Abstract: Provided is a data labeling method based on artificial intelligence, an apparatus, and a storage medium relating to the field of artificial intelligence, particularly data labeling, image recognition, and natural language processing. The method includes: determining a plurality of samples involved in clustering; performing a plurality of following operations circularly to realize iterative processing, until a convergence condition is satisfied or a quantity of iterations reaches a number threshold, comprising: pre-clustering the plurality of samples according to a vector representation of the respective samples to obtain a plurality of class clusters, each class cluster containing at least one sample; receiving labeling information for the respective class clusters and re-determining the plurality of samples according to the labeling information; and determining a clustering result according to the labeling information for the respective class clusters.

Abstract: Systems and methods are provided for identifying subscribers and/or content creators to each other while attending a real-world/live event. The real-world/live event may be in furtherance of content creation or in furtherance of providing preferential access to subscribers. Identification in the case of subscribers can be based upon subscribership information, commonality of one or more aspects of the subscribers and/or the content creators. For example, a subscriber may be identified with a level of prominence commensurate with the level at which he/she subscribers to a content creator to. Notifications and/or recommendations may be presented in an augmented reality experience along with augmented reality identifications of subscribers and/or content creators.

Abstract: Techniques are provided for optimizing workload performance by automatically discovering and implementing performance optimizations for in-memory units (IMUs). A system maintains a set of IMUs for processing database operations in a database. The system obtains a database workload information for the database system and filters the database workload information to identify database operations in the database workload information that may benefit from performance optimizations. The system analyzes the database operations to identify a set of performance optimizations and ranks the performance optimizations based on their potential benefit. The system selects a subset of the performance optimizations, based on their ranking, and generates new versions of IMUs that reflect the performance optimizations. The system performs verification tests on the new versions of IMUs and analyzes the tests to determine whether the new versions of IMUs yield expected performance benefits.

Abstract: Example methods and systems for providing notifications of unread messages is provided. A client device detects an input action proximate to a folder created by a recipient user account. The folder includes one or more online chats. The one or more online chats includes at least one unread message. The client device provides a notification relating to the at least one unread message in the one or more online chats in the folder. The notification includes at least one online chat identity that correspond to at least one online chat of the one or more online chats including the at least one unread message. The client device receives a selection of a first online chat identity that corresponds to a first online chat within the folder. Based on the selection of the first online chat identity, the client device provides access to corresponding unread messages in the first online chat.

Abstract: This disclosure describes a natural language question (NLQ) query service within a service provider network that provides row level security (RLS) for autocomplete during entry of NLQs and fuzzy matching in NLQ answering. The rules take the form of per-user predicates such as Tim can only see rows with region=US. In configurations a complex extraction and preprocessing pipeline to extract distinct combinations of values against RLS predicate “rule keys” is used. Those distinct values are indexed along with grouped rule keys to enable pushing down predicates at auto-complete time. This enables pushing part of RLS rule handling to ingestion time of a dataset rather than handling all RLS rule handling at query time, enabling meeting of latency goals. In configurations, a single logical document of unique cell values is split into multiple documents with a subset of rule keys to handle scalability limits.

Abstract: A computer measures for each column in many rows, a respective frequency of statements that filter the column in a workload of database statements, a respective count of distinct values used for filtration on the column in each statement individually, a respective frequency of each of the counts of distinct values used for filtration on the column across all of the database statements, and a respective value range of the column for each of many storage zones. A respective efficiency is measured for each of many distinct interleaved sorts. Each interleaved sort uses a respective distinct subset of the columns. Each interleaved sort is based on portions of each of the values for each row in a sampled subset of rows in each column of the subset of the columns of the interleaved sort. Efficiency measurement is based on frequencies of statements, value ranges of columns for each storage zone, and frequencies of counts of distinct values.

Abstract: In some embodiments, a method receives a label for a record in a database. A first operation is performed using a first value associated with the record to generate a first reporting object for a sustainability metric that is based on a resource. A second value for the first reporting object is generated based on performing the first operation using respective first values associated with first records based on a relationship in a data model to a first reporting object. The method uses the label to perform a second operation using the first value associated with the record to generate a third value for a second reporting object for the sustainability metric. The second reporting object is generated based on performing the second operation using respective first values associated with second records that are associated with the label.

Abstract: Computer-implemented techniques for entity disambiguation using graph neural networks (GNNs) are provided. According to an embodiment, computer implemented method can comprise receiving, by a system operatively coupled to a processor, an unstructured text snippet comprising an unknown term. The method further comprises employing, by the system, a heterogeneous GNN trained on a knowledge graph associated with a domain of the unstructured text snippet to facilitate identifying one or more similar terms included within the knowledge graph for the unknown term.

Abstract: A system includes a plurality of computing units. A first computing unit of the plurality of computing units comprises: a communication interface configured to receive an indication to roll up data in a data table; and a processor coupled to the communication interface and configured to: build a preaggregation hash table based at least in part on a set of columns and the data table by aggregating input rows of the data table; for each preaggregated hash table entry of the preaggregated hash table: provide the preaggregated hash table entry to a second computing unit of the plurality of computing units based at least in part on a distribution hash value; receive a set of received entries from computing units of the plurality of computing units; and build an aggregation hash table based at least in part on the set of received entries by aggregating the set of received entries.

Abstract: For a given file type, an optimal number of threads to use to copy files of each of a number of different discrete file sizes is determined, using a temporal difference learning, reinforcement learning approach in which file copy time is used as feedback reward reinforcement. A continuous function corresponding to the given file type and outputting the number of threads to use to copy files having this given file type and that are of any input file size is fitted onto the optimal numbers of threads determined for the discrete file sizes.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an overall assessment of a combined inventory item and structure similarity to an initial inventory item and structure. A plurality of inventory items, stored in a database, maybe retrieved to generate a score value corresponding to each of the plurality of inventory items based on a plurality of facets describing the inventory item. Based on the generated score value, a subset of the plurality of inventory items may be determined based on data points representing the subset of the plurality of inventory items that are within a preconfigured Euclidean distance from a centroid representing a data point corresponding to the initial inventory item. One or more structures corresponding to the subset of the plurality of inventory items may be dynamically generated, and their combinations are scored for finding an alternate inventory item and structure.

Abstract: An electronic device obtains a plurality of media items, including, for each media item in the plurality, a set of attributes of the media item. The device provides the set of attributes for each media item of the plurality of media items to a machine learning model that is trained to determine a pairwise similarity between respective media items in the plurality of media items and generates an acyclic graph of an output of the machine learning model that is trained to determine pairwise similarity distances between respective media items in the plurality of media items. The device clusters nodes of the acyclic graph, each node corresponding to a media item. Based on the clustering, the electronic device modifies metadata associated with a first media item in a first cluster and displays a representation of the first media item in a user interface according to the modified metadata.

Abstract: A method includes: receiving, from a client device, a data request containing a structured document; generating a set of numerical vectors representing the structured document; providing the set of numerical vectors to an auxiliary controller for generation of a predicted attribute of response data providing the search request to a primary response generator for generation of the response data; determining, at the auxiliary controller, whether the predicted attribute satisfies a modification criterion; and when the determination is affirmative, transmitting a modification command to the primary response generator to truncate the generation of the response data.

Abstract: A method of valuating a plurality of digital content items including: receiving the plurality of digital content items; for each received content item: establishing a plurality of attributes from content and characteristics of the content item; establishing a lifetime indicating a span of consumers interest in the content item; producing a valuation function for calculating a market value of the content item during its lifetime by finding and ranking nearest one or more previously processed content items having the plurality of attributes with closest similarity to the plurality of attributes of the received content item, performing weighted averaging of the valuation functions produced for the nearest one or more of the previously processed content items; and adapting, using “edge cutting” adaptation, the produced valuation function to a market response reflecting behavior of the consumers in response to the market values of the content item calculated by the valuation function.

Abstract: The present disclosure describes a monitoring environment that monitors an activity for activity that may be indicative of being prohibited by the local, the state, and/or the national governing authorities, namely suspicious activity, or activity that is prohibited by the local, the state, and/or the national governing authorities, namely prohibited activity. The monitoring environment verifies the activity is actually being monitored within the monitoring environment. The verification can require one or more monitoring persons monitoring the activity to perform one or more tasks to verify their attentiveness in monitoring the activity.

Abstract: Methods, systems, and devices for wireless communications are described. The method includes receiving a configuration message indicating a group common control resource allocated to a set of UEs that includes the UE, identifying a hashing function assigned to the UE for detecting control messaging communicated via the group common control resource that is addressed to the UE, receiving, via the group common control resource, a control message indicating addressing data and a bitmap, and processing the addressing data using the hashing function and the bitmap to determine applicability of the control message to the UE.

Abstract: Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Abstract: Provided in this disclosure is a method of organizing data from an unordered, unclustered dataset including data points having attributes. The data points are sorted into neighborhoods each having categories based on the attributes. Similarity clusters are created based on a user-selected similarity cluster scope. The clusters are arranged into a similarity tree organized dataset where the clusters are grouped into a hierarchy of similarity levels. New data points are inserted by determining similarity of their attributes to data points in grouped clusters at the highest levels of the hierarchy, and then comparing to data points in grouped clusters at progressively lower levels until a suitable cluster is determined, whereupon the new data point is then inserted. In this manner, only a selected portion of data points are compared, representing an improvement over previous methods that require comparisons to all the data points in a dataset.

Abstract: A records retention cloud application service and automated document importing and tagging system and the automated document importing and tagging processes for records retention are disclosed. The automation of the file importing and tagging enables faster centralization and management of large numbers of records.

Abstract: Systems, methods, and software to manage tags in association with vertices of a graph. In one implementation, a graph management system identifies a request to tag vertices in the graph, wherein the request indicates one or more attributes to qualify for the tag as part of a conditional expression. The graph management system further identifies vertices in the graph with the one or more attributes. Once identified, the graph management system assigns the tag to the vertices wherein the tag comprises an attribute assigned to the identified vertices.

Abstract: Systems, methods and products for classifying images according to a visual concept where, in one embodiment, a system includes an object detector and a visual concept classifier, the object detector being configured to detect objects depicted in an image and generate a corresponding object data set identifying the objects and containing information associated with each of the objects, the visual concept classifier being configured to examine the object data set generated by the object detector, detect combinations of the information in the object data set that are high-precision indicators of the designated visual concept being contained in the image, generate a classification for the object data set with respect to the designated visual concept, and associate the classification with the image, wherein the classification identifies the image as either containing the designated visual concept or not containing the designated visual concept.

Abstract: A process of anonymizing a person captured in an image. An anonymization server receives a request from an agency to anonymize a person captured in an image including an unredacted facial feature corresponding to the person and an unredacted non-facial feature. The server redacts the facial feature captured in the image to generate a first redacted image. The server then identifies a second image accessible to users not associated with the agency. When the server determines that the anonymity of the person captured in the first redacted image can be compromised using unredacted facial and non-facial features captured in the second image, the server further redacts the non-facial feature captured in the image.

Abstract: Disclosed herein is a system, comprising a distributed database comprising a plurality of partitions allocated in memory for storing a plurality of datasets. Wherein each dataset stored in the distributed database comprises at least a primary data portion stored in a respective primary partition of the plurality of partitions and at least zero additional data portions stored in respective secondary partitions of the plurality of partitions. Wherein each data portion of each dataset is mapped to a respective partition in which it is stored by a respective identifier. Wherein the primary data portion of each dataset comprises metadata stored in the primary partition, the metadata is indicative of the identifier of all additional data partitions of the respective dataset.

Abstract: In one aspect, hierarchical image segmentation is applied to an image formed of a plurality of pixels, by classifying the pixels according to a hierarchical classification scheme, in which at least some of those pixels are classified by a parent level classifier in relation to a set of parent classes, each of which is associated with a subset of child classes, and each of those pixels is also classified by at least one child level classifier in relation to one of the subsets of child classes, wherein each of the parent classes corresponds to a category of visible structure, and each of the subset of child classes associated with it corresponds to a different type of visible structure within that category.

Abstract: Methods and systems are provided for automatic classification of information in an adversarial machine learning setting. For example, a learner that includes multiple classifiers may perform data classification automatically. Each classifier may be trained with adversarial data of a different strength. For a given query to be classified, the learner is configured to intelligently select a classifier that is commensurate with the adversarial strength of the data inside the query, without explicit knowledge of that data or its adversarial strength.

Abstract: An initial Network on Chip (NoC) topology based on a set of initial requirements is incrementally modified to satisfy a set of different requirements. Each incremental modification includes minimizing a number of changes to existing components in the initial topology. Minimizing the changes includes preserving names of the existing components in the initial NoC topology.

Abstract: A resource host transmits a payload to a client device. The payload includes a first asset hosted by the resource host, and the first asset is associated with a first reference tag indicating a versioning status of the first asset. The resource host receives an Add Ref Instruction, wherein the Add Ref Instruction, which includes a custom reference tag indicating a user-selected versioning status of the first asset. The resource host associates a second reference tag with the first asset based on the custom reference tag.

Abstract: A system for allocation of one or more data structures used in a program across a number of processing units takes into account a memory access pattern of the data structure, and the amount of total memory available for duplication across the several processing units. Using these parameters duplication factors are determined for the one or more data structures such that the cost of remote communication is minimized when the data structures are duplicated according to the respective duplication factors while allowing parallel execution of the program.

Abstract: A computer measures for each column in many rows, a respective frequency of statements that filter the column in a workload of database statements, a respective count of distinct values used for filtration on the column in each statement individually, a respective frequency of each of the counts of distinct values used for filtration on the column across all of the database statements, and a respective value range of the column for each of many storage zones. A respective efficiency is measured for each of many distinct interleaved sorts. Each interleaved sort uses a respective distinct subset of the columns. Each interleaved sort is based on portions of each of the values for each row in a sampled subset of rows in each column of the subset of the columns of the interleaved sort. Efficiency measurement is based on frequencies of statements, value ranges of columns for each storage zone, and frequencies of counts of distinct values.

Abstract: A top K query directed at a table is received. The table is organized into multiple storage units. The top K query comprises a first clause to sort a result set in order and a second clause that specifies a limit on a number of results provided in response to the query. A table scan operator identifies a first set of rows from the table based on a scan set determined for the table and provides the first set of rows to a top K operator. The top K operator determines a current boundary based on the first set of rows and provides the current boundary to the table scan operator. The table scan operator prunes the scan set based on the current boundary and identifies a second set of rows from the table based on the pruning.

Abstract: An exemplary memory is configurable to operate in a low latency mode through use of a low latency register circuit to execute a read or write command, rather performing a memory array access to execute the read or write command. A control circuit determines whether an access command should be performed using the low latency mode of operation (e.g., first mode of operation) or a normal mode of operation (e.g., second mode of operation). In some examples, a processor unit directs the memory to execute an access command using the low latency mode of operation via one or more bits (e.g., a low latency enable bit) included in the command and address information.

Abstract: A system, method, and computer-program product includes identifying a target hierarchical taxonomy that includes a plurality of distinct hierarchical taxonomy categories, extracting a plurality of distinct taxonomy tokens from the plurality of distinct hierarchical taxonomy categories, computing a taxonomy vector corpus based on the plurality of distinct taxonomy tokens, computing a plurality of distinct taxonomy clusters based on an input of the taxonomy vector corpus, constructing a hierarchical taxonomy classifier based on the plurality of distinct taxonomy clusters, converting a volume of unlabeled structured datasets to a plurality of distinct corpora of taxonomy-labeled structured datasets based on the hierarchical taxonomy classifier, and outputting at least one corpus of taxonomy-labeled structured datasets of the plurality of distinct corpora of taxonomy-labeled structured datasets based on an input of a data classification query.

Abstract: A transmission apparatus includes a transmission unit. The transmission unit transmits a packet including divided image data as payload data, the divided image data being obtained by dividing image data having a predetermined frame frequency into a predetermined number of frames, the image data having the predetermined frame frequency being subjected to mixing processing for each frame, image data of a previous frame and/or a subsequent frame being selectively used in the mixing processing, and further transmits metadata including information regarding the mixing processing in association with image data of each frame.

Abstract: A method for classifying organizations involves obtaining, for an unknown organization, transactional data representing a multitude of transactions. The transactional data comprises a descriptive text for each of the multitude of transactions. The method further involves processing the descriptive text for each of the multitude of transactions to obtain one vector representing the unknown organization, categorizing the unknown organization using a classifier applied to the vector, and identifying a software service for the unknown organization, according to the categorization.

Abstract: An online content management service can collect and store receipts for a user from a variety of sources, including images captured by the user, messages received for the user at a messaging service or message management service, and/or receipts directly uploaded to the online content management service by a merchant. In the case of receipts provided as messages, a user can interact with a message management service to identify messages as receipts, and the message management service can upload such messages to the online content management service.

Abstract: A method of valuating a plurality of digital content items including: receiving the plurality of digital content items; for each received content item: establishing a plurality of attributes from content and characteristics of the content item; establishing a lifetime indicating a span of consumers interest in the content item; producing a valuation function for calculating a market value of the content item during its lifetime by finding and ranking nearest one or more previously processed content items having the plurality of attributes with closest similarity to the plurality of attributes of the received content item, performing weighted averaging of the valuation functions produced for the nearest one or more of the previously processed content items; and adapting, using “edge cutting” adaptation, the produced valuation function to a market response reflecting behavior of the consumers in response to the market values of the content item calculated by the valuation function.

Abstract: Systems and methods for determining whether a user is part of a defined segment of all users makes use of a database of user information that includes rapidly searchable field values. Predetermined segment definitions can be evaluated using information from a user's record in the database to rapidly determine if the user is a member of the segment.

Abstract: In one aspect, hierarchical image segmentation is applied to an image formed of a plurality of pixels, by classifying the pixels according to a hierarchical classification scheme, in which at least some of those pixels are classified by a parent level classifier in relation to a set of parent classes, each of which is associated with a subset of child classes, and each of those pixels is also classified by at least one child level classifier in relation to one of the subsets of child classes, wherein each of the parent classes corresponds to a category of visible structure, and each of the subset of child classes associated with it corresponds to a different type of visible structure within that category.

Abstract: A technique is described for generating a unified list (e.g., a list ribbon) of programs from a variety and disparate channels, the list for display on an over-the-top (OTT) client device. As an example, the unified list can be generated from OTT live channels and from over-the-air OTA and/or Advanced Television Systems Committee (ATSC) live channels. Further, the unified list can include OTT recordings on the cloud and OTA/ATSC recordings on the local hard drive connected to an OTA local DVR. Thus, the OTT device Client obtains the list from the DVR backend, instead of going to the local OTA client box for the local recordings.

Abstract: A recognition method includes retrieving an input including data of a first window size. The method further includes classifying the input based on comparison of warping distance of the input with a pruning threshold.

Abstract: Systems and methods for personalized visualization recommendation are described.

Abstract: Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Abstract: Systems and methods for managing network devices include performing clustering operations for network devices based on attributes of the network devices. By comparing the results of subsequent clustering operations, changes in network device attributes can be readily identified and any network devices for which attributes have changed may be subject to further investigation or remedial action (e.g., blocking traffic to/from the network device). Clustering may also be used to conduct an inventory of network devices by identifying groups of network devices that have similar attributes.

Abstract: The present disclosure generally relates to methods of operating storage devices. The storage device comprises a controller comprising first random access memory (RAM1), second random access memory (RAM2), and a storage unit divided into a plurality of zones. The controller restricts the host to a maximum number of zones that can be in the open and active state at a time. Open zones can be switched to the closed state, and vice versa, upon a predetermined amount of time expiring. The maximum number of open zones is based on one or more amounts of time to: generate parity data, copy the parity data from the RAM2 to the RAM1, update the parity data, switch a zone from the open and active state to the closed state, and the amount of space in a temporary RAM1 buffer.

Abstract: A apparatus for credentialing users across multiple devices. The apparatus includes a processor connected to a network and at least a user device. Processor is configured to receive a credential data structure, verify the credential data structure, generate a credential block, and store the credential block in a data storage system. A plurality of user devices may access the network and the data storage system to view the verified credentials.

Abstract: Systems, methods, and devices for generating a transactional change tracking summary for a database. A method includes executing a transaction on a table of a database, wherein the table includes a micro-partition and the transaction is executed on the micro-partition. The method includes, in response to the transaction being fully executed, generating a change tracking entry comprising an indication of one or modifications made to the table by the transaction. The method includes storing the change tracking entry in a change tracking stream, wherein the change tracking stream includes one or more sequential change tracking entries that each correspond to a different transaction that is fully executed on the table.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed that improve detection of malware based on ecosystem specific data. An example apparatus includes a feedback weight controller to apply, with a machine learning model, a weight to feedback associated with a sample, the feedback obtained from at least a customer ecosystem and including endpoint feedback, human feedback, infrastructure feedback, and global feedback; and a sample conviction controller to, in response to a score based on the weighted feedback satisfying a threshold for a classification, indicate to a user, with the machine learning model, that the classification for the sample is malicious.

Abstract: Provided are techniques for mode-specific search query processing. A current search query is received from a user, wherein the user has a user profile. In response to determining that a query mode for the current search query is a guided mode, a query context of the current search query is determined. A classification for the current search query is determined. One or more search influencers are identified using the classification, where each of the one or more search influencers has a corresponding user profile. The current search query is rewritten based on the query context, a private portion of the user profile of the user, and a public portion of each corresponding user profile of each of the one or more search influencers. The rewritten search query is executed to generate search results, and the search results are returned.

Abstract: A computer-implemented method includes obtaining a plurality of textual records divided into clusters and a residual set of the textual records, where a machine learning (ML) clustering model has divided the plurality of textual records into the clusters based on a similarity metric. The method also includes receiving, from a client device, a particular textual record representing a query and determining, by way of the ML clustering model and based on the similarity metric, that the particular textual record does not fit into any of the clusters. The method additionally includes, in response to determining that the particular textual record does not fit into any of the clusters, adding the particular textual record to the residual set of the textual records. The method can additionally include identifying, by way of the ML clustering model, that the residual set of the textual records contains a further cluster.

Abstract: An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using transfer learning. The processor can generate a label based on the extracted features via a machine learning classifier model trained on internal analysis states of hybrid code analyses.