Abstract: The present disclosure provides techniques and solutions for integrating data from different instances of a data source, such as a data artifact. That is, in some cases data may be disjoint, or it may overlap in whole or part. How data should be integrated can depend on whether data overlaps, or a type or extent of overlap. An artifact that consumes data can be integrated to indicate how data from underlying instances of a data source should be integrated, including when this consuming artifact requests data indirectly from a consolidation artifact. A search against the consuming artifact can be modified based on configuration information in the consuming artifact indicating how or if data from multiple instances of the data source should be integrated.

Abstract: Techniques and solutions are provided for grouping of landscape elements, such as instances of software applications or application content. Landscape elements of the same or different types can be included in groups, where the groups can also be used to exclude other landscape elements from a group. In one implementation, a consolidation landscape element can be generated to consolidate content of two or more landscape elements in a group, and having a same type. In another implementation, grouping of landscape elements can be used to control the installation of cross-type content. In a given landscape, grouping can be used to control either of both of the generation of consolidation landscape elements or the installation of cross-type content.

Abstract: Techniques and solutions are described that can be used to determine data subsets of a data set that may be responsive to a query. In one aspect, imprints are created for the data subsets, where an imprint indicates whether, for a plurality of bins, a data subset contains values within respective bins. The bins are defined at least in part using data for a set of queries. In another aspect, at least one bin of a plurality of bins is designated to be associated with values of the data set satisfying a threshold frequency. In a further aspect, imprints are created for a plurality of bins, where an imprint indicates whether the plurality of data subsets comprise a value for a given bin. A query imprint can be compared with the data subset imprints or bin imprints to determine data subsets that may be responsive to an associated query.

Abstract: Techniques for implementing artificial crowd intelligence via networking of recommendation engines are disclosed. In some example embodiments, a base recommendation engine performs a computer-implemented method comprising: receiving a recommendation request; generating a first plurality of recommendations based on the recommendation request using a base recommendation model; obtaining one or more other recommendations from one or more other recommendation engines, each one of the other recommendation engines being configured to generate the other recommendations based on the recommendation request using a corresponding recommendation model; obtaining a corresponding weight for the other recommendation engine(s); selecting at least one recommendation from the first plurality of recommendations and the other recommendation(s) using the corresponding weight(s); and causing the selected recommendation(s) to be displayed.

Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.

Abstract: A system and method of managing highly-volatile statistics of a multi-threaded application environment. The statistics are represented by one or more statistics objects. Each statistics object of the one or more statistics objects is prefixed with an object header having a version counter with an initial version count of zero. Each statistics object is associated with a statistics class instance, each statistics class instance being associated with an associative registry that is configured to allocate smallest possible objects of a size equal to or greater than to that of the statistics objects, the registry segmenting the statistics objects according to a size class. Each allocated statistics object is constructed in the object frame after the object header. Then, the object header of each allocated statistics object is initialized. Once allocated, objects can be deallocated.

Abstract: Embodiments detect malicious code in distributed software components. A detector element references a source code repository (e.g., open source, commercial) containing lines of various files of a distributed artifact. Subject to certain possible optimizations, the detector inspects the individual files and lines of the artifact file-by-file and line-by-line, to identify whether any commit history information is available from a Versioning Control System (VCS). A risk assessor element receives from the detector element, results identifying those lines and/or files for which no VCS commit history is available. The risk assessor then references code features (e.g., file extension, security-critical API calls) in the results, to generate a probability of the malicious nature of the source code lacking VCS commit history information. An analysis report including this probability and additional relevant information, is offered to a user to conduct further manual review (e.g.

Abstract: Disclosed herein are system, method, and computer program product embodiments for automatically generating events. In some embodiments, a server receives a request to subscribe to an event type for an application. The server identifies an entity in a data model corresponding to the event type. The entity is associated with application data of the application. Furthermore, the server subscribes to receive alerts associated with any change to the entity in the data model. The server receives an alert indicating a change to the entity in the data model. The alert includes the change to the entity. Moreover, the server generates an event corresponding to the event type based on the change to the entity and transmits the event to an event infrastructure.

Abstract: In an example embodiment, a solution is provided to build a generic service failover framework that can be packaged as a library and implemented by many different microservices, whether on-premises or in the cloud. Each application can implement/add/hook this service to obtain the benefits of handling failover gracefully, as well as coming with some customizable options to provide a complete failover framework.

Abstract: The disclosure relates to a computed-implemented method, a computer program, and a computer system for selectively verifying personal data. The method comprises receiving, by an identity application of a client device, personal data of a user. The method further comprises computing, via a cryptographic hash function, one or more cryptographic hashes from elements of the personal data. The method further comprises storing the cryptographic hashes, an internal identifier and a timestamp as an entry in a distributed database. The internal identifier is unique within the distributed database. The method further comprises receiving a user request from the user. The method further comprises selecting one or more of the elements of personal data for verification. The method further comprises requesting verification of the selected elements of personal data. The method further comprises determining an authorization indication in response to the verification request.

Abstract: In some implementations, there is provided a method that includes detecting a first database table at a first database instance and a second database table at a second database instance, the first database table and the second database table both including a set of data, the set of data being a same data for both the first database table and the second database table; in response to the detecting, deploying the second database table, such that the second database table comprises a virtual table linked to the set of data of the first database table; and deploying a first trigger and/or a second trigger to detect whether a request is received to perform a change to the set of data at the first database table at the first database instance and/or the second database table at the second database instance. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: Various examples are directed to systems and methods for processing queries against a process model. An analytics computing system may access query data describing a query to an analytics computing system. The analytics computing system may access process model code that comprises first function code for evaluating a function having a first input and a second input. The first function code may indicate that the first input is at a first time context corresponding to a first discrete time. And that the second input is at a second time context corresponding to a second discrete time period adjacent the first discrete time period. The analytics computing system may execute the process model code using a value for a first input at the first discrete time period and a value for a second input at the second discrete time period.

Abstract: The present disclosure involves systems, software, and computer implemented methods for proactively predicting demand based on sparse transaction data. One example method includes receiving a request to predict transaction dates for a plurality of transaction entities for a future time period. Historical transaction data for the transaction entities is identified for a plurality of categories of transacted items. The plurality of categories are organized using a hierarchy of levels. Multiple levels of the hierarchy are iterated over, starting at a lowest level. For each current level in the iteration, a plurality of transaction date prediction models are trained and tested. Heuristics for the plurality of trained transaction date prediction models are compared to determine a most accurate transaction date prediction model. The most accurate transaction date prediction model is used to make a prediction of transaction dates for the current level for the future time period.

Abstract: An in-memory database server hosting a tenant of a multi-tenant software architecture can receive a definition of a custom data field that is unique to an organization having isolated access to the tenant. The custom data field can extend a standard table defined by central metadata stored at a system tenant of the multi-tenant software architecture. Tenant private metadata that includes the definition can be stored in memory accessible only to the tenant. A tenant-dependent table that includes the custom data field can be formed, for example by retrieving central metadata defining the standard table from the system tenant and adding the custom data field using the definition. The tenant-dependent table can be presented for access via a database client at the organization. Related systems, articles of manufacture, and computer-implemented methods are disclosed.

Abstract: In some example embodiments, there may be provided a method that includes receiving a machine learning model provided by a central server configured to provide federated learning; receiving first audio data obtained from at least one audio sensor monitoring at least one machine located at the first edge node; training, based on the first audio data, the machine learning model; providing parameter information to the central server in order to enable the federated learning among a plurality of edge nodes; receiving an aggregate machine learning model provided by the central server; detecting an anomalous state of the at least one machine. Related systems, methods, and articles of manufacture are also described.

Abstract: In an example embodiment, a first function is performed on the first document received at first middleware management architecture, causing a change in the status of the first document. The change is logged in a record corresponding to the first document in a memory. Then the first document is sent to a second network via a transmission protocol layer. A notification of a change in the status of the first document within the second layer is received in a layer other than the transmission protocol layer, from the second network. The change in the second network is logged in the record corresponding to the first document in the memory. Information corresponding to the change in the status of the first document at the middleware management architecture and the change in the status of the first document in the second network is reported to the first network.

Abstract: Disclosed herein are system, method, and computer program product embodiments for utilizing an extended cache to access an object store efficiently. An embodiment operates by executing a database transaction, thereby causing pages to be written from a buffer cache to an extended cache and to an object store. The embodiment determines a transaction type of the database transaction. The transaction type can a read-only transaction or an update transaction. The embodiment determines a phase of the database transaction based on the determined transaction type. The phase can be an execution phase or a commit phase. The embodiment then applies a caching policy to the extended cache for the evicted pages based on the determined transaction type of the database transaction and the determined phase of the database transaction.

Abstract: Disclosed herein are various embodiments of a location data processing system. An embodiment operates by configuring a column of a table to store location-based data across a plurality of different coordinate systems. The location-based data to be stored in the configured column is received. The received location-based data is divided into a plurality of fragments, including a first fragment comprising a plurality of data entries. A first data entry in the first fragment includes a coordinate specification including metadata indicating how to evaluate corresponding location-based data of a first coordinate system represented by the first data entry. A query for data from the first fragment is received. The plurality of data entries of the first fragment are evaluated based on the coordinate specification to identify data that satisfies the query. The data is returned responsive to the query.

Abstract: The present disclosure involves systems, software, and computer implemented methods for database integration with an external key management system. One example method includes receiving, by a database system, a key encryption key from an external key management system external to the database system that is used to encrypt a data encryption key used to encrypt database data. The data encryption key is obtained, by the database system, using the key encryption key. Encrypted database data is decrypted, by the database system and using the data encryption key, to obtain decrypted database data before performing an operation on the decrypted database data. The database system determines that the external key management system has performed an operation on the key encryption key. In response to determining that the external key management system has performed the operation on the key encryption key, the database system modifies operation of the database system.

Abstract: Disclosed herein are various embodiments for pronoun-based natural language processing. An embodiment operates by receiving a plurality of text-based sentences each comprising a plurality of words, and each text-based sentence including a pronoun. A plurality of candidate nouns are identified amongst the plurality of words. A trigger word is identified from the plurality of words, wherein the trigger word is associated with both the pronoun and one of the plurality of candidate nouns. A score for each of the candidate nouns is received based on a relationship with the trigger word. The candidate noun with a highest score is selected as being associated with the pronoun.