46 results about "Logical query" patented technology

The invention belongs to the field of data query, and particularly discloses a data query method and system based on a large language model, a terminal and a medium. Analyzing the natural language query statement by using a natural language processing technology to obtain query parameters including a query entity, a statement dependency relationship and a user intention; utilizing a pre-trained large language model to generate a logic SQL query statement according to the query parameters; converting the logic SQL query statement into a physical SQL query statement by utilizing a semantic layer technology; the method comprises the following steps of: converting a physical SQL (Structured Query Language) query statement into a domain specific language for Elasticsearch query by utilizing an SQL parser; and executing the Elasticsearch query on the Elasticsearch cluster by using a domain specific language to obtain a query result. A natural language processing technology, a large language model and a semantic layer technology are utilized to convert a natural language query statement into an Elasticsearch query DSL, the data query process is simplified, the data query efficiency and precision of a user are improved, the cost is reduced, and the query requirement is met.

According to one embodiment, host infrastructure analysis logic that attempts to detect a malicious host operating within a network prior to a cyber-attack being conducted by the malicious host is described. The host infrastructure analysis logic includes querying logic, profile confirmation logic, classification logic and reporting logic. The querying logic retrieves salient characteristics associated with a plurality of hosts operating within the network and determines whether any hosts are suspicious. The profile confirmation logic, if a suspicious host is detected, establishes communications with that suspicious host to retrieve additional context information. The classification logic, based on the retrieved information, determines whether the suspicious host is malicious, prior to and without reliance on information associated with a cyber-attack being conducted by that host. The reporting logic outputs analytic results identifying at least the suspicious host is operating as a malicious host.

The invention discloses a multi-language data analysis-oriented extensible system, method, equipment and medium, and relates to the technical field of multi-language analysis, the multi-language data analysis-oriented extensible system comprises a grammar analysis module used for analyzing a query language and generating a language-specific syntax tree structure after analysis; the grammar adaptation module is used for converting a language-specific grammar tree structure into an abstract grammar tree AST in a uniform format; the abstract syntax tree processing module injects a permission control strategy, a field desensitization rule and an alarm exception expression into the AST; the business processing module is used for executing business-related rule check and label injection; the query plan generation module is used for constructing a logic query path and a corresponding distributed execution scheme; and the task scheduling module issues the distributed execution scheme to the corresponding execution node. According to the method, by constructing a unified multi-language grammar analysis framework and a standardized abstract syntax tree AST representation mechanism, compatibility and fusion of multiple query languages such as SQL, SPL and natural language are achieved.

The invention discloses a big language model knowledge question-answering method based on semantic analysis correction, and belongs to the field of natural language reasoning, the method comprises the following steps: extracting a key entity from a natural language question, matching a target entity in a knowledge graph, and mining a plurality of knowledge paths in the knowledge graph for model training; adopting a prompt instruction and a knowledge path to supervise and train the large language model, so that the large language model has the capability of generating a multi-hop reasoning path conforming to a knowledge graph structure; performing knowledge path decoding based on the trained model, converting a natural language problem into a plurality of candidate reasoning paths, and converting the candidate reasoning paths into logic query statements to be executed in a knowledge graph, thereby completing fact verification and completion of the paths; and inputting the high-quality path subjected to graph verification and the natural language question into a large language model to obtain an accurate and explainable answer. According to the method, deep fusion of structured knowledge and a language model is realized, and the reasoning ability, the answer accuracy and the interpretability in a complex question and answer task are improved.

The subject technology receives a query. The subject technology generates a set of query blocks based on parsing the query. The subject technology stores query block metadata for each query block from the set of query blocks. The subject technology restores a set of logical query block boundaries. The subject technology performs a hash-based query block matching. The subject technology generates, after performing the hash-based query block matching, a final query plan. In an example, if a (same) query is executed again the same logical query blocks would produce the same metadata (e.g., identifier, name and hash). This metadata can be used to match logical query blocks between multiple executions of the same query.

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The invention provides an enhanced symmetric searchable encryption method and system, and relates to the field of data security and privacy protection. The method comprises the steps that a plaintext document set is symmetrically encrypted, keywords are extracted, and an encryption index token is generated through a pseudo-random function; constructing a reverse index structure, and mapping the token to a document identifier; dynamic insertion, deletion and modification of documents are supported, and indexes are synchronously updated in real time; cipher query is realized by generating a search token, and after the server returns a matching result, the client decrypts the matching result to obtain an original text. According to the system, through multi-keyword Boolean logic query, an index structure is compressed by adopting a Bloom filter, the retrieval efficiency is improved in combination with a jump pointer or a B + tree, a false query strategy is introduced to hide an access mode, and the anti-attack ability is enhanced. Compared with an existing scheme, the method has the advantages that the searchability, the system performance and the privacy protection capability of the encrypted data are improved, and the method is suitable for security data retrieval application in cloud computing, database systems and block chain environments.

The application provides a database instruction statement execution method, device and equipment and a readable storage medium, which can be applied to the technical field of computers, and comprises the following steps: analyzing a database instruction statement to obtain a plurality of syntax structures of the database instruction statement and semantics of the plurality of syntax structures; constructing a target abstract syntax tree according to a predetermined mapping relationship; performing semantic analysis on the target abstract syntax tree to obtain a logical query plan tree; optimizing logical operators corresponding to standard nodes and extended nodes in the logical query plan tree according to preset optimization strategies matched with node types until the logical query plan tree no longer changes, to generate a physical execution plan tree; and executing physical execution operators corresponding to the standard nodes and the extended nodes in the physical execution plan tree according to preset execution strategies matched with node types, to obtain an execution result of the database instruction statement.

The invention discloses a building vector graph multi-scene intelligent simplification method and system, and belongs to the technical field of geographic information systems. Comprising the following steps: establishing a four-level data system comprising an original data layer, an engineering cache layer, a display cache layer and a terminal view layer; monitoring data change and user interaction events through an event bus; the event is responded, the current application scene is intelligently recognized, and the corresponding simplified parameter configuration is dynamically loaded; based on the configuration, executing simplification logic on the target building vector graph; querying a topological relation to carry out cooperative processing on the contours of the adjacent buildings; and synchronously updating a processing result to the four-level data system. Through four-stage data caching, dual-drive triggering and scene self-adaptive judgment, efficient, high-quality and self-adaptive processing of building simplification in multiple scenes such as cartographic integration, real-time display and spatial analysis is realized, and the system flexibility, the resource utilization rate and the user experience are improved.

The invention provides a data query method and device, equipment and a medium, and relates to the technical field of computer software, in particular to the technical field of databases. The method comprises the steps that a logic query request for a logic wide table is received, the logic wide table is constructed based on multiple physical tables, and multiple groups of dependency relationships exist among the multiple physical tables; analyzing the logic query request to determine a to-be-queried target table in a plurality of physical tables; sorting the plurality of groups of dependencies to obtain a global dependency sequence and a reference table in the plurality of physical tables; on the basis of the topological structure, determining a necessary dependence path from the reference table to the target table; respectively converting at least one necessary dependency relationship included in the necessary dependency path into physical table connection relationships, and sequentially combining the physical table connection relationships according to the sequence of the at least one necessary dependency relationship in the global dependency relationship sequence to obtain a physical query statement; and performing data query by utilizing the physical query statement.

The present invention relates to the technical field of geographical knowledge graph embedding, and specifically discloses a method for constructing an implicit reasoning model of a geographical knowledge graph considering time period features, including the following steps: First, construct a multi-scale geological sample data set; then establish an implicit reasoning model considering time period features; finally, evaluate the model performance through evaluation indicators and analyze experimental results. By adopting the above method for constructing an implicit reasoning model of a geographical knowledge graph considering time period features, aiming at the problem of insufficient ability of existing time encoders to extract time period features, a geographical logical query and answer oriented to time period encoding is constructed. The limitations of existing time encoders in processing time period information and multi-scale time information are solved, a time period encoder oriented to time period features is constructed, and the effectiveness of the time period encoder and its performance in downstream tasks are verified using a geological sample data set.

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 provides a database access method and system supporting unified authentication and business model mapping, and the method comprises the steps: uniformly converting a query request into a standard abstract syntax tree, and intercepting an identity certificate in the query request to construct a complete authority context object; mapping the permission context object into a temporary role name with the minimum required permission, and sending the temporary role name to a key management system to generate a temporary database connection voucher; the permission context object is received, and a specific RLS predicate character string and a CLS function expression are generated based on a preset RBAC strategy rule, an RLS constraint predicate template and a CLS constraint desensitization function template; based on the business model, mapping the standard abstract syntax tree to generate an initial logic query plan; and according to the RLS predicate character string and the CLS function expression, forcibly solidifying the security policy into the initial logic query plan to generate a target logic query plan. The technical problem that authentication and authorization mechanisms are separated in the prior art is solved.

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The invention relates to a query execution method and device for a heterogeneous distributed database and electronic equipment. The method comprises the steps that after an SQL query request initiated by a service application is received, the SQL query request is converted into a logic query plan; generating a plurality of candidate physical execution plans which aim at each database operator in the logic query plan and comprise different target computing nodes; for each candidate physical execution plan, combining the operator type, the data volume, the expected performance information of the target computing node and the real-time load information, performing cost evaluation to obtain the corresponding total cost; determining the candidate physical execution plan with the lowest total cost in all the candidate physical execution plans as a target execution scheme; and instantiating the target execution scheme into a distributed execution plan with a computing node identifier, and scheduling a distributed execution engine to execute the distributed execution plan. The technical problem that resource utilization is low in efficiency due to the fact that an optimizer lacks hardware perception is solved.

The invention discloses a method for solving complex query containing numerical values in knowledge graph reasoning. The method comprises the following steps: 1) establishing a model of complex logic query containing numerical values; the model comprises a numerical value-entity predictor and an entity filter; wherein the numerical value-entity predictor is used for deriving a numerical value, an entity or a statistic of a given sub-query; the entity filter is used for comparing the numerical value of the sub-query prediction with the entity attribute value obtained by calculation, and filtering out entities meeting constraints on the knowledge graph by taking the numerical value of the sub-query prediction as a constraint value; according to the method, the complex query related to statistics and the query with numerical constraint can be effectively processed, and the complex query related to statistics and the query with numerical constraint can be effectively processed.

The invention relates to the technical field of data processing, can be applied to the fields of medical health, financial science and technology and the like, and discloses a real-time data intelligent query method, device and equipment and a storage medium. The real-time data intelligent query method comprises the steps that multiple heterogeneous data sources are registered, field names, data types and service meanings in the heterogeneous data sources are recognized, and preliminary semantic fingerprints are generated; based on the preliminary semantic fingerprints, constructing multilayer semantic mapping; receiving a query request of a user, analyzing the query request based on the multilayer semantic mapping, and generating a logic query plan; acquiring a real-time data source state, and based on the logic query plan, performing dynamic path selection in combination with the real-time data source state to generate a cross-source query plan; and executing the cross-source query plan, obtaining query results of the heterogeneous data sources, performing result fusion on all the query results through the semantic consistency alignment model, and outputting a fusion result in a unified format. By means of the method, intelligent semantic association and real-time optimization access of cross-source data are achieved.

The present invention discloses an interpretable knowledge reasoning method based on a multi-round generation strategy, including: given a knowledge graph to be queried, and using the TransE model to generate entity vectors of each entity and relationship vectors of each relationship in the knowledge graph; obtaining a query condition and identifying the relationship between entities in the query condition; calculating the similarity between the entity vectors of each entity in the knowledge graph and the entities in the query entity set to obtain a candidate entity set; based on the entities and the relationship between entities in the query condition, following the multi-round generation strategy; calculating the similarity between the candidate entities in the candidate entity set and the logical query vector, and taking the entities with similarity higher than a preset threshold. The solution of the present application realizes generating first-order logic rules for complex queries, using semantic similarity to measure the relevance between a given query and candidate entities, and generating an answer entity set.

This invention discloses a conversational business query method and system based on permission semantic parsing and dynamic desensitization backtracking. The method receives multiple rounds of business queries from users; parses user identity, position, organizational level, authorized data domain, field sensitivity level, and display granularity into permission semantic vectors, and aligns them with a query semantic graph to form a permission envelope; generates candidate logical queries based on the query semantic graph, and constructs a fragment backtracking key for each answer fragment, including field source, aggregation function, filter condition hash value, permission version, desensitization rule version, minimum display granularity, and session inheritance tag; when there is follow-up questioning, error correction, drill-down, or permission changes, the fragment backtracking key is compared and the permission residual change is calculated, driving the fragment security state machine to execute valid, pending recalculation, frozen, downgraded, or rejected display. This method can improve the security, traceability, and interactive continuity of business query results.

To improve the technological process of computerized answering of logical queries over incomplete knowledge bases, obtain a first order logic query; with a trained, computerized neural network, convert the first order logic query into a logic embedding; and answer the first order logic query using the logic embedding.

The invention relates to a method, a device and equipment for realizing a Prometheus cluster. The method comprises the following steps: configuring a first label, a second label and a third label for each Prometheus instance according to an acquisition configuration template and environment variables during operation; the first label and the second label are used for determining a collection target; the third label is used for identifying the type of the Prometheus instance; according to the pre-calculation configuration template, pre-calculation fragmentation configuration and pre-calculation layering configuration are carried out on the Prometheus instance; and a query component is configured to complete query and aggregation of Prometheus data. Therefore, duplicate removal and backup can be carried out in advance by utilizing Prometheus label information, and the standby instance can be queried only when a certain main instance does not respond, so that half of memory loss can be saved, duplicate removal logic is avoided, and the query performance is better; and the requirements of high reliability, easy expansion, low resource utilization rate and the like are well met.

The invention provides a parameter configuration method and device, equipment and a storage medium. The method comprises the following steps: receiving a configuration template sent by a service end, wherein the configuration template comprises configuration logic, variable data, stable data and a preset rule base; analyzing the variable data to obtain to-be-configured data; comparing preset standard stable data with the stable data to obtain feature data of the stable data; querying a preset rule base according to the feature data to obtain a configuration rule; querying a preset database according to the configuration logic to obtain an available primary key value range of the to-be-configured parameter table; generating a to-be-executed statement according to the to-be-configured data, the available primary key value range, the configuration logic and the configuration rule; storing the to-be-executed statement in a to-be-executed file; and sending the to-be-executed file to the service end. The parameter configuration efficiency can be improved, the parameter configuration accuracy is improved, and the requirement for the service capacity of operation and maintenance personnel is lowered.

Embodiments identify code portions. An embodiment receives a logical query, indicating a selected behavior and constructed in a logical query grammar, associated with a codebase. The logical query grammar is: (1) configured to represent logical queries each having (i) a unary predicate including a head variable, (ii) one or more predicate citations associated with the head variable, and (iii) one or more predicate citations associated with one or more other variables different from the head variable; (2) configured with variable name reuse; (3) configured to represent at least one logical query having one or more conjoined citations associated with (i) a given head variable and (ii) exactly one other variable different from the given head variable; and (4) configured with stratified negation. A logical graph representing the codebase is searched based on the query to generate a result indicating a presence of a code portion exhibiting the selected behavior.

Methods, systems, and computer programs are presented for generating and managing query plan representations using a unified framework based on a common query plan configuration. The system includes a memory with instructions and one or more computer processors. The instructions, when executed, cause the system to provide a user interface (UI) for a development tool to create a configuration for a plan builder. The UI offers options to create a plurality of query plans, including a logical query plan, a physical query plan, a query plan hash, and a query plan signature. The system receives parameters to create the configuration and select a query plan from the plurality of query plans. The system generates a first query plan based on the parameters and causes the presentation of the first query plan on a display.

The invention provides a database instruction statement execution method, device and equipment and a readable storage medium, which can be applied to the technical field of computers, and the method comprises the following steps: analyzing a database instruction statement to obtain a plurality of grammar structures of the database instruction statement and semantics of the plurality of grammar structures; constructing a target abstract syntax tree according to a predetermined mapping relation; performing semantic analysis on the target abstract syntax tree to obtain a logic query plan tree; according to a preset optimization strategy matched with the node type, logic operators corresponding to standard nodes and expansion nodes in the logic query plan tree are optimized until the logic query plan tree does not change any more, and a physical execution plan tree is generated; according to a preset execution strategy matched with the node type, physical execution operators corresponding to the standard nodes and the extension nodes in the physical execution plan tree are executed, and an execution result of the database instruction statement is obtained.

The invention discloses a temporal feature knowledge graph logic query answering method, medium and equipment, and the method comprises the steps: taking fixed entity embedding as input according to the post-order traversal of a query calculation tree, carrying out query single-hop projection operation when a projection operator is traversed, and converting entity embedding or query embedding into next-hop query embedding; when negative operators are traversed, complementation is carried out, and when intersection or union operators are traversed, query embedded input of the shunt pairs and relation feature vectors of the shunt pairs are extracted; mapping the semantic similarity of the relation feature vectors into initial weights of the three logic systems; splicing query embedding and relation feature vectors, inputting the spliced query embedding and relation feature vectors into MLP, and calculating dynamic weights of the three logic systems; generating a mixed weight of the three logic systems by utilizing a gating mechanism to obtain query embedding; and calculating a query score according to the query embedding and each entity embedding to obtain a query answer set. The problem that the query precision is restricted by a fixed logic strategy is solved.

The invention relates to the technical field of big data processing, in particular to a method for automatically converting query statements among heterogeneous databases, which comprises the following steps of: firstly, analyzing and reconstructing a logic query request of a user to obtain a logic query object, and carrying out information association and matching by using components of the logic query object; therefore, the optimal physical table and the corresponding target data source engine can be quickly found out, and the problem of low response speed caused by direct query in the prior art is solved; on the basis, after the optimal physical table and the corresponding target data source engine are obtained, the heterogeneous data type can be automatically converted into a preset unified data type, so that the problem of compatibility error reporting caused by cross-database is solved. Compared with the prior art, the method has the advantages that the optimal physical carrier can be automatically selected on the basis of semantic analysis, data processing of dialect-level grammar conversion is accurately completed, and query efficiency and universality between heterogeneous databases are improved.

The application discloses a kind of collaborative filtering methods based on logic box embedding inference, comprising the following steps: S1, original data is collected and data set is made;S2, original data is cleaned and handled, and user interaction sequence and score sequence are generated;S3, user interaction sequence and score sequence generate first-order logic query, and then generate logic calculation graph;S4, user interaction sequence generates multiple item box embedding, and score sequence generates multiple relationship vector embedding according to user interaction behavior and score in logic calculation graph;S5, item box embedding and relationship vector embedding are calculated according to logic calculation graph to obtain a target item box embedding;S6, the distance between target item box embedding and the nearest item box embedding is calculated, and the nearest n items are recommended to the current user as the most suitable project.This method can effectively integrate the recommendation algorithm framework of collaborative filtering and logical reasoning, effectively improve the performance of recommendation, and provide a new idea for subsequent engineering application.