an asynchronous metadata service, a request indicating the second application for which the bulk-push criterion is satisfied. The request may be configured to cause the asynchronous metadata service to query a database in the source computing environment, identify a latest version of one or more rows that include metadata associated with the second application, and generate data records indicating the latest version of the one or more rows that include the metadata associated with the second application. The first application may receive the data records via an asynchronous data stream between the first application and the second application.

Abstract: According to some embodiments, systems and methods are provided including a memory storing processor-executable code; and a processing unit to execute the processor-executable program code to cause the system to: receive a request for a sequence, the sequence including two or more components; identify one or more possible sequences based on the request; build a sequence based on the identified one or more possible sequences, wherein building the sequence includes adding an extension to the sequence; validate the built sequence; and store the validated sequence. Numerous other aspects are provided.

Abstract: A method of detecting anomalies in data, includes receiving a dataset with a plurality of multidimensional data points (MDDPs) wherein a portion of the plurality of MDDPs are labeled and wherein other MDDPs of the plurality of MDDPs are unlabeled; based on a neighborhood size k of the plurality of MDDPs, computing a neighborhood radius ox for each MDDP in a reference dataset computed for the plurality of MDDPs; and generating a locally adaptive similarity (LAS) kernel of a newly arrived MDDP (NAMDDP) based on the neighborhood radius ox. The method additionally includes applying a random walk model to the LAS kernel to determine a probability of the NAMDDP being an anomaly; and if the NAMDDP is an anomaly, outputting data associated with an alarm or notification responsive to the detection of the anomaly.

Abstract: A technique of managing space-accounting updates includes receiving a set of updates to space-accounting metadata of a specified volume, performing a lookup for the specified volume in a volume table that maps volumes to respective delta records, the lookup identifying a delta record that stores a set of space-accounting changes for the specified volume, and writing to the delta record to account for the set of updates.

Abstract: A computer-implemented method for generating a summary of a graph database comprising a set of RDF tuples including obtaining the graph database and generating a summary having a set of probabilistic filters. Each probabilistic filter of the set determines if at least one RDF tuple existing in the graph database corresponds to a respective basic graph pattern of the probabilistic filter with a possibility of false positive.

Abstract: Examples provide record retention to content items in a content management system. The system identifies a content item stored in a content items database and displays a user interface (UI) that includes a list for a categorization criterion. User input is received from the UI indicating a user selection for the first categorization criterion. A retention mapping schedule maps the criterion options to retention labels of a retention schedule. A retention label for the content item is determined based on the first user selection and the retention mapping schedule, the retention label being defined in the retention schedule and having an expiration duration defining how long content items marked with the retention label are retained. The retention label is stored as metadata for the content item, and the content item is deleted after an expiration duration of the content item has elapsed.

Abstract: A mechanism is described for facilitating misuse index for explainable artificial intelligence in computing environments, according to one embodiment. A method of embodiments, as described herein, includes mapping training data with inference uses in a machine learning environment, where the training data is used for training a machine learning model. The method may further include detecting, based on one or more policy/parameter thresholds, one or more discrepancies between the training data and the inference uses, classifying the one or more discrepancies as one or more misuses, and creating a misuse index listing the one or more misuses.

Abstract: Synchronizing loosely coupled systems where a source system determines a source evaluation of a validation function based on a data record sent to a target system and the source system receives from the target system a target evaluation of the validation function based on the data record. The source system compares the source evaluation to the target evaluation and, in response to a mismatch, the source system executes a predefined action for synchronizing the data record at the target system with the data record at the source system. The predefined action may comprise the source system resending the data record to the target system.