Abstract: The described technology is generally directed towards configuring a client device with client configuration data based on client context data. The configuration data can include endpoints of various services to which the client can connect that are appropriate for the client device based on the client context data, along with dimension information (route key values) for connecting to each such service. For example, a roaming client device can be given an endpoint and dimension information to connect to a content service in the roaming region, with a different endpoint and dimension information for communicating user information to a home region to which the user is affiliated. This facilitates single hop/reduced latency for content requests, and compliance with home regulations via a single hop to the home service.

Abstract: Various embodiments include systems, methods, and non-transitory computer-readable media for managing data. Consistent with these embodiments, a method includes identifying a data record from a database; converting the data record into a data object; partitioning the data object into a plurality of files; generating a plurality of events based on the plurality of files; and causing the plurality of events to be transmitted to a destination.

Abstract: Examples include bypassing a portion of an analytics workflow. In some examples, execution of an analytics workflow may be monitored upon receipt of a raw data and the execution may be interrupted at an optimal bypass stage to obtain insights data from the raw data. A similarity analysis may be performed to compare the insights data to a stored insights data in an insights data repository. Based, at least in part, on a determination of similarity, a bypass operation may be performed to bypass a remainder of the analytics workflow.

Abstract: A computer-implemented method for optimizing a distributed database includes receiving, at an aggregator, one or more query logs comprising past queries received by the distributed database. The method includes generating, by the aggregator, a query prediction model based on the one or more query logs. The method includes predicting, by the aggregator, a future query using the query prediction model. The predicted future query is predicted to be received by an edge device. The method includes causing, by the aggregator, data for responding to the predicted future query to be transmitted to the edge device.

Abstract: Presented herein are systems and methods are presented for detecting out-of-vocabulary (OOV) words in an automatic speech recognition (ASR) system, determining an intended word for the OOV, and adding the intended word to a repository of words. A method may involve receiving audio input data including a series of spoken words; determining that one of the spoken words is an out of vocabulary word absent from a repository of words; generating word candidates based on characteristics of the out of vocabulary word; presenting the word candidates on a display; receiving intended word input data that indicates a selection of one of the word candidates as an intended word for the out of vocabulary word; and adding the intended word to the repository of words. Additionally, one or more devices or apparatuses may be configured to perform such method.

Abstract: This disclosure relates to a content cluster system that provides a framework for leveraging large language models (LLMs) to tag content items (e.g., interactive multimedia content items, such as gaming content items) with attribute tags and, based on attribute tags for related content items, generating cluster descriptions of a cluster of content items. Features of the content cluster system involve tagging content items, determining multi-dimensional embeddings for the content items, and clustering the content items based on proximity of values contained within the multi-dimensional embeddings. The content cluster system may further utilize the LLM to generate one or more cluster descriptions based on the associated tags to create a more creative and dynamic representation of related groupings of titles (e.g., gaming titles). By utilizing LLMs and machine learning resources, the content cluster system provides a scalable approach to conventional approaches in determining and presenting groupings of titles.

Abstract: A system and method for objective quantification and mitigation of privacy-risk of a dataset is disclosed.

Abstract: The present disclosure relates to a system, a method, and a product for intent discovery. The system includes a processor in communication with a memory storing instructions. When the processor executes the instructions, the instructions are configured to cause the processor to: obtain documents comprising a set of utterances, extract the set of utterances from the documents, generate a set of utterance embeddings based on the set of utterances, clusterize the set of utterance embeddings to obtain a plurality of clusters, obtain a cluster label for each cluster, encode each document based on a number of times each utterance cluster identifier (ID) appears to obtain an encoded document, perform latent Dirichlet allocation (LDA) on the encoded documents to obtain K topics, and each topic corresponding to a list of key clusters with cluster IDs, and for each topic, replace the cluster IDs with the cluster labels.

Abstract: A method for providing data streams to a client over a network interface wherein the data streams comprise message data streams which form provenance views based on provenance information is disclosed. The method comprises, by a routing component; receiving (101), from a client, a request comprising a query for a provenance view submitted, obtaining (104) provenance information from a provenance information database based on the query of the received request, wherein the provenance information database comprises provenance relationships between provenance entities, obtaining (105) message data from a message data database based on the query of the received request, wherein the message data database comprises data corresponding to the provenance entities, deriving (106) correlated data based on the obtained provenance information and the obtained message data, and providing (109), to the client, the derived correlated data as a provenance view in message data streams.

Abstract: A hybrid system for natural language processing is provided. The system may include a transceiver operable to receive a query from a user. The query may include a stock portion integrated with a set of real-time conditions specific to the user. The transceiver may transmit the query to a model and to a response application. The model may receive the query and communicate with a data store. Based on historical data stored at the data store, the model may separate the stock portion from the set of real-time conditions, formulate a response to the stock portion and insert placeholders into the response for responses to the real-time conditions portion. The response application may receive the query and the response. The response application may communicate with private data stores to formulate responsive elements for the placeholders. The response application may insert the responsive elements into the placeholders to complete the response.

Abstract: A reward determination system determines distribution of a reward received from a data user to reward distribution targets in a platform for distribution and utilization of biological data provided by data providers. Each reward distribution target has: development task information obtained by quantifying a workload of a task required for developing the platform into numbers; data provision task information obtained by quantifying a workload of a task required for providing the biological data into numbers; and data processing task information obtained by quantifying a workload of a task required for processing the biological data into numbers. A reliability parameter and a contribution parameter of each task are calculated based on the development task information, the data provision task information, and the data processing task information on each task, and a reward to be allocated is determined for each reward distribution target based on the reliability parameter and the contribution parameter.

Abstract: A server for a vehicle-to-everything (V2X) service receives, from a first V2X device, a subscription request for requesting subscription of the V2X service, and sets a subscription area for the first V2X device. The server publishes, to the first V2X device, at least one V2X message published by at least one second V2X device associated with the subscription area.

Abstract: A head image registration uses a plurality of combined 2D and depth images, for example RGBD images, of a head recorded from different positions. Landmark points are determined for each of the combined images. The registration is performed as a coarse registration based on the landmark points followed by a fine registration based on full point clouds. Based on the registration, a head model may be generated.

Abstract: Examples of the present disclosure describe systems and methods for determining relationships between content items to create a visualization associated with the various content items. The visualization may provide information regarding what various individuals in a group, team, or organization have been working on (e.g., content, documents, projects).

Abstract: Embodiments of the present disclosure relate to a method, an apparatus and a computer program for providing a machine-learning system to be used for classifying transactions as either fraudulent or genuine, and a method, an apparatus and a computer program for classifying transactions as either fraudulent or genuine. The method for generating a machine-learning system for classifying transactions as either fraudulent or genuine based on a plurality of training transactions, each training transaction being associated with labelling information that indicates whether the training transaction is either genuine or fraudulent, comprises clustering the plurality of training transactions into a plurality of clusters based on a similarity measure. The method comprises determining, for each of the plurality of clusters, whether the cluster is homogeneous or heterogeneous. A heterogeneous cluster includes both fraudulent and genuine training transactions.

Abstract: A method for assigning data to similarity groups (sim-groups). The method includes: partitioning a data stream, originating from a data source, into stream chunks; for at least a first stream chunk of the stream chunks: initializing a first chunk bin-map for the first stream chunk; partitioning the first stream chunk into first chunk segments; updating the first chunk bin-map based on a chunk segment processing of the first chunk segments; computing, to obtain a first similarity distance set, a similarity distance between the first chunk bin-map and each sim-group bin-map in a first set of sim-group bin-maps; identifying a first sim-group corresponding to a first similarity distance in the first similarity distance set; and assigning the first stream chunk to the first sim-group.

Abstract: A similarity search system includes a database of original vectors, a hierarchical database of bins and a similarity searcher. The hierarchical database of bins is stored in an associative memory array, each bin identified by an order vector representing at least one original vector and the dimension of the order vector is smaller than the dimension of the original vector. The similarity searcher searches in the database for at least one similar bin whose order vector resembles an order vector representing a query vector and provides at least one original vector represented by the bin resembling the query vector.

Abstract: Described are input output (IO) device configured to perform operations for performing a table lookup with a single wide key larger than a width of a system bus. These operations comprise: receiving the lookup key; performing a plurality of extraction cycles to determine a plurality of key fragments; calculating a final hash value for the lookup key by sequentially calculating, via a hash chain, an interim hash value for each of the key fragments; determine a read access address for a table entry of a logic table based on the final hash value for the lookup key; determine a plurality of read requests based on the read access address; determine a hit on the table entry with the lookup key by issuing each of the read requests to the memory subsystem; and provide the hit on the table entry to the requesting entity or a next processing entity.

Abstract: A message management method based on time and location is applied to the network system. Comprises obtaining a user account, a location information and a time information through an electronic device, and transferring the user account, the location information and the time information to a message server; obtaining a geographic information from a map database based on the location information, and displaying a region of the geographic information on a display of the electronic device; and in a display page of the display, using the user account, the time information and the region as a filter condition, obtaining a name, an avatar of a relevant user from a user database, and obtaining a message of the relevant user from a message database, and displaying the name, avatar and message of the relevant user on the display page according to the sending location of the message.

Abstract: A system and method for clustering computing interface calls. A method includes: determining a plurality of computing interface cluster definitions, the plurality of computing interface cluster definitions including a plurality of parameter type strings; and clustering a plurality of computing interface call instances into a plurality of clusters based on the plurality of computing interface cluster definitions, wherein a number of clusters among the plurality of clusters is fewer than a number of computing interface call instances among the plurality of computing interface call instances, wherein clustering the plurality of computing interface call instances includes determining a plurality of portions of the plurality of computing interface call instances which match types of parameters represented by respective parameter type strings of the plurality of parameter type strings.

Abstract: User interfaces for presenting media items are described. In one example, an electronic device receives a user input specifying a hashtag in a first user interface of an application of an electronic device, and in response, provides, for display, a second user interface that comprises a first portion, a second portion, and a third portion, wherein: the first portion is configured to receive a sequence of text, and the sequence of text comprises the hashtag by default; the second portion comprises a search result based on the hashtag, the search result comprises a plurality of media items associated with the hashtag; and the third portion is configured to receive one or more user interactions for creating a new media item.

Abstract: An automotive data processing system includes a storage subsystem and a processor. The storage subsystem is disposed in a vehicle and is configured to store at least data produced by one or more data sources of the vehicle. The processor is installed in a vehicle and is configured to apply, to the data stored in the storage subsystem or that is en route to be stored in the storage subsystem, at least one model that identifies one or more specified features-of-interest in the data, so as to generate metadata that tags occurrences of the specified features-of-interest in the stored data, and to export at least part of the metadata to an external system that is external to the vehicle.

Abstract: A method and a computer program for discovering possible errors in a production process for manufacturing metal products. The method involves removing at least one process parameter value from the cluster or adding at least one process parameter to the cluster. Second Z-score values, which are compared with the first Z-score values, are then determined for the thus-altered cluster. The changes in the Z-score values provide suggestions for troubleshooting and process optimization which are direct and can be implemented immediately.

Abstract: Data races are resolved and rows are deduplicated between upqueries and updates to an underlying database, in a database caching layer on top of the underlying database. The caching layer maintains a dataflow graph of nodes representing row data of the underlying database, database operators, and partially or fully materialized queries, wherein queries that use common row data and/or database operators share corresponding nodes. A data race resolution and row deduplication algorithm may be applied on every node that contains a partial materialization, and is correct regardless of how many times this node is reused throughout the dataflow graph. It prevents any of the nodes from seeing duplicated packets between the external upqueries that are originated from each node and any underlying database change events which the node observes.

Abstract: An apparatus for conditioning raw data based on temporal interpolations to generate optimal extrapolations of an entity, comprising a processor and a memory containing instructions configuring the processor to receive raw data associated with a temporal element from an entity condition the raw data, wherein conditioning the raw data includes clustering the raw data into primary clusters, wherein clustering the raw data includes dividing each primary cluster into a plurality of secondary clusters each contains a corresponding temporal interpolation, and ranking the plurality of secondary clusters as a function of the corresponding temporal interpolations, determine an extrapolation for each secondary clusters of the ranked plurality of secondary clusters based on the conditioned raw data, and generate a progression model as a function of the extrapolations.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses for generating synthetic data based on time series predictions and plural machine learning models. Generating the synthetic data may include receiving one or more data records that include transaction data of a user, categorizing and/or segmenting the one or more data records, determining a first predicted time step based on the categorizing and/or segmenting, and performing an iterative process that determines further predicted time steps. The first predicted time step may be determined using one model of a plurality of machine learning models. The iterative process may determine the further predicted time steps using the plural machine learning models. Based on iterations of the iterative process, potential time series may be determined. The synthetic time series may be determined from the potential time series. The synthetic time series may be used by additional processes, such as additional machine-learning processes.

Abstract: Processes and machines are disclosed for detecting malicious email campaigns based on unique but similarly spelled attachments. Email log(s) from network appliances are retrieved, filtered, normalized, and converted into field-based organized data for comprehensive analysis. Cluster analysis is performed. Filenames of email attachments are transformed into numerical vectors and a cosine similarity termset analysis is performed on the numerical vectors. Data is organized into time bins for burst detection. Statistical analysis is performed on the time bins. Pattern recognition is performed to identify alphanumeric similarities in the filenames of the attached files in order to detect malicious email campaigns. Machine learning may be used to optimize the cosine similarity threshold and other query variables, and to update existing cybersecurity filters and firewalls. Mitigation can be performed to remove malicious emails that were delivered to recipient mailboxes.

Abstract: The present invention proposes a method for intelligent management of valve production process data, a medium, and an apparatus. Through results of grid classification of sampling points, the method constructs information entropy of grid distribution density levels as well as grid distribution density, which takes into account the circumstance that sampling points may not exist in the classification space, so as to avoid grids where sampling points do not exist from affecting the local density of the sampling points; secondly, based on the core relative distance of the sampling points in a seed grid, the method constructs a coverage density distance, which takes into account the magnitude of the local density of the sampling points in the seed grid as well as differences in the distance from sampling points that have a relatively large local density in the other seed grids.

Abstract: An example operation may include one or more of receiving, by a resolver node, asset data to be recorded on a blockchain, executing, by the resolver node, a smart contract to apply an asset data validation format to the asset data, rejecting, by the resolver node, non-conforming asset data from being stored on the blockchain based on the execution of the smart contract, and accepting the asset data validated by the smart contract.

Abstract: Low latency search for nearest neighbors in a dataset containing a large number of entries is improved using an error correction code (ECC) for partitioning data into clusters and retrieval. During initialization and preprocessing a d-dimensional space with clusters corresponding to ECC codewords is specified. Entries in the dataset are embedded into this space and associated with respective codewords, each codeword specifying a cluster. An index associates the codewords, clusters, and entries. During a query of the dataset, a query entry is processed to determine a query embedding in the d-dimensional space. The query embedding is used as input for a list decoder of the ECC. The list decoder provides a set of nearest codewords, with those codewords representing a set of candidate clusters that may contain nearest neighbors. The dataset entries associated with the candidate clusters may then be searched to determine query results comprising specific entries.

Abstract: Techniques and a system to facilitate estimation of a quantum phase, and more specifically, to facilitate estimation of an expectation value of a quantum state, by utilizing a hybrid of quantum and classical methods are provided. In one example, a system is provided. The system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can include an encoding component and a learning component. The encoding component can encode an expectation value associated with a quantum state. The learning component can utilize stochastic inference to determine the expectation value based on an uncollapsed eigenvalue pair.

Abstract: According to the present invention, provided is a method for collecting filtered text data, comprising the steps in which: a computing device acquires first text data and records the first text data in a text data pool; the computing device acquires second text data; the computing device performs a calculation in a deep learning model by using the first text data and the second text data as input values and calculates a first feature vector corresponding to the first text data and a second feature vector corresponding to the second text data; and the computing device compares the degree of similarity between the first feature vector and the second feature vector, and records the second text data in the text data pool when the degree of similarity is less than a predetermined value.

Abstract: A risk-prediction-preparation module to generate a risk-prediction-model, is provided herein. The risk-prediction-preparation module includes accessing a data-storage of transactions to operate a group-by operation on transactions related to data-points, according to a logical-entity into entities. Then, clustering entities of a clean-financial dataset into clusters. Selecting data-points of: (a) entities from the clusters to a first dataset and (b) a preconfigured amount of entities randomly to a second dataset. Selecting all entities that have at least one ‘fraudulent’ data-points in at least one related data-point to add all the entities to the first dataset and the second dataset. Using vectorized and scaled extracted features for training a first machine-learning-model of fraud detection on the first dataset and training a second machine-learning-model of fraud detection on the second dataset to collect results.

Abstract: A method including generating, by a navigation service, a route for navigating from a route origin to a route destination using a private roads repository. The method includes identifying a ghost origin and a ghost destination of a ghost road along the route. The method includes sending, using an application programming interface of a base roads engine, a first request for a route from the ghost origin to the ghost destination. The method includes receiving, from the base roads engine in response to the first request, a replacement section from the ghost origin to the ghost destination. The method includes replacing, in the route, the ghost road with the replacement section to create an updated route including segments. The method includes generating an estimated travel time from the route origin to the route destination over the segments of the updated route. The method includes presenting the estimated travel time.

Abstract: A method for deployment of machine-learning based operators within a query is described. For this embodiment, a sequence of operators associated with a query is identified, which includes at least a first operator and at least a second operator. The second operator is configured to perform operations, in accordance with a machine learning (ML) component, on data received as input from execution of the first operator. Schemas associated with the machine learning component is retrieved along with schemas associated with other operators within the sequence. Compatibility between at least an output schema associated with the first operator and an input schema associated with the second operator associated with the ML component is determined. Thereafter, a portion of the sequence of operators including at least the second operator and another operator of the sequence of operators successive to the second operator may be stored within a data store for subsequent use.

Abstract: A system and method of enhancing the trustworthiness of an artificial intelligence system include detecting whether a data element includes an existing data domain tag, processing the data element into a transformed data element, generating a data domain tag, where the data domain tag includes at least a data domain identifier and a timestamp, appending the data domain tag to the transformed data element, creating a signature for the transformed data element and the appended data domain tag using a private key, and creating another signature for the data domain tag using the private key.

Abstract: A system for automated information support processing is disclosed. The system may receive a natural language information support request from a plain text input channel. The system may determine a first user intent based on the information support request. The system may compare the first user intent with a set of support rules. The system may determine a dispositioned outcome based on the set of support rules and the user intent. The system may return the dispositioned outcome.

Abstract: An example system includes a processor to execute a key point analysis to extract key points from a number of input sentences. The processor can compute directional relation scores between the extracted key points. The processor can construct a key point graph based on the extracted key points and the directional relation scores. The processor can generate a key point graph visualization based on the key point graph.

Abstract: A method and apparatus for preparing an image on a cloud platform, and a device and a storage medium are provided. The method may include: receiving an image request for a target object, and obtaining a first storage backend of the target object according to the image request; obtaining a second storage backend of a Glance service in the cloud platform, and comparing the second storage backend with the first storage backend; and obtaining an image for the target object on the second storage backend in a cloning manner when the first storage backend is the same as the second storage backend. According to the method, when the first storage backend is the same as the second storage backend, the image for the target object is obtained on the second storage backend in the cloning manner, so that the downloading and uploading processes are omitted.

Abstract: Existing content such as books are reorganized and condensed as electronic books for display on a mobile computing device. The electronic books have a hierarchical structure. A user interacts with the content of the book by way of a touch screen of the mobile computing device. The navigation may be non-linear in nature and the book is reconstructed as a set of primary ideas, supporting ideas, stacks of cards for the supporting ideas, and individual cards comprising elements and commentary from or about the book.

Abstract: Domain name system (DNS) configuration during virtual private network (VPN) connection includes, by a VPN entry server, receiving from a client device, via a VPN tunnel between the entry server and the client device, a first request for first content that identifies a first external source for the first content, receiving, from an operative DNS server configured for the tunnel, an Internet Protocol (IP) address of a first VPN system exit server, in response to determining that the first content is unavailable via the first system exit server, identifying a second DNS server, such that a second VPN system exit server for obtaining the first content is available using the second DNS server, obtaining, from the second system exit server, the first content, wherein the second system exit server obtained the first content from the first external source, and transmitting, to the client device, via the tunnel, the first content.

Abstract: Embodiments disclosed herein describe systems and methods to generate statuses of higher level integrated logical clusters from one or more output files generated by the clusterwares of a plurality of lower level physical clusters. The systems and methods provide an interactive dashboard graphical user interface (GUI) rendering the statuses of the higher level logical clusters. In response to a drill down selection by the system administrator, the systems and methods may render resource level statuses of the plurality of resources forming the higher level logical cluster. Therefore, by using a single dashboard, a system administrator can seamlessly transition between statuses at different level of abstractions for multiple resources distributed across multiple geographically diverse datacenters. Furthermore, the dashboard allows the system administrator to perform failover operations.

Abstract: Provided are a computer program product, system, and method for pre-processing a table in a document for natural language processing (NLP). A graphical user interface (GUI) provides a representation of table items in a table in a document including a set of a main element comprising an entity whose value is to be extracted, a conditional element that refines the entity, and a value element comprising a value for the entity. Graphical controls are rendered in the GUI to enable a user to select an element from the table to be the main element, conditional element, and value element. The set of the main element, conditional element, and value element are updated with the user selected element to form a modified set. The modified set of the main element, conditional element, and the value element are provided to an NLP engine to perform natural language processing.

Abstract: The present disclosure relates to database technology and in particular to dynamically updating and customizing database partitions. A computer-implemented engine is disclosed for identifying and retrieving a number of data records applicable to generate a response to a request, the engine having access to at least two partitions. Partition statistics are generated indicating correlations between the data records and, based on that partition statistics, the data records having the strongest correlation with each other are relocated to partitions so that the number of partitions which have to be queried in order to generate a response to a data request is minimized. Furthermore, the computational load caused when generating responses is more equally distributed across the partitions.

Abstract: A system for generating a workload model for a target information handling system includes gathering workload data from a plurality of information handling systems, dividing the workload data into a plurality of workload data bins, identifying workload data characteristics for each workload data bin and identifying workload data sets that may be applicable to the target information handling system. A workload mix may be determined based on the target information handling systems and workload data characteristics. Real customer workload data including real-time or near real-time workload data may be used to check a workload model for accuracy before deploying the workload model to a target information handling system.

Abstract: Embodiments of the present disclosure relate to an article processing method, electronic device, and computer program product. The method includes: determining, based on content of a target article, a target article vector associated with the target article; acquiring a reference article vector set associated with a reference article set; and determining, based on a distance in an article vector space between the target article vector and a reference article vector in the reference article vector set, a reference article vector associated with the target article vector in the reference article vector set as an association article vector. By using the technical solution of the present disclosure, an association article associated with a target article can be accurately provided based on the target article selected by a user, so that reports on the target article and its association articles can be further provided to the user for analysis and selection.

Abstract: Methods, systems, and computer-readable media are disclosed herein to provide rule-based reconciliation of records. Specifically, rules are utilized to reconcile one or more records and identify duplicates therein. Once duplicate records are identified, one or more ranking sets can be utilized to identify which of the duplicate records to write to the system.

Abstract: Clustering structured log data by key-values includes receiving, via a user interface, a request to apply an operator to cluster log messages according to values for keys associated with the request. At least a portion of each log message comprises structured machine data including a set of key-value pairs. The method further includes receiving a log message and determining whether to include the log message in a cluster based at least in part on an evaluation of values in the structured machine data of the log message for the keys associated with the request. The cluster is included in a set of clusters. Each cluster in the set is associated with a different combination of values for the keys associated with the request. The method further includes providing, via the user interface, information associated with the cluster.

Abstract: Systems and methods for scaling application and/or storage system functions of a distributed storage system based on a heterogeneous resource pool are provided. According to one embodiment, the distributed storage system has a composable, service-based architecture that provides scalability, resiliency, and load balancing. The distributed storage system includes a cluster of nodes each potentially having differing capabilities in terms of processing, memory, and/or storage. The distributed storage system takes advantage of different types of nodes by selectively instating appropriate services (e.g., file and volume services and/or block and storage management services) on the nodes based on their respective capabilities. Furthermore, disaggregation of these services, facilitated by interposing a frictionless layer (e.g.

Abstract: A storage device generates and stores a key stream and a value stream by extracting from data a plurality of keys and a plurality of values respectively corresponding to the plurality of keys. The storage device includes a controller and a non-volatile memory. The controller receives from a host information about an invalid key included in the key stream together with a compaction command, and performs a compaction operation on the key stream in response to the compaction command. The non-volatile memory stores the key stream and the value stream. The controller merges the key stream with another key stream based on the information about the invalid key in the compaction operation.