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: 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: 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: 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: 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.

Abstract: The present disclosure provides a technical solution of multi-modal chatting, which may provide response to user query by using multi-modal response in the interaction between chatbot and human beings, so that the expressing ways and the expressed content by the chatbot could be richer by using such response in a multi-modal way.

Abstract: Deleting web browser data by maintaining a set of Uniform Resource Locators (URL) hostnames, where a URL hostname is added to the set of hostnames responsive to the URL being accessed by a web browser and responsive to determining that predefined grouping conditions that define a logical group is met by the URL, and deleting one or more types of data maintained by the web browser in association with URLs associated with the hostnames in the set of hostnames, where the deleting is performed in accordance with a predefined deletion policy that specifies the types of data that are to be deleted and predefined deletion conditions, and where the deleting is performed responsive to determining that the predefined deletion conditions are met and determining that the web browser is not currently accessing any URL associated with the hostnames in the set of hostnames.

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: Systems and methods of processing queries for column-oriented database systems involve processing the queries to identify which of values of column data are to be accessed for the query. A select bitmap is then generated having k bits wherein each bit corresponds to one of the values of the column. The select bitmap is generated such that each bit representing a value of the column data that is to be accessed for the query has a first value and each bit representing a value of the column data that is not to be accessed for the query has a second value. Encoded values are then extracted from memory for each of the values represented in the select bitmap by a bit having the first value. The extracted encoded values are decoded to generate decoded query data. The decoded query data is then processed to generate result data.

Abstract: A computer-implemented method of managing artefact information and a computer system arranged and configured to execute the steps of the computer-implemented method are provided, wherein at least one internal sequence of artifact information is stored in an internal data store; wherein at least one external sequence of artifact information is stored in a respective external data repository, and wherein the respective internal sequence relates to the respective external sequence. The computer-implemented method includes: importing metadata relating to the respective external sequence from the respective external data repository to a data storage platform; importing the metadata relating to the respective external sequence from the data storage platform to the internal data store; and introducing a link into the respective internal sequence, wherein the link is based on the metadata and links the respective internal sequence with the respective external sequence.

Abstract: A system can maintain respective extended attributes for respective files in a file system, wherein the respective extended attributes comprise respective first-in-first-out (FIFO) queues of user identities that have been determined to have modified the respective files. The system can receive an indication to perform a delete operation on a first portion of the file system, wherein the indication is indicative of a first user identity for which files are to be preserved. The system can, in response to receiving the indication, evaluate the respective files, comprising in response to determining that the first user identity is omitted from a FIFO queue of the respective FIFO queues, delete a file of the respective files that corresponds to the FIFO queue; and in response to determining that the first user identity is identified in the FIFO queue, refrain from deleting the file.

Abstract: An embodiment for improved linking of tabular columns to column types in an ontology unseen during training. The embodiment may for a target table, encode a target tabular query column, table headers, and target types independently to generate permutation invariant representations of tabular data associated with the target table. The embodiment may, for each of the target types, extract and further encode auxiliary information. The embodiment may process the encoded tabular data to obtain a first vector and a second vector. The embodiment may concatenate the first vector and the second vector to generate a final query vector. The embodiment may process the encoded target types through a third transformer to obtain a third vector. The embodiment may calculate a score to model interactions between the target tabular query column of the target table and the target types.

Abstract: Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.

Abstract: In some implementations, there is provided a method that includes receiving a query request including a top k query operator for query plan generation, optimization, and execution, wherein k defines a threshold limit of query results for the top k query operator; inserting into a query plan a check operator associated with the top k query operator; in response to executing the query plan, checking, by the check operator, whether an early exit occurs due to the top k query operator reaching the threshold limit; in response to the early exit occurring due to the top k query operator reaching the threshold limit, stopping processing, by the check operator, including opening of another fragment of a database table; and in response to the early exit not occurring, allowing, by the check operator, the opening of the other fragment of the database table.

Abstract: Techniques are described for a computing system to synchronize project data between media applications. A method includes (a) operating a first project adapter module to convert a first media project generated by a first media application from a first project format into a generalized project format, thereby generating a generalized project; (b) operating a synchronization service to manage a set of contextual rules; (c) operating a second project adapter module to convert, with reference to the set of contextual rules, the generalized project into a second project format used by a second media application, thereby generating a second media project; and (d) viewing the second media project using the second media application. A system, apparatus, and computer program product for performing this method and similar methods are also described.

Abstract: The present disclosure discloses an image/video feature descriptor extraction method and apparatus for image/video search. An image/video feature descriptor extraction method may comprise obtaining a search requested image/video from a user, performing spatio-temporal transformation on the search requested image/video, extracting a feature map from the image/video subjected to the spatio-temporal transformation, and extracting an image/video feature descriptor by applying TNIP (Temporal Nested Invariance Pooling) to the feature map.

Abstract: Disclosed is a method for constructing a database using a video, which is performed by a computing device. The method may include acquiring the video. The method may include extracting a representation of an image with respect to each frame of the acquired video. The method may include extracting a representation of a text with respect to each frame of the acquired video. The method may include determining a primary frame among the frames of the acquired video based on the representations of the images and the representations of the texts of the frames of the acquired video. The method may include generating a database for representations associated with the determined primary frame.

Abstract: A database system enumerates one-column candidate referential integrities (1CRIs) from a plurality of input columns in one or more relations. The database system applies one or more disqualification tests to the 1CRIs to eliminate illegitimate 1CRIs resulting in a list of non-disqualified 1CRIs, wherein the disqualification tests are applied to an 1CRI being tested (hereinafter (A*,B*), A* representing a set of values of a referenced column or columns and B* representing a set of values of a referencing column or columns) until (A*,B*) is disqualified or until all of the disqualification tests have been executed and (A*,B*) has not been disqualified, in which case (A*,B*) is added to the list of non-disqualified 1CRIs, wherein each of the disqualification tests reduces the likelihood of incorrectly adding (A*,B*) to the list of non-disqualified 1CRIs.