Abstract: Methods for page split detection and affinity in query processing pushdowns are performed by systems and devices. Page servers perform pushdown operations based on specific, and specifically formatted or generated, information, instructions, and data provided thereto from a compute node. Page servers also determine that page splits have occurred during reading of data pages maintained by page servers during pushdown operations, and also during fulfillment of compute node data requests. To detect a data page has split, page servers utilize information from a compute node of an expected next data page which is compared to a next data page in the page server page index. A mismatch in the comparison by page servers indicates data page was split. Compute nodes and page servers store and maintain off-row data generated during data operations via page affinity considerations where the off-row data is stored at the same page server as the data.

Abstract: A request to send a file is received. A file type for the file is identified. For example, the file type may a Joint Photographic Experts Group (JPEG) file or a Portable Document Format (PDF) file. In response to receiving the request to send the file and identifying the file type for the file, a format of the file is reordered. Reordering the format of the file is based on an application and/or an application type that will be receiving the file. For example, the application may be an Adobe Acrobat® reader that is receiving a PDF file that has been reordered for more efficient reading.

Abstract: One embodiment provides a method, including: receiving a query from a user; providing the query to data owners, wherein each of the data owners has a local machine learning model and wherein the plurality of data owners train a meta-model; secret sharing model output from the data owners between the other data owners, wherein the model output comprises an output responsive to the query computed using the local machine learning model; receiving, from each of the plurality of data owners, a set of meta-features corresponding to the query; and generating a response to the query, wherein the generating comprises determining, by evaluating the meta-model using the set of meta-features received from each of the plurality of data owners, weights for outputs from the local machine learning models and aggregating the outputs in view of the weights.

Abstract: A distributed database encrypts tables using table encryption keys protected by a client master encryption key. The client may revoke and subsequently restore authorization to access the client master encryption key. A sweeper process of the distributed database examines encrypted tables and identifies changes to the status of a corresponding client master encryption key. A response to an identified change in status is initiated.

Abstract: A centralized database management system performs data synchronization with lower bandwidth consumption and higher efficiency. The system manages data synchronization and data reconciliation across multiple databases managed by multiple DBMS across different client servers. The system generates and sends instructions that encode each data table into an invertible bloom filter and identifies differences between the two databases by performing a subtraction operation on the two invertible bloom filters. The system may generate a third invertible bloom filter comprising information associated with differences between the two data tables. The system may send instructions to the source and the destination databases, where a first and a second invertible bloom filters are encoded for the source and the destination databases, respectively. The system may decode the third invertible bloom filter, identify the different elements, and generate instructions to the source and/or the destination database.

Abstract: Bid values submitted for various keywords can take into account the recovery propensity between paid search and organic search. When submitting a bid to a search engine provider for a keyword, an entity may get a certain level of performance in return. If not submitting a bid, however, the entity will likely still get some level of performance, although likely less than for paid search. In order to optimize for a parameter such as impressions, purchases, or profit, the recovery propensity can be taken into account in order to adjust the bid price, taking into account the relative performance of paid and organic search and then optimizing for the determined goal. Organic search data in some embodiments can be obtained through testing or modeling, or a combination thereof.

Abstract: A seed value assigned to a database table is determined. Numerically ordered invocation numbers are determined. Unordered pseudorandom numbers are generated based on the seed value and the invocation numbers to index temporally ordered data changes to the database table. It is determined whether the total number of yet-to-be-saved pseudorandom numbers reaches a maximum total number threshold. If so, the yet-to-be-saved pseudorandom numbers and a sequence of corresponding invocation numbers are saved in a sync table.

Abstract: Apparatus and methods are provided for multiple smart glasses to enter in a distributed ledger network such as a blockchain to concurrently modify documents. These networked smart glasses may store the document and any changes made to the document in a distributed ledger, communicate the changes to the other smart glasses and request approval or disapproval of the changes. Each smart glass or user may approve or disapprove the changes suggested by other users. The document may only be finalized when all suggested changes are approved or disapproved.

Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

Abstract: Systems and methods for providing automated data governance are disclosed. The system may include a plurality of data environments, a metadata repository storing data attributes and classification requirements, a policy repository, one or more processors, and a memory in communication with the one or more processors storing instructions to execute steps of a method. The system may receive a first dataset from a first data environment having a first dataset ID. The system may transmit the dataset ID to the metadata repository and the metadata repository may return an indication that the first dataset includes at least one data attribute and at least one associated classification requirement. The system may transmit the classification requirement to the policy repository and receive classification code associated with the classification requirement. The system may modify the first dataset by transmitting instructions to the first data environment to execute the classification code.

Abstract: In some implementations, a monitoring device may receive configuration information associated with an extract, transform, load (ETL) pipeline that includes one or more data sources and one or more data sinks. The monitoring device may generate, based on the configuration information, lineage data related to a data flow from the one or more data sources to the one or more data sinks in the ETL pipeline. The monitoring device may generate one or more predicted quality metrics associated with the ETL pipeline using a machine learning model. The monitoring device may generate a visualization in which multiple nodes are arranged to indicate the data flow from the one or more data sources to the one or more data sinks and further in which the one or more predicted quality metrics are encoded within the visualization.

Abstract: An experience rating and skill discovery system (ERSDS) and a method for determining credibility of experience ratings provided by one or more reviewers and discovering skills of opportunity seekers based on a relationship between the reviewers and the opportunity seekers are provided. A skill profile module of the ERSDS reads profile data from a user profile list and generates a skills profile list. An invitation module transmits invitations to reviewer devices for providing the experience ratings.

Abstract: A method to dynamically switch between catalog sharing protocols includes monitoring, over a period of time, access to a catalog used to index data sets. Using information gathered during this monitoring period, the method divides the period of time into intervals based on which of a plurality of sharing protocols, used to access the catalog, would provide the best performance during the respective interval. The method schedules the sharing protocols to operate during their respective intervals going forward, and switches between the sharing protocols in accordance with the schedule. In certain embodiments, switching between the sharing protocols includes temporarily operating in a hybrid mode in which multiple sharing protocols operate simultaneously. When using this hybrid mode, the switch may occur when one sharing protocol begins to perform better than the other. A corresponding system and computer program product are also disclosed.

Abstract: The present system and method relate to an automated crawler for crawling a primary online content object and storing a set of results, a parser for parsing the stored set of results to generate a plurality of key phrases and a content corpus, a plurality of models for processing at least one of the plurality of key phrases or the content corpus, wherein the processing results in a plurality of topic clusters which arrange topics within the primary online content object around a core topic based on semantic similarity, a suggestion generator for generating a suggested topic that is similar to at least one topic among the plurality of topic clusters and for storing the suggested topic, and an application for developing a strategy for development of online presence content.

Abstract: Systems and methods are described herein that address the shortcomings in conventional systems via a novel technique for utilizing a social interactions and knowledge about social connections to facilitate the exchange of information from a source of the information to a consumer of the information. For example, a consumer of information may be any individual or entity seeking information. A provider of information may be any entity or individual that may provide the information sought by the consumer. As provided herein, the systems identify providers that may most efficiently provide accurate information to the consumer without requiring the consumer to waste time reviewing irrelevant information.

Abstract: A method and system for engramic indexing of information technology (IT) infrastructure. Specifically, the method and system disclosed herein enable the efficient access, search, and/or management of enterprise-scale IT infrastructure and topologies using semantic context and natural language processing. That is, query context may be optimized using mapped semantics based on organizational constructs and machine learning, thereby reducing query overhead, increasing response performance, and improving contextual display capabilities in mass-scale environments.

Abstract: A method includes encoding data in accordance with a width parameter to produce a first set of data slices. Storage of the first set of data slices is maintained in a set of storage units of a storage pool. An expanded set of storage units of the storage pool is determined based on an additional subset of storage units added to the storage pool. Storage of the first set of data slices is maintained in the set of storage units after addition of the additional subset of storage units added to the storage pool. An updated width parameter is determined by increasing the width parameter based on the expanded set of storage units. The data is encoded in accordance with the updated width parameter to produce a second set of data slices. Storage of the second set of data slices is maintained in the expanded set of storage units.

Abstract: A method for validating a query result for a query of a database uses an index of the database. A selection of a set of source data from the database is received and a first hash operation is performed on the source data in the database resulting in a database hash value for the source data. A second hash operation is performed on the source data in the index resulting in an index hash value. The index hash value is compared with the database hash value, and a guarantee indication is provided for the source data in the index.

Abstract: The present invention discloses an efficient storage method for time-series data, comprising: storing time-series data collected by each data sampler and static attribute data of its data sampler separately; when each time series is stored, based on a unique ID of each time series, storing corresponding time-series data; and when the static attribute data is stored, the static attribute data are stored in another database independently, wherein each data sampler saves one corresponding record in a database storing the static attribute data. According to the present invention, the storage space can be saved, the processing efficiency and the processing speed can be improved, and the query processing can be flexibly carried out.

Abstract: A high-performance distributed ledger and transaction computing network fabric over which large numbers of transactions (involving the transformation, conversion or transfer of information or value) are processed concurrently in a scalable, reliable, secure and efficient manner. In one embodiment, the computing network fabric or “core” is configured to support a distributed blockchain network that organizes data in a manner that allows communication, processing and storage of blocks of the chain to be performed concurrently, with little synchronization, at very high performance and low latency, even when the transactions themselves originate from distant sources. This data organization relies on segmenting a transaction space within autonomous but cooperating computing nodes that are configured as a processing mesh. Each computing node typically is functionally-equivalent to all other nodes in the core.