Abstract: Methods and systems are disclosed herein for updating a knowledge graph based on a user confirmation. A media guidance application receives a user communication and isolates a term of the user communication. The media guidance application identifies a candidate component of a knowledge graph associated with the term. The media guidance application requests user input directed to confirming whether the term is associated with the candidate component. In response to receiving the user input, the media guidance application modifies a strength of association between the term and the component.

Abstract: Techniques and solutions are described for storing and processing metadata, including to instantiate database artefacts at a target system based on metadata for database artefacts maintained at a source system. The target system can query the source system for metadata associated with database artefacts of the source system. The target system can instantiate database artefacts based on such metadata. The database artefacts of the target system are linked to corresponding database artefacts of the source system, such as by associating a database artefact of the target system with an API useable to obtain data or metadata from the source system for a corresponding database artefact of the source system. The target system obtains additional data or metadata for a database artefact of the target system using a corresponding API.

Abstract: An example operation includes one or more of solving, by a scheduler node, integer programming problem of maximizing a sum of organizations' endorsing peers that run chaincodes from a plurality of chaincodes within a consortium, making, by the scheduler node, endorsement policies (EPs) for the chaincodes from the plurality of the chaincodes to be satisfiable at any time, applying administrator's constraint of available endorsing peers to the maximized sum of organizations' endorsing peers, and adding resulting endorsing peers to a maintenance list.

Abstract: This application is directed to recognizing unstructured information based on hints provided by structured information. A computer system obtains unstructured information collected from a handwritten or audio source, and identifies one or more terms from the unstructured information. The one or more terms includes a first term that is ambiguous. The computer system performs a recognition operation on the first term to derive a first plurality of candidate terms for the first term, and obtains first contextual information from an information template associated with the unstructured information. In accordance with the first contextual information, the computer system selects a first answer term from the first plurality of candidate terms, such that the first term is recognized as the first answer term.

Abstract: A method for determining a storage location includes one or more processing modules of one or more computing devices of a storage network (SN) receiving a data object to store in a storage network (SN) and determining whether the data object is subject to a legal restriction, where a data object is subject to a legal restriction based on the data object requiring storage in a jurisdiction that subjects the data object to a retention policy. The method continues by determining one or more attributes of a first storage location of a plurality of storage locations and based on a determination that the data object is subject to a legal restriction and at least one attribute of the one or more attributes of the first storage location, transmitting a write threshold number of write requests to a plurality of SUs at the first storage location.

Abstract: An efficient blend of home/personal and work/productivity related content based on a user's intent is provided, wherein the user's intent can be determined based on context information, learned user interaction patterns, and historical work and home characteristics and patterns. The system is individualized to the user and operative to generate a user experience that provides a blend of relevant home/personal and work/productivity related information to the user based on the user's current work and life characteristics. From a determined user intent, various aspects provide personalized computing experiences tailored to the user and, in some examples, incorporation of the user's patterns into an efficient blend of personal and productivity workflows.

Abstract: To execute function-step-based graph queries on a graph engine that has its own graph query language, rather than re-implementing an existing infrastructure to support function-step-based graph protocols, function-step-based graph queries are transformed to the graph query language that is understood by the graph engine. The existing infrastructure computes the results of the transformed queries. Result sets are then transformed to function-based-based result sets, which are returned to customers. In this manner, the graph engine supports function-step-based graph query workloads without implementation of the function-step-based graph protocol.

Abstract: Methods and systems for request orchestration. One system includes an electronic processor configured to receive a request including request metadata and identify a data attribute associated with the request. The electronic processor is also configured to determine an execution plan for enriching the request metadata based on the data attribute. The electronic processor is also configured to execute an application function according to the execution plan to enrich the request metadata. The electronic processor is also configured to evaluate the enriched request metadata. The electronic processor is also configured to generate and transmit a response to the request based on the evaluation of the enriched request metadata.

Abstract: A method for managing data processing includes receiving, from a user of a data query system, a data query for data stored in a data store in communication with the data query system. The method also includes receiving a staleness parameter indicating an upper time boundary for the data query. The upper time boundary limits a query response to data within the data store that is older than the upper time boundary. The method further includes determining whether the data stored within the data store satisfies the staleness parameter. When a portion of the data within the data store fails to satisfy the staleness parameter, the method includes generating the query response that excludes the portion of the data that fails to satisfy the staleness parameter.

Abstract: A method, apparatus, and system including performing a partitioning function on a first table of a join query, determining a size of the first table based on the partitioning function, and distributing the first table to a set of nodes of a computing cluster based on the size of the first table.

Abstract: An approach is provided for optimizing a system resource of a cloud database. Components of a database system are divided into micro-systems according to functions and execution levels. A cluster analysis of the micro-systems and an analysis of workload patterns are performed. Different combinations of the micro-systems are generated. Images of the micro-systems and of the different combinations of the micro-systems are generated. A query is received and analyzed at a current layer specifying a set of micro-systems specified by a function of the database system. Service(s) associated with micro-system(s) specified by next layer(s) are pre-loaded and activated. A partial execution of the query is performed and a result of the query is generated at a selected edge or client side, where the selection is based on the analysis of the workload patterns.

Abstract: Systems, methods, and devices for retrying a query. A method includes receiving a query directed to database data and assigning execution of the query to one or more execution nodes of an execution platform, the one or more execution nodes configured to execute the query on a first version of a database platform. The method includes determining that execution of the query was unsuccessful. The method includes assigning a first retry execution of the query to the one or more execution nodes of the execution platform and determining whether a regression or an intermittent fault caused the execution of the query to be unsuccessful based at least in part on whether the first retry execution of the query was successful or unsuccessful.

Abstract: A computerized system and method may include, in response to receiving a blockchain via a communications network that includes information associated with an event, parsing, by a blockchain parsing engine being executed by a blockchain node, the information to identify a status state of an item related to the event. The blockchain may be inclusive of the information along with the status state of the item may be stored in a storage unit. An event tracking engine may determine from the parsed information that the status state of the item transitioned from a first state to a second state. Responsive to the event tracking engine determining that a qualifying state is satisfied by the item being in the second state, automatically executing, by the blockchain node, a smart code inclusive of initiating communications between a first party and a second party.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A content retrieval system uses a graph neural network architecture to determine images relevant to an image designated in a query. The graph neural network learns a new descriptor space that can be used to map images in the repository to image descriptors and the query image to a query descriptor. The image descriptors characterize the images in the repository as vectors in the descriptor space, and the query descriptor characterizes the query image as a vector in the descriptor space. The content retrieval system obtains the query result by identifying a set of relevant images associated with image descriptors having above a similarity threshold with the query descriptor.

Abstract: A method comprises a client device receiving a verification request comprising an interaction identifier and generating a random sampling of a number of block headers. The random sampling according to a random distribution generated based on a probability density function. The client device can query two or more full nodes for random samplings of block headers. The client device can receive the random samplings of block headers from the two or more full nodes and compare samplings of block headers received from two or more full nodes. The samplings of block headers are the random samplings of block headers. The client device can verify at least one block header of the samplings of block headers, then determine that a blockchain maintained by at least one of the two or more full nodes is valid in response to verifying the at least one block header of the samplings of block headers.

Abstract: An information processing device for processing target data according to one or more embodiments may include a preprocessor and a preprocess ID assigner. The preprocessor may be configured to generate preprocessed data by performing at least one preprocess on the target data. The preprocess ID assigner may be configured to assign, to the preprocessed data, a preprocess ID corresponding to the at least one preprocess.

Abstract: A method of automated inquiry response includes forming clusters that represent a meaning. The method includes assigning a level of sophistication to the clusters and generating sub-clusters within the clusters that represent a sentiment or a level of sophistication. The method includes assigning responses to the sub-clusters that address the meaning of the cluster and are modified based on the sentiment or a level of sophistication. The method includes computing a substantive issue, a sentiment, and a level of sophistication of a received inquiry. The method includes identifying clusters to which the inquiry pertains and generating an order of the identified clusters based on the assigned level of sophistication. The method includes crowdsourcing a comparison of the substantive issue of the inquiry to meanings of the identified clusters. The method includes offering a response associated with one of the identified clusters and with the sub-cluster for the identified sentiment.

Abstract: A system and method for managing data storage and data access with querying data in a distributed system without buffering the results on intermediate operations in disk storage.

Abstract: At least one analytical agent extracts a plurality of attributes from each of a plurality of member input vectors. Each member input vector includes raw data characterizing contextual aspects about an associated and different user. Thereafter, a content search vector is generated for each user by the at least one analytical agent that includes the attributes extracted from the member input vector associated with such user and weights corresponding to each attribute that are particular to such user. A search engine, accessing a content library, then matches each content search vector with one of a plurality of content workflows based on both the attributes and weights within such content search vector. A context engine then initiates execution of each matching content workflow which results in tailored messages specified by the matching content workflow being sent to the user associated with the matching content workflow.