Patent classifications
G06F16/258
GEOLOCATION NAME SYSTEM
A system and method for representing physical coordinates related to an address in machine-readable format. The disclosed invention provides a method for assigning an identifier to a set of geographical coordinates, such that said identifier may be used to share location information in lieu of a regular address (street name, city, state, etc.). The disclosed invention further allows said identifier to be correlated to additional information related to the address, such as altitude, in order to more accurately point a user to the desired location by only using the assigned identifier.
MACHINE LEARNING TECHNIQUES FOR SCHEMA MAPPING
Techniques are disclosed for generating a database schema using trained machine learning models that, in some embodiments, may include graph neural networks (GNN). A GNN may identify source to target database schema mappings using, among other features of the graph, context data associated with each node in a graph. Context data describes relationships between a particular node and some (or all) of the other nodes in the graph. The system may use this context data (and other graph data) in combination with a trained GNN model to identify a mapping between one or more source database entities to corresponding target database entities.
FEDERATED SEARCH OF MULTIPLE SOURCES WITH CONFLICT RESOLUTION
Methods and apparatuses related to federated search of multiple sources with conflict resolution are disclosed. A method may comprise obtaining a set of data ontologies (e.g., types, properties, and links) associated with a plurality of heterogeneous data sources; receiving a selection of a graph comprising a plurality of graph nodes connected by one or more graph edges; and transforming the graph into one or more search queries across the plurality of heterogeneous data sources. A method may comprise obtaining a first data object as a result of executing a first search query across a plurality of heterogeneous data sources; resolving, based on one or more resolution rules, at least the first data object with a repository data object; deduplicating data associated with at least the first data object and the repository data object prior to storing the deduplicated data in a repository that has a particular data model.
CLIENT DEVICES AND DATA STORAGE SERVER FOR SELECTIVE STORING OF DATA
A client device for storing a data set in a database is provided. The data set includes a plurality of initial data elements. The client device is configured to determine a storage location of the database for each initial data element and to obtain storage location configuration information based on the storage location. The client device is further configured to process, based on the storage location configuration information, each initial data element of a first subset of the plurality of initial data elements into a processed data element using one or more data processing operations and to transmit a modified data set to a data storage server for storing the modified data set in the database, wherein the modified data set comprises the processed data elements in the first subset and unprocessed initial data elements in a second subset which is complementary to the first subset.
Methods, Systems and Computer Program Products for Handling Data Records Using an Application Programming Interface (API) and Directory Management System
An application programming interface (API) resident on a computer is provided that, upon receiving a message that a data set associated with an encounter experienced by a subject is available, causes a processor to read a structured file associated with the data set, the structured file having a set of records assigned to a subset of pre-defined fields and a location of one or more unstructured objects, the pre-defined fields being organized according to an ontology having at least records related to the subject, the encounter and the data set; and populate at least first and second independent and distinct relational databases using endpoints of the API. The first relational database excludes records associated with the subject and the encounter and the second relational database includes records associated with the subject and the encounter. The second relational database includes multiple tables that can be accessed by invoking the API.
Language-agnostic graph-based combinatorial application framework
A computer-implemented schema-independent method of modeling data from diverse sources is described. A server transmits to a client computer a blueprint for visualizing and interacting with data, wherein the blueprint defines an application, for visualizing and interacting with data. The application may operate on the client computer within a web browser and may include program code or scripts that operate within the web browser and transmit data and commands to and from the server. In response to receiving a data fetch message from the application, the server receives data from a selected one of a plurality of domains. The server then transforms the received data into a semantic data format. The transformed data is then stored by the server as a first data set. The first data set can then be transmitted to the client computer for further processing and visualization by the application using the blueprint.
Data Processing Method And Apparatus, And Device
A data processing method and apparatus, and a device are provided. In this application, a plurality of data processing modules may collaboratively process data. Data output by each data processing module is stored in a data set, the data set includes a plurality of pieces of data, each piece of data carries one index, and the index indicates a data processing module that generates the data. A first data processing module in the plurality of data processing modules may obtain, from the data set, first data carrying a first index, where the first index indicates a data processing module that generates the first data. Then, the first data processing module processes the first data to generate second data carrying a second index, where the second index indicates the first data processing module. Then, the first data processing module stores the second data into the data set.
LOW LATENCY INGESTION INTO A DATA SYSTEM
Described herein are techniques for improving transfer of metadata from a metadata database to a database stored in a data system, such as a data warehouse. The metadata may be written into the metadata database with a version stamp, which is monotonic increasing register value, and a partition identifier, which can be generated using attribute values of the metadata. A plurality of readers can scan the metadata database based on version stamp and partition identifier values to export the metadata to a cloud storage location. From the cloud storage location, the exported data can be auto ingested into the database, which includes a journal and snapshot table.
Multidimensional associative memory and data searching
A method for searching data includes storing a probe data and a target data expressed in a first orthogonal domain. The target data includes potential probe match data each characterized by the length of the target data. The probe data representation and the target data are transformed into an orthogonal domain. In the orthogonal domain, the target data is encoded with modulation functions to produce a plurality of encoded target data, each of the modulation functions having a position index corresponding to one of the potential probe match data. The plurality of encoded target data is interfered with the probe data in the orthogonal domain and an inverse transform result is obtained. If the inverse transform result exceeds a threshold, information is output indicating a match between the probe data and a corresponding one of the potential probe match data.
CROSS-SILO DATA STORAGE AND DEDUPLICATION
In some aspects, a computing system may generate a content-defined tree. A content-defined tree may be a tree of cryptographic hashes where each leaf is a hash of a chunk (e.g., data chunk) of a data object, and each parent node (e.g., interior node) is the hash of a concatenation of the hashes of the parent's children nodes. To create parent nodes for the leaf nodes, a computing system may group leaf nodes together based on a rolling hash (e.g., a rolling hash of the hashes of the leaf nodes) satisfying a condition. Each parent node may include a hash that represents the concatenation of the hashes of the leaf nodes that fall under the corresponding parent node.