Abstract: Systems and methods for data migration in multi-layer model-driven applications is provided. The traditional systems and methods simply provide for comparison based migration approaches, and thus face severe challenges in case of model-driven applications, wherein continuous capturing of transformations in model changes is required. Embodiment of the proposed disclosure provide for a changelog based data migration methodology by modelling, a model-driven application conceptual model; generating, a plurality of optimized data models from the modelling; extracting, from each of the plurality of optimized data models, at least one changelog capturing one or more model changes and transformations in each of the plurality of optimized data models; and executing the data migration using each of an executing changelog.

Abstract: A centralized database identifier repository may identify databases using a unique identifier, or key tag, for each database. Each identified database may include data relating to one or more specific data elements. The repository may include a variety of data elements. Each data element may be associated with one or more database keys. The repository may be a repository of reference pointers. The repository may facilitate data viewing and data retrieval. A requestor may search for a data element using the centralized repository. The repository may retrieve data relating to a specific data element, from all databases identified by unique identifiers, that include data relating to the data element. The databases' unique identifiers may be encrypted tokens.

Abstract: Systems, apparatuses, and methods for automated data aggregation, automated webpage navigation, or automatically performing a task by entering data into multiple webpages. In some embodiments, this is achieved by use of techniques such as natural language processing (NLP) and machine learning to enable the automation of data aggregation and other tasks involving websites without the use of pre-programmed scripts.

Abstract: Systems and methods for multi-layered key-value storage are described. For example, methods may include receiving two or more put requests that each include a respective primary key and a corresponding respective value; storing the two or more put requests in a buffer in a first datastore; determining whether the buffer is storing put requests that collectively exceed a threshold; responsive to the determination that the threshold has been exceeded, transmitting a write request to a second datastore, including a subsidiary key and a corresponding data file that includes the respective values of the two or more put requests at respective offsets in the data file; for the two or more put requests, storing respective entries in an index in the first datastore that associate the respective primary keys with the subsidiary key and the respective offsets; and deleting the two or more put requests from the buffer.

Abstract: A computer analyzes blockchain ledger content. The computer receives a set of attributes associated with a predetermined entity and applies a one-way function to the attributes, generating an inquiry hash. The computer receives access to a blockchain ledger that includes a report with at least one report hash associated with an attribute of a report entity. The computer searches the report using the inquiry hash as a search key. The computer generates a list of candidate reports containing hashes that matches the inquiry hash. The computer assigns an entity matching confidence rating to candidate reports based, at least in part, on a predetermined identification utility value associated with each inquiry hash matched. The identification utility value indicates a likelihood that the report entity is the predetermined entity. The computer generates a list of high assurance reports having entity matching confidence ratings above a predetermined assurance threshold.

Abstract: Techniques for contextual modification of data sharing constraints in a distributed database system are disclosed. The constraint modifications can improve data sharing processes, particularly in applications that involve cross-model data sharing and/or have a need for low data latency.

Abstract: In some embodiments, a method selects a sequence of programs watched by a user account. The method calculates a first set of weights based on comparing content of the sequence of programs to content of a target program and calculates a second set of weights based on an order of the sequence of the programs and the first of weights. The first set of weights and the second set of weights are applied to the sequence of programs to generate a prediction of a similarity of the sequence of programs to the target program. Then, the method outputs the prediction of the similarity for use in determining a recommendation for the user account.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing semi-structured data. One of the methods includes maintaining a plurality of schemas; receiving a first semi-structured data item; determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas; and in response to determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas: generating a new schema, encoding the first semi-structured data item in the first data format to generate the first new encoded data item in accordance with the new schema, storing the first new encoded data item in the data item repository, and associating the first new encoded data item with the new schema.

Abstract: Systems and methods for updating values of roll-up summary fields (RSFs) associated with a data model are described. A server computing system receives data associated with roll-up summary fields (RSF) of objects of a data model. The data is in in a serialized format. The computer system deserializes the data to determine values of the RSFs at nodes of a graph associated with the data model. The computer system updates a value of a RSF at a first node of the graph. The computer system updates a value of one or more RSFs at one or more remaining nodes of the graph based on said updating the value of the RSF at the first node. The computer system serializes the values of the RSFs at all of the nodes of the graph to generate serialized data subsequent to said updating the value of the one or more RSFs at the one or more remaining nodes of the graph.

Abstract: Ranking a group of datasets using a computer includes determining a set of target data fields from a set of process documents that indicate user data field preferences. A set of target dataset attributes from a set of data use documents indicate user data scope preferences. A plurality of metadata sets for an associated plurality of datasets the computer determines having a field suitability value exceeding a predetermined suitability threshold value. The FSV represents a degree of similarity between a set of fields associated with said dataset and the set of target data fields. The computer assesses metadata sets with regard to the target attributes and generates a compared attribute score for each candidate dataset. A degree of likelihood is indicated that an associated dataset will have content exhibiting said target dataset attributes. The computer candidate datasets is based on the compared attribute score.

Abstract: An example system and method may provide an importance score for a data file based on the content of the data file. An importance score may be used to determine whether to store the data file in a regular reliability storage media or in a higher reliability storage media. A controller generates a document vector for a data file based on content processed from a data file. The data file includes metadata and the content. The controller generates, using an artificial intelligence (AI) model and the document vector, a data file importance score for the data file. The controller then stores the data file in one of the first data storage zone and the second data storage zone based on the data file importance score.

Abstract: A graph updating device includes: a K neighbor vertex search unit that searches for a K neighbor vertex set of an added vertex in a neighbor graph on the basis of the neighbor graph and an object added to the neighbor graph as an added vertex and outputs the K neighbor vertex set; a vertex selection unit that selects a vertex candidate set on the basis of the neighbor graph, the added vertex, and the K neighbor vertex set of the added vertex and outputs the vertex candidate set, the vertex candidate set being a set of vertices that is present in the neighbor graph and possibly contains the added vertex in a K neighbor vertex set thereof; and a neighbor graph updating unit that reconstructs a K neighbor vertex set related to all vertices of the neighbor graph using K neighbor vertex sets of respective vertices of the vertex candidate set and adds the K neighbor vertex set of the added vertex to the reconstructed K neighbor vertex set to generate an updated neighbor graph.

Abstract: A server system may include one or more hardware processors that execute computer-readable instructions from a non-transitory memory that cause the processor to receive a time component associated with a query request and one or more relational identification tags associated with a subset of a plurality of data items stored in one or more databases. The processor may then query the one or more databases to identify one or more time series data items based on the time component and the relational identification tags. After querying the databases, the processor may transmit the one or more time series data items to a computing device configured to display the one or more time series data items.

Abstract: Data items are aggregated in a quantile sketch according to a compactor hierarchy. A first number of data items are stored in a first buffer corresponding to a first (i.e., lowest) compaction level of the compactor hierarchy, and a top level number of data items are stored in a top buffer corresponding to a top compaction level of the compactor hierarchy. For a first subset of the first number of data items, each data item is already stored in the top buffer, and a weight of the respective data item stored in the top buffer is increased by 1. For a second subset of the first number of data items, each data item does not match any data item stored in the top buffer, and a second number of data items are selected from the second subset and stored in a second buffer of a second compaction level.

Abstract: A computer-implemented method includes writing a plurality of change records to a first set of redo records in a first transaction log file. The computer-implemented method further includes determining, while writing a change record to a redo record, that the change record includes changes made to data associated with an in-scope table. The computer-implemented method further includes updating the first transaction log file with information indicating that the redo record includes changes made to data associated with the in-scope table. The computer-implemented method further includes accessing the first transaction log file from storage in response to receiving a request for replicating changes made to data associated with in-scope tables. The computer-implemented method further includes scraping a first redo record in the first transaction log file in response to determining that the first redo record includes at least one change record associated with the in-scope table.

Abstract: Novel tools and techniques are provided for implementing tracking or storing of equipment configuration data using immutable ledger functionality of blockchains. In various embodiments, in response to receiving a first request for first configuration data that is output by first equipment, a computing system might determine whether a communicatively coupled data repository contains the first configuration data. If so, the computing system might retrieve and send (to the requesting device) the first configuration data. If not, the computing system might send, to a blockchain system, a second request for identifying a blockchain containing a block containing the first configuration data.

Abstract: A storage system with garbage collection prioritizes data segments for garbage collection in the storage memory. Priority of each data segment relates to amount of processing device work for garbage collection of the data segment versus benefit relating to amount of dead data to be reclaimed by garbage collection of the data segment. Garbage collection is performed according to the priority of each data segment.

Abstract: A computer system comprises a logic system, and, operatively coupled to the logic system, a computer-memory system holding instructions that, when executed by the logic system, cause the computer system to: receive a token-behavior selection corresponding to a real-world asset to be tracked on a virtual ledger; receive a virtual-ledger architecture selection identifying a provider-defined architecture of the virtual ledger; construct a template for registration of a token class on the virtual ledger according to the provider-defined architecture of the virtual ledger, wherein each new token instantiated from the token class exhibits a set of behaviors determined by the token-behavior selection; and provide access to the template to a client computer device.

Abstract: A system and method provides information to a user about other users who have shown an interest in the user or in whom the user shows an interest, or other users in whom the user has shown disinterest or other users who have shown disinterest in the user, as indicated by actions performed with respect to a website or other Internet-accessible repository of data.

Abstract: A method of updating a server knowledge graph, is performed by a server and includes obtaining a server knowledge graph of the server, and obtaining a plurality of device knowledge graphs by receiving a device knowledge graph from each of a plurality of devices. The method further includes generating a knowledge graph for server knowledge graph extension, based on the obtained plurality of device knowledge graphs, and updating the obtained server knowledge graph, using the generated knowledge graph for server knowledge graph extension.