11 results about "Datalog" patented technology

Methods, systems, and machine-readable media perform a search of field service records in a datastore using generative artificial intelligence (AI). An utterance requesting a search of field service records is received from a user device. The generative AI selects one or more actions with which to process the user utterance. The generative AI also resolves a datetime range. A field service record data query language (DQL) query is built based on the selected one or more actions and the datetime range. The DQL query is executed on a field service record datastore to receive a list of field service records, which are then transmitted to the user device responsive to the utterance. The generative AI can also be used to format the field service records for display before transmitting to the user device. Generative AI hallucinations and inaccuracies are avoided in the search results.

This specification provides one or more embodiments of a data query method, apparatus, electronic device, and storage medium. The method includes: during a data query of queried data based on the compilation result of a data query language, in response to the end of a data query for the current data unit, obtaining a first query time for the current data unit, and swapping the order of a first predicate and a second predicate in the compilation result of the data query language, wherein the queried data includes multiple data units; in response to the end of a data query for the next data unit, obtaining a second query time for the next data unit; in response to the first query time being greater than or equal to the second query time, retaining the order of the first predicate and the second predicate in the compilation result; and in response to the first query time being less than the second query time, restoring the order of the first predicate and the second predicate in the compilation result of the data query language.

The present invention discloses a method and system for automatically mining third-party component vulnerabilities in Internet of Things firmware based on Datalog, belonging to the field of Internet of Things security technology. The system includes: a firmware preprocessing module, which collects and preprocesses firmware and stores it in a firmware warehouse; a Datalog encoding module, which extracts files in the firmware and extracts string content, and re-encodes the decompiled results of the binary files using the Datalog encoding method; a third-party component identification and rule extraction module, which identifies third-party components in the firmware based on regular matching and edit distance, and obtains relevant third-party component usage rules; a vulnerability query module, which uses a Datalog query template filled based on the third-party component usage rules to perform logical queries on third-party component misuse vulnerabilities in the firmware. The present invention can quickly and accurately mine third-party component misuse vulnerabilities in Internet of Things firmware.

The invention discloses a logistics financial data processing method and device, and relates to the technical field of data processing. The specific implementation mode of the method comprises the steps of receiving a data acquisition request of target financial data sent by adopting a preset financial control; based on the data acquisition request, a graph-like data query language is adopted to generate a query statement; and obtaining target financial data from a data source based on the query statement, and feeding back the target financial data to the client, so that the client displays the target financial data. Development of an API layer is replaced by a graphical data query language, a declarative language is provided for a foreground system, the foreground system can self-define a data structure and express data requirements, the problem that the foreground system excessively obtains unnecessary data due to the fact that redundant fields are covered when the API layer returns a request is solved, and waste of network and memory resources is reduced.

The invention discloses an automatic threat assessment method for an intelligent network connection system, and the method comprises the steps: a security information input module which constructs an attack target, an attack entrance, a vulnerability set and system configuration represented by a Datalog statement based on an ontology model, and takes the attack target, the attack entrance, the vulnerability set and the system configuration as the input of an attack path reasoning module; the attack path reasoning module is used for generating a logic attack graph through MulVAL framework reasoning, attack graph deconstruction and attack graph optimization on the basis of input security information and a designed reasoning rule; and the quantitative risk assessment module is used for disassembling an attack path of the logic attack graph, generating a Bayesian attack graph by calculating a reachable probability and a risk value of the attack path, and finally visualizing the Bayesian attack graph. The method is applied to a real open test vehicle, threat analysis and evaluation are carried out on the automatic driving control unit of the target vehicle, and the practicability is ensured.

A computer-implemented system is provided for configuring and managing a federation ecosystem implemented in a data query language and comprising a plurality of subgraphs. The system includes a sandbox registry in communication with the subgraphs. The sandbox registry is configured to test and verify changes to the subgraphs to ensure validity of the subgraphs. The system also includes a global registry in communication with the sandbox registry. The global registry is configured to register the subgraphs after the subgraphs are tested and verified by the sandbox registry. The system further includes a portal in communication with the global registry. The portal is configured to present to a user the subgraphs registered with the global registry and receive from the user instructions for combining two or more of the subgraphs to form at least one supergraph.

The invention provides a structured statement execution method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a structured statement, and checking the grammar correctness of the structured statement, the language type of the structured statement being one of the following: a data definition language, a data manipulation language, a data control language and a data query language; under the condition that the grammar of the structured statement is correct, analyzing the structured statement by adopting SQL Parser to obtain a hierarchical abstract syntax tree; determining the language type of the structured statement according to the hierarchical abstract syntax tree; and processing the structured statement according to the language type of the structured statement to obtain a target statement, and executing the target statement to perform corresponding operation on the ES cluster. According to the method, the SQL instruction is accurately converted into the domain specific language adapting to the ES internal working principle, the cost that an SQL user is familiar with ES native API and grammar is reduced, and deep integration of the SQL protocol and the ES is achieved.

The embodiment of the specification provides a method and device for training a sequence generation model. According to the method, first, an original training sample is obtained, which includes a first sentence for querying a target data table through a natural language, metadata of the target data table, and a second sentence as a data query language. Then, according to a preset probability, a predetermined number of noise adding operations are applied to the training sample, wherein any one of the noise adding operations at least includes modifying one of the first sentence and the second sentence, thereby generating a noise-added sample including a source sentence, target metadata and a target sentence. Then, an input sequence is formed based on the source sentence and the target metadata, the input sequence is processed by using the sequence generation model to obtain an output sequence, and the sequence generation model is updated according to the output sequence and the target sentence.

The present invention belongs to the field of knowledge graph rule conflict detection and discloses a rule conflict detection method and system based on topological sorting and constraint solving, which is used to judge the legality and rationality of rules and regulations in enterprise supply chain management systems. The present invention adopts a rule parsing method based on an abstract syntax tree (AST) to parse a rule string written in Datalog syntax into JSON format and semantically associate it with an existing rule set. When adding or modifying a rule in a rule set, the rule set is tested for terminology semantic inconsistency conflicts. If there is no conflict, the addition or modification is successful; otherwise, an error message is displayed and the addition or modification is not performed. A topological sorting method is used to detect whether dependency loop conflicts occur in the rule set to prevent rule reasoning from falling into deadlock. The concept of constraint solving is introduced to detect whether there are mutually exclusive rules in the rule set to avoid errors in the rule reasoning process, thereby ensuring the correctness of rule reasoning.

The invention relates to a heap vulnerability detection method and device, computer equipment, a readable storage medium and a program product. The method comprises the steps that when a target program runs, a target library function called by the target program is hijacked, and operation log data of a heap memory is recorded; processing the operation log data to obtain target operation log data in a datalog data format; and analyzing the target operation log data to obtain a vulnerability detection result. By adopting the method, the heap vulnerability detection precision can be improved.

A system, method, and computer-program product includes obtaining a data query schema that provides instructions for constructing computer-executable search queries according to a search syntax permitted by a target data query language, extracting, from the data query schema, one or more sets of query components that define the search syntax of the target data query language, synthetically generating a plurality of natural language-to-search query training data samples based at least in part on the one or more sets of query components, and configuring a natural language-to-search query machine learning model based on training a machine learning text-to-text transformer model using the plurality of natural language-to-search query training data samples.