180 results about "Tree generation" patented technology

The invention discloses an archive digitization full-life-cycle encryption integrity verification method and system, relates to the field of digital archive safety management, and is used for solving the problem of integrity and safety guarantee in archive digitization management. Logic units are divided through a semantic analysis engine, non-uniform blocks are generated based on sensitivity dynamic partitioning, local hash values are calculated, and a multi-level verification tree is constructed to generate root hash and a hash path mapping table; acquiring visitor identities, terminal environments and timestamps in each stage of an archive life cycle, generating state snapshots in combination with a hash path, and constructing a life cycle state snapshot chain; reconstructing a target logic unit verification path according to the access request, analyzing the structural difference between a current path and a historical snapshot chain through a path reconstruction type difference verification algorithm, and identifying structural offset, node tampering or path loss; and response control is triggered for abnormal verification, including session key updating and permission freezing, so that the security integrity guarantee of the digital archive in the full life cycle is improved.

The invention relates to the technical field of digital asset management, in particular to a block chain-based carbon asset full-life-cycle traceability and digital asset management platform. According to the platform, multiple data modeling and intelligent contract mechanisms are fused, and credible management of carbon assets in the whole process from generation, accounting, registration, transaction to auditing is achieved. The method comprises the following steps: collecting operation data of a forestry carbon sink project, constructing a structured Hash fingerprint, generating index root Hash by adopting a Merkle tree, and calculating a carbon sink amount as a basic data source of carbon assets; accounting the carbon sink credibility based on a Bayesian network model and eliminating abnormal data; carrying out anti-fact intervention analysis by utilizing a causal map, and screening abnormal assets with low causal consistency; on-chain matchmaking transaction of the carbon assets and the users is completed through a clustering and greedy matching mechanism; a life cycle auditing module is combined to evaluate responsibility contribution of key behavior variables to ESG indexes, and quantifiable, traceable and verifiable green asset full life cycle management is achieved.

The invention discloses an intelligent fault tree generation method and system based on joint simulation and dynamic causal reasoning, relates to the technical field of fault trees, and solves the problems that the manual construction efficiency of a complex system fault tree is low, the hidden failure path omission ratio is high, and a model and operation and maintenance data are disjointed. The method comprises the following steps: constructing a multi-physics field coupled system joint simulation model; capturing a propagation path of the fault among the functional units in real time, and generating a fault propagation map; constructing a minimum cut set based on Monte Carlo simulation and Bayesian network reasoning, and automatically adapting an AND / OR logic gate to generate a fault tree; and dynamically updating the knowledge graph in combination with an online learning technology. The method has a good application prospect in the field of health management of equipment with high safety requirements.

The invention relates to the technical field of enterprise data processing, and discloses an intelligent analysis system for enterprise operation data based on artificial intelligence. The system comprises an operation data acquisition module, an operation state analysis module, a decision tree generation module, a data compensation module and an execution parameter generation module. The operation data acquisition module acquires enterprise finance, supply chain logistics and market dynamic data in real time, integrates and cleans multi-source heterogeneous data, and generates an operation state data set; the operation state analysis module identifies a deviation degree between the key business index and a preset threshold value, and calculates a multi-dimensional abnormal value by means of a dynamic weighting strategy to obtain an abnormal feature set; a decision-making tree generation module constructs a multi-layer decision-making path according to the multi-layer decision-making path, matches an optimal branch in combination with a historical case library, and generates a visual decision-making tree; the data compensation module analyzes the influence of missing data and automatically supplements an external data source to generate a compensation parameter set; and the execution parameter generation module analyzes node priorities, quantifies resource configuration and time window parameters, and generates a strategy execution parameter packet.

The invention discloses an artificial intelligence algorithm-based e-commerce product recommendation method and system, and relates to the technical field of product recommendation. Comprising the following steps: constructing a user-behavior path flow tree by adopting a multi-criterion splitting mechanism, and generating a node path set; respectively slicing and recombining the user portrait set and the commodity portrait set, and carrying out cross combination; constructing a behavior cluster atlas to which the user belongs, projecting cross commodity nodes in the node path set and the candidate cross mapping set into an anti-cross atlas structure among behavior clusters, and extracting interaction points as a candidate recommendation set; and performing weight regression calculation on each node of the path of the user-behavior path flow tree by utilizing path probability density mapping corresponding to each cross commodity node in the candidate recommendation set, and generating a commodity recommendation sequence according to the maximum path passing probability. According to the method, the recommendation process with the behavior chain criterion and the coupling map mapping is constructed, so that the user experience is improved, and the conversion efficiency and the content distribution capability of the platform are enhanced.

The invention discloses a front-end Service code automatic generation method and system, and relates to the technical field of computers.The method comprises the steps that in response to a code generation demand of a user, the code generation demand is analyzed through a preset demand analysis model, and a demand analysis result is obtained; according to the demand analysis result, matching in a preset code syntax tree library to obtain a target code syntax tree; performing parameter optimization on the target code syntax tree to obtain an optimized target code syntax tree; generating an initial code in combination with the optimized target code syntax tree and YApi interface data; optimizing the initial code through a preset code optimization mechanism to obtain an updated code, and outputting the updated code at a front-end window; according to the method, the demand association graph and the interface calling chain are constructed according to the code generation demand, the highly matched syntax tree is screened out from the code syntax library, the corresponding code is generated, code optimization is performed, and the quality and reliability of the generated code are improved.

Provided are a method and device for parsing a database query statement, and a storage medium. A query statement for a database table to be queried is obtained, and an empty database table corresponding to the database table to be queried is created; the query statement is executed in the empty database table, and a parser installed in a database is called to parse the query statement to obtain a syntax tree, and an execution plan is generated based on the syntax tree for execution in the empty database table; and the syntax tree is obtained from the parser in an execution process of the query statement, and a syntax tree serialization result is generated and output as a parsing result of the query statement.

The invention discloses a government affair task dynamic distribution and multi-level auditing method and system, belongs to the technical field of government affair systems, and aims to solve the technical problem of how to realize a government affair task management method of task dynamic disassembly, hierarchical intelligent auditing and multi-source data deep fusion. Comprising the following steps: disassembling a government affair task by adopting a heterogeneous task tree generation method to form multiple levels of subtasks; the subtasks are distributed to an execution end based on the optimal distribution path; after receiving the subtasks, the execution end executes data acquisition and data submission operations; performing multi-level auditing on the data passing the basic logic verification according to a preset multi-level auditing rule, and executing rejection correction if any link in the multi-level auditing process is rejected; the data are stored in a global database, and data tables in the global database are associated through unique identification fields; and associating fields existing in the global library through an intelligent filling engine, and matching filling contents according to an acquisition scene to realize data updating and multiplexing.

Systems, apparatuses and methods provide technology that receives a first operator prompt associated with a character in a computing application, and generates, with a first machine learning model during an offline process, first responses based on the first prompt, where the first responses are dialog of the character. The technology stores the first responses into a dialog tree during the offline process, receives a second prompt associated with an end user of the computing application, generates, with the first machine learning model during the offline process, second responses to the second prompt and based on the first responses stored in the dialog tree, where the second responses are dialog of the end user, and adds the second responses to the dialog tree during the offline process.

The invention provides a front-end code evaluation method and system, electronic equipment and a program product, and the method comprises the steps: obtaining a front-end code, carrying out the compiling and rendering of the front-end code, and obtaining a generated front-end page and a target front-end page; performing code extraction processing on the generated front-end page and the target front-end page, and performing redundant node cleaning and code structure tree generation processing on extracted markup language codes to obtain a generated code tree and a target code tree; performing tree structure and element content error calculation processing on the generated code tree and the target code tree to obtain a content structure error; performing visual structure error calculation processing on the generated front-end page and the target front-end page to obtain a visual structure error; and according to the content structure error and the visual structure error, determining and obtaining an evaluation result for generating the front-end code. The scheme can improve the generation accuracy of the front-end code, and can be widely applied to the technical field of artificial intelligence.

To generate a summary that holds causal relationship for a plurality of images.SOLUTION: A summarization apparatus includes: a rhetorical structure tree generation unit configured to generate a rhetorical structure tree for a plurality of images regarding a certain event related in time series; an event relation generation unit configured to generate a tree structure that represents a relationship between events related to the images, using the images as nodes, based on the rhetorical structure tree; and a summary generation unit configured to extract subtrees from the tree structure so as to satisfy the constraints for the summary of the images.SELECTED DRAWING: Figure 2

The invention relates to the technical field of natural language processing and artificial intelligence, and discloses a large-model complex instruction-oriented fine-grained intention recognition method, which comprises the following steps of: constructing a candidate analysis forest of an input instruction, and executing entity alignment of each node and a domain knowledge graph; performing semantic compatibility verification on the candidate dependency trees by utilizing entity relationships in the atlas, and screening an optimal analytic tree in combination with syntactic probability and knowledge consistency scores; if the analytic tree meeting the threshold value does not exist, a semantic conflict edge is positioned, and candidate mounting points are searched by using a map neighborhood relation to reconstruct a dependency structure; and finally, generating standardized data containing a structured analytic path based on the optimal analytic tree, and performing fine adjustment on the large model. According to the method, logic constraint and dynamic repair are carried out on the syntactic structure by introducing the knowledge graph, analysis errors caused by multiple modification or structural ambiguity in a complex instruction are effectively solved, and the accuracy and robustness of intention recognition of a large model in the vertical field are improved.

The invention belongs to the technical field of spacecraft product quality and reliability analysis modeling, and particularly relates to a fault tree generation method and device based on a knowledge graph and a large model fusion technology. The method comprises the following steps: constructing a spacecraft product fault domain ontology model, establishing a tag system comprising entity tags and relation tags, and extracting related knowledge from a technical document, a SysML model and an FMEA table by using a large language model to form a triple; according to entity types and relation types of different source knowledge, fusion is carried out, and a fault knowledge graph is constructed; obtaining a function dependence sub-graph, a fault behavior sub-graph and a redundant sub-graph of a function or a composition structure from the fault knowledge graph, and retrieving a specific sub-graph from the fault knowledge graph according to a user question; analyzing fault propagation relation and redundant structure information based on function dependence in the specific sub-graph to construct an OR gate and an AND gate, and mapping nodes in the specific sub-graph to a basic event, an intermediate event, a top event and a gate to generate a fault tree.

The invention discloses a document processing method and related equipment, and belongs to the technical field of data processing.The method comprises the steps that in response to a document input instruction, a to-be-processed target document is obtained; performing structure analysis on a to-be-processed target document to generate a directory tree of the target document; calling a dynamic recursive slicing algorithm, traversing and analyzing the directory tree of the target document, and generating a plurality of text slices with dynamic lengths; and vectorizing the plurality of text slices with the dynamic lengths, and uploading and storing the vectorized text slices to a database of a retrieval enhancement generation system. By constructing the directory tree and traversing the directory tree by adopting the dynamic recursive slicing algorithm, the document structure can be more accurately understood, the semantic integrity of the document slices is improved, and the retrieval accuracy and the answer generation quality of the retrieval enhancement generation system are further effectively improved.

The embodiment of the invention provides a page style code generation method and device, a medium, equipment and a program product. The method comprises the following steps: updating a current page element code to obtain a target page element code, and determining a style name and a hierarchical relationship of a target page element according to a first abstract syntax tree corresponding to the target page element code; updating a target object based on the style name and the hierarchical relationship of the target page element, wherein the target object is used for storing the style name and the hierarchical relationship of the current page element corresponding to the current page element code; and updating a second abstract syntax tree corresponding to the current page style code according to the updated target object, and generating a target page style code according to the updated second abstract syntax tree. According to the embodiment of the invention, the second abstract syntax tree of the existing page style code is updated based on the style name and the hierarchical relationship in the target object, a complete abstract syntax tree of the page style code does not need to be regenerated, and the generation efficiency of the page style code is improved.

The application relates to an object classification method and device, computer equipment, a storage medium and a computer program product. An initial decision tree is generated based on training operation data and a training label corresponding to a training object, and the initial decision tree is used as a current decision tree; the training operation data is input into the current decision tree to obtain a current round prediction result, a prediction error is generated based on the training label, the current round prediction result and a historical round prediction result; a backward decision tree of the current decision tree is generated based on the training operation data and the prediction error, the backward decision tree is used as the current decision tree, the step of inputting the training operation data into the current decision tree to obtain the current round prediction result is returned to be executed until a first convergence condition is met, and a plurality of backward decision trees are obtained; and an object classification model generated based on the initial decision tree and each backward decision tree is used to obtain a prediction label corresponding to a target object by fusing prediction results of target operation data of the target object of each decision tree, so that the object classification accuracy can be improved.

This invention discloses a method and system for multi-robot collaborative operation in oil and gas fields based on a large language model, relating to the fields of robot collaboration and intelligent planning. The method acquires oil and gas field operation task information, pre-sets task construction rules, uses a large model to parse task instructions and form a hierarchical task tree, and then writes oil and gas field operation constraint information to form a constrained hierarchical task tree. Simultaneously, it acquires robot capability information and constructs a skill library, matches and selects execution robots, and thus determines the multi-robot collaborative operation arrangement to complete the oil and gas field operation task. The system includes a task acquisition module, a task rule pre-setting module, a task tree generation module, a constraint writing module, an execution subject determination module, and a collaborative execution module. This invention, through the collaborative design of the method and system, enhances the understanding and collaborative stability of multi-robot systems for complex tasks, improving their collaborative efficiency and task completion quality in oil and gas field scenarios.

The invention relates to a system development method and device, computer equipment, a computer readable storage medium and a computer program product. Obtaining a system model constructed based on a first language; the first language is a semi-formalized modeling language; analyzing the system model to obtain an abstract instantiated syntax tree corresponding to the system model, and performing system analysis at least including system resource budget analysis based on the abstract instantiated syntax tree to obtain an analysis result; under the condition that the analysis result meets a preset condition, generating a target code of a second language matched with the system model based on the abstract instantiation syntax tree; the second language is a programming language. By adopting the method, the model development efficiency and quality can be improved.

The invention provides a business processing method and device, equipment and a storage medium. The method comprises the following steps: analyzing a syntax tree of a business source code to obtain a function dependency relationship in the syntax tree and a first data query function used for accessing an external data source; determining a plurality of second data query functions from the first data query functions according to the function dependency relationship; wherein the plurality of second data query functions do not depend on one another and are used for accessing the same external data source; combining the plurality of second data query functions to obtain an optimized syntax tree; and generating an executable code according to the optimized syntax tree, and executing the executable code. According to the method, the data query efficiency of the business source code can be improved, so that the business processing efficiency is improved.

The invention relates to a service execution track tree generation method and device, computer equipment and a storage medium. The method comprises the following steps: generating a target node log set according to each target node log data; performing branch structure tiling analysis according to the service execution process branch tree to obtain first key value mapping of each service execution process branch node, obtaining a current canvas configuration tree, and performing node information analysis according to the current canvas configuration tree to obtain second key value mapping of child nodes of each parallel gateway node; the service execution process branch nodes are service execution process nodes having node branches in the service execution process branch tree; and updating the corresponding target node log data according to each first key value mapping, removing the target node log data corresponding to each second key value mapping from the target node log set, and generating a service execution track tree according to the target node log set and the current canvas configuration tree. By adopting the method, the visibility of the trajectory data and the comprehensiveness of the trajectory data can be improved.

The present application relates to the technical field of electronics, and discloses a DOM tree generation method and an electronic device. The method is applied to an electronic device. When a Web application loads a webpage comprising a Web component, the Web component is a file in a target format, the file in the target format is a file recognizable by the electronic device, and thus, when a rendering engine invokes the Web component, the file in the target format can run directly in the rendering engine. In addition, the rendering engine comprises a function set used for creating a DOM tree of the Web component, the rendering engine can generate a rendering context used for indicating an entry of the function set, and thus, the rendering engine can invoke a function in the function set via the Web component and the entry of the function set, thereby directly acquiring, within the rendering engine, the function used for creating the DOM tree, and then completing the creation of the DOM tree within the rendering engine. Thus, interaction between the rendering engine and a node on the DOM tree of the Web component no longer needs to be performed via an execution engine, thereby significantly saving data binding overhead and conversion overhead.

The invention discloses an intelligent fault tree generation method based on cooperation of a multi-modal large model and a large language model, and relates to the field of fault tree analysis. In order to solve the defects of low tree building efficiency, insufficient cross-modal information processing and incomplete fault causal chain reasoning in the prior art, the technical scheme provided by the invention comprises the following steps: carrying out topological structure analysis on a system flow chart by adopting a multi-modal large model to obtain an equipment network table; taking the equipment network list as input, and performing fault mode directional retrieval on the equipment information base by adopting a large language model to obtain a fault mode list; taking the equipment network list and the fault mode list as input, performing failure reason reasoning by adopting a large language model, and establishing a fault causal chain from a system layer to an equipment layer; and taking the fault causal chain as input, constructing a fault tree by adopting a large language model, and generating a complete fault tree structure from a system top event to an equipment basic event. The method is suitable for safety and reliability analysis work of a complex industrial system.

The present disclosure relates to a card interface generation method, device, system and related equipment, and relates to the field of computer technology. The method includes: receiving layout information of a card interface, the layout information including one or more components; generating a virtual view tree including one or more virtual nodes according to the layout information; generating a layout engine node tree according to the virtual view tree, and assigning the view attribute information corresponding to each virtual node in the virtual view tree to the corresponding node of the layout engine node tree; using a cross-platform layout calculation engine to calculate the view attribute information applicable to each node in the native view tree according to the layout engine node tree; generating a native view tree according to the virtual view tree, and assigning the calculated view attribute information applicable to each node in the native view tree to the corresponding node of the native view tree; and rendering and generating a card interface according to the native view tree. The present disclosure can realize the dynamic update of the card interface layout style without modifying the code.

The invention discloses a reminding strategy generation method and device, a storage medium and computer equipment, relates to the technical field of data processing, can be applied to the field of finance, and mainly aims to solve the problem of low reminding strategy generation accuracy. The method mainly comprises the steps of obtaining user attribute information, historical repayment data and account operation behavior data of a to-be-reminded user, and social environment data in a preset historical time period; the social environment data, the historical repayment data and the account operation behavior data are predicted through a repayment success rate prediction model, a repayment success rate confidence interval is obtained, and the repayment success rate confidence interval is used for representing the repayment success rate range of the to-be-reminded user under the preset confidence coefficient; and according to the user attribute information and the repayment success rate confidence interval, generating a target reminding strategy of the to-be-reminded user through a pre-constructed hierarchical rule tree. The method is mainly used for generating reminding strategies.

The present invention uses an error cause inference device including: a data preprocessing section that generates training data having a format suitable for input to a machine learning model using processing target data; and a model tree generation section that generates a learning model for detecting an error, i.e., an error detection model, with the training data as input, and generates a model tree that expresses relationships between error detection models using a tree structure with error detection models as nodes. Thereby, even without adding labels to error causes in advance, it is possible to generate learning models that detect errors by various types of errors that occur.

A system for inducing taxonomy based on a data sample and an inference classification of raw data (506A) using the induced taxonomy (IT). includes processing arrangement (PA) (106) using set of modules selected from: a segmentation module configured to segment data sample into ontological segments a clustering module configured to cluster ontological segments into ontological clusters (206); a subtree generation module configured to large language model to generate subtree (208, 302) for each ontological cluster; and a taxonomy construction module configured to induce taxonomy comprising root node (210A, 302A, 304A, 702) and combination of subtrees. The PA includes a classification module configured to map IT to set of label configuration objects (504A, 602A-D); and classify raw data using a set of label configuration objects derived from mapped IT. Included is computer-implemented method for inducing taxonomy based on data sample and inference classification of raw data using IT.

The embodiment of the invention provides a clock tree generation method and a chip, and relates to the technical field of integrated circuits, and the method comprises the steps: determining a plurality of groups of sub-clock trees according to the node position of a clock tree and a preset grouping rule; and performing clock wiring based on the multiple groups of sub-clock trees and the selectable driving units to obtain a clock tree, the number of clock tree nodes in each group of sub-clock trees being determined according to the driving capability and the driving distance of the selectable driving units. Therefore, the problem of large clock skew caused by the fact that nodes in a clock tree deviate from a symmetrical structure due to the fact that various devices exist in a chip in a traditional Htree clock can be solved, and the effect of high-speed and stable transmission of clock signals is achieved.

Some embodiments of the invention provide a method for defining code-based policies. The method generates a policy-builder first view of a policy for display in a graphical user interface (GUI) by processing a syntax tree that is generated from a code second view of the policy. The method receives, through the policy-builder first view, a modification to a portion of the policy. To reflect the modification, the method updates a portion of the syntax tree that corresponds to the portion of the policy that is affected by the modification. Based on the updating of the syntax tree, the method updates the code second view by modifying a portion of the code second view that corresponds to the updated portion of the syntax tree.

The invention discloses a multi-modal multi-hop question and answer method, device and system and a storage medium, a reinforcement learning teacher is combined with an implication tree, a student model is distilled to improve the generation quality of the implication tree, and multi-path generation is introduced to improve the generalization ability; and further performing iterative reasoning on the sub-questions in the implication tree by using multi-modal expert iteration, and continuously updating the intermediate answers. By the adoption of the technical scheme, the multi-modal multi-hop question and answer accuracy and the implication tree generation quality are improved.

The application provides a message conversion code generation method, related device and computer storage medium, the method comprises the following steps: respectively analyzing an XML schema definition source file and a target XML schema definition file to obtain an XML schema definition source file object tree and a target XML schema definition file object tree; generating a first hypertext markup language tree according to the XML schema definition source file object tree in a preset format; generating a second hypertext markup language tree according to the target XML schema definition file object tree in a preset format; showing the first hypertext markup language tree and the second hypertext markup language tree to a user; receiving a mapping relationship group of nodes in the first hypertext markup language tree and nodes in the second hypertext markup language tree edited by the user; and generating a message conversion code according to the mapping relationship group of the nodes in the first hypertext markup language tree and the nodes in the second hypertext markup language tree. Thus, the development work is assisted.