Abstract: Embodiments of the present disclosure provide a data processing method and an electronic device, which relate to the computer field. The method includes: acquiring a time-series dataset, the time-series dataset comprising multiple time-series data items each comprising a time and multiple attribute parameters corresponding thereto; acquiring a target attribute parameter being at least one of the multiple attribute parameters; determining, based on a time-series model, at least one influence factor of the target attribute parameter, the at least one influence factor indicating at least one attribute parameter influencing the target attribute parameter and at least one time corresponding to the at least one attribute parameter; and outputting the at least one influence factor. As such, according to the embodiments of the present disclosure, for a target attribute parameter, at least one influence factor can be determined based on a time-series dataset and a time-series model.

Abstract: A method for dynamic execution of sub-graphs within executable graph-based models is provided. Processing circuitry obtains an executable graph-based model comprising a plurality of sub-graphs and an overlay structure comprising processing logic associated with the plurality of sub-graphs. Each sub-graph defines a hierarchical structure of related nodes. The processing circuitry receives a stimulus and a context associated with the stimulus. In response to the stimulus being received and based on the context, the processing circuitry maps the stimulus to a first sub-graph of the executable graph-based model. The processing circuitry causes execution of processing logic within the overlay structure based on the mapping. The processing logic is associated with one or more nodes of the first sub-graph.

Abstract: Partial commits of file layouts can be performed and managed. In response to a file layout request from a client device (CD), a server can communicate, to CD, first extent list data, comprising a first mapping of a group of blocks, in a data store of the server, to which CD is able to write data to the file. CD can write, and track the writing of, data to first blocks, but not second blocks, of the group of blocks. CD can generate second extent list data comprising a second mapping of the first blocks in the data store to which data is written. CD can communicate a partial commit request, comprising the second extent list data, to the server. In response to the partial commit request, the server can commit the second mapping relating to the first blocks to the data store.

Abstract: A method includes analyzing a first log of a first log type generated by a first data store and determining if the first log has a first format of the first log type. In response to determining that the first log does not have the first format of the first log type, the first data store and the first log type are identified as degraded. A first impact score is determined for the first log type. First dependency information is analyzed for the first data store. In response to determining that no data store receives data items from the first data store, a report is generated. The report includes an identification that the first data store is degraded, an identification that the first log type is degraded, and the first impact score associated with the first log type.

Abstract: Systems and methods are provided for determining contextual objects related to web content. Web content may include one or more elements, which may be extracted from the web content and analyzed to identify any contextual objects. The web content elements may be hyperlink elements, and contextual objects may be identified based on the hyperlink elements. A dominant entity may be identified for the web content, and contextual objects relating to the dominant entity may be identified. When a request for web content is received, contextual objects may be provided with the requested content. Personalized contextual objects may be selected from the identified contextual objects based on data associated with the request for web content. Selection of a contextual object may result in navigation to a browsing environment associated with the selected contextual object.

Abstract: A method for providing cross-account data distribution management is disclosed. The method includes receiving an indication of a change in an object repository of a producer account, the change including an addition of data sets into the object repository; scheduling computing resources based on the indication and a predetermined guideline; identifying, via an application programming interface, parameters that correspond to a data warehouse of a consumer account; initiating the computing resources based on the scheduling to copy the data sets from the object repository to a producer data lake; transmitting, based on the identified parameters, the data sets from the producer data lake to a consumer data lake by using a managed data lake; and persisting the data sets from the consumer data lake in the data warehouse.

Abstract: Systems, methods, and non-transitory computer readable media with instructions for methods here may be used to create and render interactive charts using large amounts of data, by efficiently dividing up the storage and processing of the data between a networked side and a local application side. In certain example embodiments, these two sides work in conjunction with one another, alternatively or additionally, in certain example embodiments, they may act independently and/or alone. The resulting charts may then be used by being embedded in external web pages.

Abstract: Hierarchical storage of files is described. An example method includes determining an input/output (IO) mode, a file size, and a file access frequency of a target file, and determining IO mode performances of the IO mode at different tiers of a storage system. The method further includes determining, based on the file size of the target file, respective storage costs when the target file is stored at the different tiers of the storage system. In addition, the method further includes determining a target tier at which the target file is stored based on the IO mode performances, the respective storage costs, the file size, and the file access frequency. In this way, it is possible to make full use of less expensive storage tiers and save the cost of the storage system, as well as to reduce the response time and improve the performance of the storage system.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at a platform, an electronic document and corresponding metadata; encoding the electronic document; sending the encoded document as a byte stream to a unit extraction service; decoding, by the unit extraction service, the byte stream into a string file; standardizing, by the unit extraction service, partition separation characters; determining, by the unit extraction service and based on the partition separation characters, a value of a first key; assigning, by the platform, a value of the corresponding metadata as a value of a second key; indexing the first key, the value of the first key, the second key, and the value of the second key in a search index; and providing a search function via an interface of the platform, wherein the search function searches the search index.

Abstract: A method utilizes a policy engine for supply chain security analysis. The method includes processing programming code, written in an imperative programming language, using a fact collector to instantiate a programming object representing a set of facts of a build system that includes an artifact. The method further includes processing the programming object using a mapper to expose the set of facts as a fact database. The method further includes evaluating a policy, written in a declarative programming language, and the fact database using a policy engine to construct a result corresponding to the artifact of the build system. The method further includes presenting the result with a supply chain security analysis of the artifact.

Abstract: An embodiment establishes a creative work database based in part on data representative of a plurality of identified creative works and authors associated with the plurality of identified creative works. The embodiment extracts a set of a first set of features from an unidentified creative work. The embodiment compares the first set of features corresponding to the unidentified creative work to a second set of features corresponding to an identified creative work to obtain a similarity score between the unidentified creative work and the identified creative work. The embodiment compares the similarity score to a threshold similarity score, and upon a determination that the similarity score meets the threshold similarity score, identifies a particular author to associate with the unidentified creative work. The embodiment authenticates the new identified creative work. The embodiment updates the creative work database to include the new identified creative work.

Abstract: Systems and methods for matching media items of a first type to media items of a second type are provided. A data store comprising first media items of a first type is accessed. A first media item of the first media items is associated with a first media item characteristic. A second media item of a second type is identified. The second media item includes a second media item characteristic. A matching first media item of the first media items that matches the second media item is determined based on the first media item characteristic and the second media item characteristic. Ranking of the second media item or the matching first media item is adjusted to reflect the correspondence between the second media item and the matching first media item. Information associated with the matching first media item is provided to a first user device based on the adjusted ranking.

Abstract: A method including automatically determining, by a machine learning model trained based at least in part on sample items stored in a sample database, a query embedding vector for a query image of a query item. The method further can include determining, based on a respective embedding distance between the query image of the query item and a respective image of each of the sample items, neighboring items from among the sample items. The respective embedding distance can be calculated based on the query embedding vector for the query image and a respective embedding vector for the respective image of each of the sample items. Each of the sample items can include the respective image and at least one respective item label. The method also can include determining a respective normalized weight for each of the neighboring items based on the respective embedding distance between the query image and the respective image of the each of the neighboring items.

Abstract: Various embodiments of the present disclosure provide multi-stage data lineage tracking techniques for automatically generating holistic and accurate data catalog for complex data ecosystems. The techniques may include generating a critical attribute collection for a data-related task based on one or more natural language descriptions for the data-related task. The techniques include receiving a data lineage map that defines a plurality of hierarchical data layers for a data ecosystem associated with the data-related task. The techniques include generating a critical attribute map for the data-related task by identifying a data element for a critical attribute at each of the plurality of hierarchical data layers of the data lineage map. The techniques include identifying noncritical attributes for the data related task generating a task attribute map for the data-related task based on the noncritical attributes and the critical attribute map.

Abstract: A method of classifying a file, including extracting metadata from the file, assigning a classification for the file by applying a machine learning model that was trained to classify files based on the metadata, determining a confidence level representing an accuracy of the classification, wherein if the confidence level is below a threshold value analyze the content of the file to assign a classification for the file based on the content; and store the assigned file classification.

Abstract: Techniques are provided for creating a “ubiquitous search index” which allows for full-text as well as value range-based search across all columns from multiple database tables, multiple user-defined unmaterialized views, and external sources. In one implementation, the data is indexed in a peculiarly constructed schema-based JSON format without duplicating data. The techniques maintain eventual consistency with the normalized source of truth database tables, and do not have a significant impact on the performance of transactional Data Manipulation Language (DML) operations.

Abstract: Systems, computer program products, and methods are described herein for dynamic visual graph structure providing multi-stream data integrity and analysis. The present disclosure is configured to provide a reactive system aimed to trace the root cause of incidents and uncover potential gaps in security of an enterprise system. Maintaining accurate and meaningful information related to incidents is the key for success of data security protocols. The integrity of message data is kept intact for improved forensic investigation, as each database may keep varying information related to a single global session.

Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) are disclosed herein to provide for the privacy-respectful learning of iconic scenes and places, wherein the learning is based on information received from one or more client devices in response to one or more collection criteria specified as part of one or more collection operations launched by a server device. In some embodiments, differential privacy techniques (such as the submission of predetermined amounts of noise-injecting, e.g., randomly-generated, data in conjunction with actual data) are employed by the client devices, such that any insights learned by the server device only relate to “hot spots,” “themes,” or other scenes, objects, and/or topics that are highly popular and captured in the digital assets (DAs) of many users, ensuring there is no way for the server device to learn or glean any insights related to particular users of individual client devices participating in the collection operations.

Abstract: An illustrative method includes a storage management system receiving, from a containerized application, a storage operation request associated with a storage volume in a storage system, the storage system including a plurality of volume instances of the storage volume that correspond to a plurality of data management models, identifying, from the plurality of volume instances, one or more particular volume instances based on the storage operation request and a data management model of each volume instance in the plurality of volume instances, and directing the storage operation request to the one or more particular volume instances to be performed on the one or more particular volume instances.

Abstract: According to some embodiments, a central cloud-based repository of data may contain consolidated facts about enterprise applications. A computer processor of a discovery engine may execute discovery in a local application process and, based on the executed discovery, automatically create a generic structured set of facts from locally accessible data. The discovery engine may then store the generic structured set of facts in the central cloud-based data repository using a standard format (e.g., JSON). The central cloud-based data repository may, for example, store facts from different application instances and/or facts from different applications. According to some embodiments, a user generated query is created in a query language (e.g., SQL) and executed on the central cloud-based repository of data to automatically create an answer. Moreover, an automated ML agent may, in some embodiments, evaluate information in the central cloud-based repository of data.