Systems and methods for multiple updates to a database using paths is disclosed. Updates to a graph database can be performed by associating an attribute node, that stores the updated value, to the entity node to-be updated. When the entity node is queried for the value, the nearest attribute node is identified using a shortest path determination.

Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Implementations described herein relate to methods, systems, and computer-readable media to selectively synchronize database objects. In some implementations, a method includes receiving a request to synchronize records that include a corresponding root record and one or more connected records from a first database instance to a second database instance, wherein the request includes a specified graph configuration and an object boundary identifier; collecting the one or more records by traversing a corresponding graph configuration associated with each of the one or more root records; generating a snapshot that includes the one or more records into one or more object record sets based on a corresponding object boundary identifier associated with each of the one or more root records and the one or more connected records; publishing the snapshot to the second database instance; and updating the second database instance.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for assigning operations of a computational graph to a plurality of computing devices are disclosed. Data characterizing a computational graph is obtained. Context information for a computational environment in which to perform the operations of the computational graph is received. A model input is generated, which includes at least the context information and the data characterizing the computational graph. The model input is processed using the machine learning model to generate an output defining placement assignments of the operations of the computational graph to the plurality of computing devices. The operations of the computational graph are assigned to the plurality of computing device according to the defined placement assignments.

A diamond asset comprising one or more diamonds and an encryption chip is used to asset-back a cryptographic token that can be used to conduct transactions. The cryptographic token is written to a blockchain using a smart contract that is configured to enable a transaction associated with the token in response to two or more of: a signature by the encryption chip, a signature by the owner of the diamond asset, and a validation of a visual layout of the diamond asset.

A graph neural network to predict net parasitics and device parameters by transforming circuit schematics into heterogeneous graphs and performing predictions on the graphs. The system may achieve an improved prediction rate and reduce simulation errors.

Examples of the present disclosure describe systems and methods for ontology-based graph query optimization. In an example, ontology data relating to a graph or isolated collection may be collected. The ontology data may comprise uniqueness and topology information and may be used to reformulate a query in order to yield a query that is more performant than the original query when retrieving target information from a graph. In an example, reformulating a query may comprise reordering one or more parameters of the query relating to resources, relationships, and/or properties based on uniqueness information. In another example, the query may be reformulated by modifying the resource type to which the query is anchored based on the topology information. The reformulated query may then be executed to identify target information in the isolated collection, thereby identifying the same target information as the original query, but in a manner that is more performant.

A search query relating to a search for people and including one or more search terms is received. A search graph for the search is created from a previously created graph which is a directional graph in which people are represented by nodes and content is represented by nodes or edges. The search graph is generated by filtering out nodes or edges that represent content that is determined not to be relevant to the search terms in the search query; and, for the remaining content that is determined to be relevant to the search terms in the search query, adding to the graph a measure of the relevance of the content to the search terms. The search results are generated by operating on the search graph to identify people in the search graph who are sources of content that is relevant to the search terms.

The present invention may provide, to quantize data including a definite value and an estimated value, a definite value and estimated value-based data quantization method comprising the steps of: a data quantization apparatus collecting, from at least two information manager-side apparatuses, data corresponding to a pre-set definite value for each period of a previous section pre-set on the basis of a current date, an estimated value and definite value for a current year on the basis of the current date, and an estimated value for each period of a subsequent section pre-set based on the current date; calculating at least one comparison reference value on the basis of a provision value after collecting the provision value that can be compared with the estimated value and the definite value; and quantizing the data for each period and for each section via a method for assigning a weight to the current year for each period, and each period of the previous section and subsequent section, by comparing the definite value for each period of the previous section, the definite value for each section of the current year, and the estimated value for each period of the subsequent section with the comparison reference value.