Abstract: Methods and apparatus are disclosed for representing a dynamic hierarchical system as a composite graph data structure. Members of a system are represented as primary nodes of a tree. Multiple system states have respective trees, which can be overlaid to obtain a composite graph. The composite graph can be augmented with secondary nodes for member attributes, and further nodes for state-dependent values of the attributes. Methods of processing bottom-up, top-down, and filtered queries are disclosed. Applications to military, manufacturing, and communication networks are provided.

Abstract: An improvement of the functionality of a computerized automatic recommendation engine is provided. In particular, a method for identifying uncertain classifications made by a computerized recommendation engine through the utilization of historical solution data, such that they can be flagged for subsequent human review, thereby improving the training process for the recommendation engine, is disclosed.

Abstract: Some embodiments relate generally to the processing of compressed multidimensional data and selection of engagement rules based on the compressed multidimensional data. In some embodiments, a method includes retrieving, via a processor, a multidimensional data profile that includes a set of first inclination distributions, each associated with a data dimension. The processor matches a first set of engagement rules to the multidimensional data profile to define a matched set, each engagement rule of the first set of engagement rules having a corresponding confidence level and a corresponding set of second inclination distributions. The processor selects an engagement rule from the matched set that has a corresponding confidence level no less than a corresponding confidence level for each remaining engagement rule from the matched set, and sends a signal causing display of a stimulus to a user according to the selected engagement rule and not according to the remaining engagement rules.

Abstract: A first copy of a database object may be constructed prior to applying a designated database update request to a first database. The database object may be represented by a plurality of database table rows in the first database, and the request may update one or more of the plurality of rows. The request may be applied to the first database to update the one or more of the plurality of rows in the first database. A second copy of the database object may be constructed after applying the database update request to the first database. A message identifying a difference between the first copy of the database object and a second copy of the database object may be transmitted to a remote computing device.

Abstract: A query referencing an external table function provided by a remote software component is received. Requests to execute the external table function on input data are sent to a proxy service. A first request includes a batch of input rows from the input data. A first response to the first request received from the proxy service includes a first portion of result data and a pagination token. The pagination token indicates that at least a second portion of the result data corresponding to the first batch of input rows is to be obtained from the remote software component. Based on the pagination token, a second request is sent to obtain the second portion of the result data. One or more responses are received from the proxy service that comprise at least the second portion of the result data. The result data is processed according to the query.

Abstract: The subject technology receives raw input data from a source table, the raw input data including data comprising input features for a machine learning model, the raw input data being in a first format including at least multiple rows with each row including multiple columns of values. Based at least in part on the source table, the subject technology generates table metadata corresponding to the source table. Based at least in part on the received raw input data, the subject technology generates column metadata corresponding to values from the source table. The subject technology generates cell data for a feature store table based at least in part on the values from the source table. The subject technology performs at least one database operation to generate the feature store table including at least the generated table metadata, the generated column metadata, and the generated cell data.

Abstract: One example method includes receiving a set of filesystem parameters, creating a simulated filesystem based on the filesystem parameters, receiving a set of target characteristics for a file collection, based on the target characteristics, slicing a datastream into a grouping of data slices, populating the simulated files with the data slices to create the file collection and forward or reverse morphing the file collection from one generation to another without rewriting the entire file collection.

Abstract: Provided are a doubleheader logging methods of a slotted page and a database apparatuses. The method of doubleheader logging of a slotted page performed by a database apparatus includes determining a valid slot header among a first slot header and a second slot header of a page to select a slot header; selecting a valid slot header according to the determination result; and performing a transaction based on the selected valid slot header.

Abstract: Methods and systems are disclosed for receiving a sequential federated query; deconstructing the sequential federated query into query elements; identifying a Transactional-Unstructured Data Source (TUDS), a Contextual-Characteristic Data Source (CCDS), and a data organization parameter based on the query elements; generating a TUDS result data set from the TUDS based on the parameter; processing the TUDS result data set and the parameter to develop a CCDS query; generating a CCDS result data set from the CCDS based on the developed CCDS query and the parameter; generating a final sequential federated query data set based on the CCDS result data set and the parameters; processing a formatted sequential federated query data set based on the processing of the final sequential federated query data set and the parameter; and providing the formatted sequential federated query data set to a management system for action.

Abstract: A method of generating search results, comprising; receiving, by a computing system, an instruction to generate search results relating to a SKU stored in a database; extracting, by the computing system, a context based on information relating to the SKU; generating, by the computing system, a dynamic search string, by: generating a key based on the instruction; identifying a dictionary based on the context, the dictionary containing a plurality of dictionary term; and generating the dynamic search string by determining the dictionary term corresponding to the key; searching, by the computing system, using the dynamic search string, in content data; returning results from the content data matching the dynamic search string; and generating for display on a client device, the results.

Abstract: An example operation includes one or more of receiving a request associated with a software library, identifying metadata of the software library, determining, via chaincode, whether data of the software library has been previously stored on a blockchain, and in response to a determination that the software library has not been previously stored, storing the identified metadata of the software library and a notarization value generated by the chaincode within the blockchain.

Abstract: Provided is a method of truncating one or more blocks in a blockchain (300) by an aging process executed by participating computer node (501, 502) of the blockchain. The method includes truncating one or more blocks (310, 320) with a time stamp (210) that is older than a pre-determined cut-off time (t1) by the computer node; creating a new block (360) in which one or more data packets of the new block capture essential data (312, 320) of blocks that are truncated; and appending the new block to the blockchain.

Abstract: A data aggregation system for aggregation of data from at least two data sources includes: a data aggregation unit configured to determine a data aggregation action to be executed by the system, in response to a message received by at least one data source device, each message comprising data; a consistency checking unit configured to check the consistency of each message received from a data source device using one or more consistency rules and determine an action to be executed by said data aggregation unit depending on the consistency checking; and an accuracy metric determination unit configured to determine an accuracy metric for the executed action based on feedback values received from a set of at least one user device, said data aggregation unit comprising a rule updating unit configured to update said consistency rules based on the accuracy metrics determined for the executed actions.

Abstract: An example operation may include one or more of identifying a caller blockchain node and one or more callee blockchain nodes within a blockchain network and issuing, by the caller blockchain node, application programming interface calls to application programming interfaces corresponding to each of the one or more callee nodes, in response to a first application programming interface call being issued successfully, directing a smart contract associated with the caller blockchain node to initiate a distributed transaction involving the one or more callee nodes to perform the application program interface calls, the caller node issues application programming interface calls and the one or more callee nodes each performing application programming interface requests.

Abstract: Systems and methods for processing out of order data incrementally are provided. A database is maintained containing rows of data, each row of data having a timestamp and pertaining to a transaction, for example in the e-commerce platform. New data for new rows of data is received. At least some of the data is out of order. Each new row of data is processed in the same manner irrespective of whether the row is out of order or in order using a computation graph including at least one execution node configured to perform out-of-order incremental processing. A processing result is output based on the processing, wherein the result is up to date based on data that has been received.

Abstract: A flexible tagging and searching system can be configured to associate tags with the input data to enable a search of the input data. The flexible tagging and searching system can receive user data and determine an identifier associated with the user data. The system can compare the identifier with other identifiers to determine that the identifier is unique. After determining that the identifier is unique, the system can associate a critical tag with the user data and store the critical tag in a database. Then the system can associate a non-critical tag with the user data. In some instances, the system can return query results such as a set of tag data and/or a set of data items.

Abstract: Technologies are described for performing automated data integration, reconciliation, and/or self-healing using machine learning. For example, data integration can be checked using a reconciliation procedure. The number of times that the reconciliation is performed can be determined dynamically by a machine learning model. For each iteration, reconciliation can be performed to check integrated data against source data. If any reconciliation errors are found, then self-healing operations can be performed. Results of the reconciliation can be output. The reconciliation results can be used to update the machine learning model so that the machine learning model can dynamically adjust the number of iterations to perform based at least in part on reconciliation results.

Abstract: Aspects of a data environment, such as the creation, provisioning, and management of data stores and instances, are managed using a separate control environment. A user can call into an externally-facing interface of the control environment, the call being analyzed to determine actions to be performed in the data environment. A monitoring component of the control plane also can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events in the data environment. A workflow can be instantiated that includes tasks necessary to perform the action. For each task, state information can be passed to a component in the data environment operable to perform the task, until all tasks for an action are completed. Data in the data environment can be accessed directly using an externally-facing interface of the data environment, without accessing the control plane.

Abstract: The purpose of the present invention is to provide a technology which assists a verifying party in ascertaining an anomaly in an event of which notification has been made. Provided is an assistance device, comprising: an acquisition unit which acquires as an associated event, from among events which take place among a plurality of elements, and with respect to elements which have been associated with an event which has been detected as an anomalous event, an event other than the anomalous event which has been associated with the elements; and a generating unit which, on the basis of the anomalous event and the associated event, generates a relational graph in which the elements are vertices, the relations among the elements are edges, the anomalous event and the associated event are respectively represented, and the associated event is displayed in a display screen in a different manner from the manner in which the anomalous event is displayed.

Abstract: Examples of a record generation system are provided. The system may receive a record generation requirement from a user. The system may obtain record data, a plurality of user documents, and identify a record corpus from the record data. The system may sort the record data into a plurality of data domains. The system may determine at least one record mapping context including a record value from the plurality of user documents. The system may determine a selection rule from the plurality of data domains for each of the record mapping context. The system may create a record index corresponding to the plurality of user documents. The system may create a record generation model corresponding to the record generation requirement based on the record index. The system may generate a record generation result corresponding to the record generation requirement comprising the relevant record generation model.