Abstract: The present invention generally relates to systems and methods for providing an enterprise user with an electronic identity and an electronic mailbox when the user has denied, degraded, intermittent, or latent network connectivity. In aspects, a database limited to a single user containing the user's electronic identity and electronic mailbox is provided. The single user database is replicated using a multi-master replication scheme across the cloud and on-premises servers. When a user is entering an environment with denied, degraded, intermittent, or latent network connectivity (“DDIL”), the single user database is replicated to a DDIL server. The user is provided access to their electronic identity and electronic mailbox in the single-user database via the DDIL server during periods of denied, degraded, intermittent, or latent network connectivity.

Abstract: A type restriction contextually modifies an existing type descriptor. The type restriction is imposed on a data structure to restrict the values that are assumable by the data structure. The type restriction does not cancel or otherwise override the effect of the existing type descriptor on the data structure. Rather the type restriction may declare that a value of the data structure's type is forbidden for the data structure. Additionally or alternatively, the type restriction may declare that an element count allowable for a data structure's type is forbidden for the data structure. Type restriction allows optionality (where only a singleton value for a data structure is allowed), empty sets (where no value for a data structure is allowed), and multiplicity (where only a limited element count for a data structure) to be injected into a code set independent of data type. Type restriction allows certain optimizations to be performed.

Abstract: Provided is a system that includes at least one processor programmed or configured to receive an XML data file, wherein the XML data file includes data associated with one or more input parameters of a machine learning model, generate a code generation template based on the data associated with one or more input parameters of the machine learning model included in the XML file, where the code generation template includes one or more keys associated with one or more parameters of a transaction aggregate for an account of a user, and generate a file of executable code based on the code generation template, wherein the file of executable code includes instructions that, when executed by at least one processor, causes at least one processor to retrieve transaction aggregate data associated with the transaction aggregate for the account of the user. A method and computer program product are also provided.

Abstract: A storage control system receives a request to access target data and searches a primary metadata structure to find an associated metadata entry. The primary metadata structure comprises a log-structured merge tree comprising a first level of segments which comprises a group of segments having an associated group filter, and individual filters associated with respective segments of the group of segments. The storage control system searches the primary metadata structure by performing a lookup operation using the group filter to determine whether the associated metadata entry is potentially present in a given segment of the group of segments, and performing a lookup operation using the individual filters to identify the given segment of the group of segments which potentially includes the metadata entry, when the metadata entry is determined to be potentially present in a given segment of group of segments, using the group filter.

Abstract: A method for distributed tokenization of sensitive strings of characters, such as social security numbers, credit card numbers and the like, in a local server is disclosed. The method comprises the steps of receiving from a central server at least one, and preferably at least two, static token lookup tables, and receiving a sensitive string of characters. In a first tokenization step, a first sub string of characters is substituted with a corresponding first token from the token lookup table(s) to form a first tokenized string of characters, wherein the first sub string of characters is a substring of the sensitive string of characters. Thereafter, in a second step of tokenization, a second sub string of characters is substituted with a corresponding second token from the token lookup table(s) to form a second tokenized string of characters, wherein the second substring of characters is a substring of the first tokenized string of characters. Optionally, one or more additional tokenization steps is/are used.

Abstract: A method for providing dietary recommendation for a subject includes acquiring a dietary target for the subject, acquiring data associated with dietary consumption of the subject, and determining a balance score based on the acquired dietary target and the acquired data associated with dietary consumption of the subject. The method further includes acquiring a plurality of meal options for the subject, where each of the plurality of meal options is representative of a suggested meal, determining a salience score for each of the plurality of meal options, where the determination is based on the dietary target, dietary information of the respective meal option, and the determined balance score, and generating a personalized dietary recommendation for the subject based on at least one of the determined salience scores.

Abstract: A data acquisition apparatus (200) comprises a processing resource operably coupled to an input unit (204) and an output unit (206). The processing resource (202) is arranged to provide an execution environment for supporting a user interface. An enquiry module (268) is provided and supported by the execution environment. The apparatus (200) also comprises a communications unit (166, 168) operably coupled to the processing resource for supporting communications over a communications network. The enquiry module (268) is arranged to generate (410) a search query relating to a point of interest and receive search results in response thereto via the communications unit (166, 168), the enquiry module (268) also being arranged to use the search results to derive data associated with the point of interest.

Abstract: An information processing apparatus according to an embodiment includes: a common data model management unit that manages information indicating a common data model corresponding to a plurality of modules in common; a unique data model management unit that manages information indicating a unique data model corresponding to at least one of the modules; and a common management unit that manages a version of a module corresponding to the common data model managed by the common data model management unit, a version of a module corresponding to the unique data model managed by the unique data model management unit, and a version of a module corresponding to a newly installed data model, and verifies compatibility of the versions.

Abstract: A method of updating a data set using event-based conditions includes adding a first data point to the data set and triggering a first event indicating that the data set has changed. Adding the first data point to the data set triggers the first event. The method also includes, in response to the first event, updating conditions for completing the data set. The conditions are associated with action pathways for receiving or verifying missing data points in the data set. The method further includes triggering a second event indicating that the conditions for completing the data set have changed and, in response to the second event, distributing the conditions to a plurality of distributed services. Each of the plurality of distributed services is configured to execute one or more of the action pathways for receiving or verifying the missing data points in the data set.

Abstract: Disclosed are techniques for relational database locks based on columns. Database transactions may be targeted to specific columns of one or more records, instead of the entire row for those records, using primary keys. Column locks on specific keys are stored separately than column locks on ranges of keys, which are both checked when requesting a new column lock for either a single key or a range of keys. When a threshold number of columns for a given record, or range of records/keys, have been locked, the column locks for that record, or range of records, can be combined into a single row level lock to reduce resource costs for maintaining multiple concurrent locks.

Abstract: A payment service system monitors data associated with a dynamic information feed and determines trending causes based on the monitoring. The system accesses user information associated with a user and identifies a trending cause that is relevant to the user based on the user information. The system transmits, to the user's mobile device, a recommendation alert that is formatted based on a local application on the user's mobile device, and causes the user's mobile device to surface the recommendation alert to recommend the relevant trending cause within the local application. The system receives an indication of an interaction with the recommendation alert via the user's mobile device. In response, the system facilitates a transfer of at least one asset from an account associated with the user to at least one account associated with at least one recipient entity associated with the relevant trending cause according to a specified distribution.

Abstract: An apparatus, computer-readable medium, and computer-implemented method for efficiently classifying a data object, including representing the data object as a data object vector in a vector space, each dimension of the data object vector corresponding to a different feature of the data object, determining a distance between the data object vector and centroids of data domain clusters in the vector space, each data domain cluster comprising data domain vectors representing data domains, sorting the data domain clusters according to their respective distances to the data object vector, and iteratively applying data domain classifiers corresponding to data domains represented in a closest data domain cluster in the sorted data domain clusters to the data object.

Abstract: In one embodiment, a method includes obtaining candidate data generated by a vehicle. The candidate data comprises a subset of sensor data identified based on a set of neural network models executing on the vehicle. The method also includes determining whether the candidate data can be associated with one or more categories of a set of categories for training data based on a set of categorization models. The method further includes associating the candidate data with the first category in response to determining that the candidate data can be associated with at a first category of the set of categories. The method further includes determining whether the candidate data can be associated with a second category. The set of categories lacks the second category. The method further includes including the second category in the set of categories in response to determining that the candidate data can be associated with the second category.

Abstract: An embodiment may involve, based on a profile associated with a client device, selecting an audio file containing music. Based on an attribute of the audio file containing the music, an audio file containing a story may be selected. A playlist for the client device may be generated, where the playlist includes (i) a reference to the audio file containing the music, and (ii) a reference to the audio file containing the story. A server device may transmit the playlist to the client device over a wide area network. Reception of the playlist at the client device may cause an audio player application to retrieve and play out each of the audio file containing the music and the audio file containing the story.

Abstract: Described are improved systems, computer program products, and methods for adaptively provisioning an ordered sequence in a clustered database environment. The approach includes identifying a cached list of sequence numbers. A request for one or more sequence numbers in a database environment may be received. A determination may be made to decide whether the request pertains to an ordered sequence. The one or more sequence numbers may be adaptively provisioned to fulfill the request based at least in part upon an independent cache implementation or upon a shared cache implementation.

Abstract: Methods and systems for anomaly detection in relational databases. The methods and systems perform operations comprising: accessing a data object including a data set that has been collected over a given time interval; selecting a reference data point from the data set; computing an angle representing a data growth rate of the data set at least within the given time interval relative to the reference data point; determining that the angle representing the data growth rate of the data set within the given time interval exceeds a specified threshold; and in response to determining that the angle representing the data growth rate of the data set within the given time interval exceeds the specified threshold, triggering an anomaly detection operation.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for governing a set of information assets using an information governance system. The method includes one or more processors applying one or more high-level classification assignment rules to one or more information assets of the set of information assets. Furthermore, the method includes one or more processors applying one or more high-level classification propagation rules to the one or more information assets provided with the high-level classification assignments for propagating the respective high-level classification assignments upwards within a containment hierarchy formed by the set of information assets to one or more superordinate information assets of the set of information assets.

Abstract: Embodiments of the system in include a memory that stores a metamodel including a plurality of predefined characteristics for data sets. A data repository stores a plurality of heterogeneous data sets, each of the plurality of data sets comprising a plurality of data batches received over time. An interface receives a new data set for storage into the data repository, and data health reasoner to retrieve the stored metamodel from the memory, the stored metamodel including a plurality of predefined characteristics. The data health reasoner determines measured values of a subset of the plurality of predefined characteristics identified based on the stored metamodel, and determines a set of data health metrics for the data set based on the measured values of the subset of the set of the predefined characteristics. The data health reasoner formulates a plurality of data validation assertions for the data set and apply the plurality of data validation assertions to each instance of the data set.

Abstract: Enhanced filter accuracy is disclosed with respect to determining whether a data element is present in a data store. The filter can correspond to a probabilistic filter with multiple levels. At each level after a representation of an original data element is captured in a data structure, a predetermined modification can be applied to the data element and a representation of the resulting modified data element can be captured in the data structure. In query operation, a check be performed for the presence or absence of an input data element and a number of modifications of the input data element, which results in a reduced false positive probability and improved accuracy. A multidimensional data structure can also be employed in conjunction with multiple levels to further improve accuracy.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving a plurality of records associated with a first geographical area; identifying a plurality of corrections to a first attribute in the first geographical area in the plurality of records for a particular time period; based on identifying the plurality of corrections to the first attribute, computing a first metric representing a quantity of the plurality of corrections to the first attribute per effort during the particular time period; accumulating a first value representing a total number of errors across a plurality of time periods up to and including the particular time period based on the identified plurality of corrections; and generating a first model that predicts accuracy of the first attribute in the first geographical area based on the metric and the accumulated first value.