56 results about "Parse tree" patented technology

According to the artificial intelligence-based data analysis system and method provided by the invention, a set of novel data analysis system architecture is designed, and key technical components such as natural language processing, a large language model, database query optimization, multi-modal visualization and a semantic knowledge graph are fused; data transmission between modules is realized through unified intermediate data objects such as a structured query intention, an analytic tree and a structured query language template object, and asynchronous collaboration is realized through event driving and a message queue mechanism, so that a non-professional user can input an analysis request through a natural language; semantic analysis, structured query language query statement generation, data query and result visualization presentation are automatically completed, the method can be widely applied to data analysis scenes in the industries of government affairs, traffic, finance, education and the like, the data use efficiency is improved, the technical threshold is reduced, and the digital decision-making ability is enhanced.

The invention relates to the field of wisdom education, and particularly discloses a teaching strategy optimization model and grammar error early warning method based on data mining, and the method comprises the following steps: S1, obtaining original code data in a student code library in real time, and preprocessing the original code data to obtain a structured data matrix; s2, for the structured data matrix, generating a grammar parse tree through a grammar parser, positioning error nodes and extracting context features by using a node traversal algorithm, and constructing a single-error multi-dimensional feature vector; meanwhile, an error association rule base is constructed based on historical error data, a causal relationship across error types is identified, and dynamic knowledge graph data is formed. According to the technical scheme, association analysis and deep mining can be carried out on the multi-source learning data, dynamic solution suggestions for student individual errors or group generality errors are formed, and teachers are assisted to quickly adapt to dynamically changing learning requirements of the students.

The invention is suitable for the technical field of data query, and provides an index query method and device, electronic equipment and a storage medium, and the index query method comprises the following steps: obtaining a first type of query language statement input by a user; performing grammar analysis on the first type of query language statement based on a predefined grammar rule to generate a corresponding analysis tree; traversing the analytic tree, identifying a query target in the first type of query language statement, and constructing a query semantic object based on the query target, the query target including one or more of an index and a physical table; and according to the query semantic object, generating a second type of query language statement corresponding to the first type of query language statement for an underlying data system to perform index query. According to the scheme, by introducing the query semantic object and supporting mixed recognition and processing of the index and the physical table, the problems that in an existing query mode, flexibility is insufficient, dynamic parameters cannot be expressed, and multi-source joint query cannot be supported are solved.

The invention relates to the technical field of electric digital data processing, and discloses a method for detecting log abnormity of an electric power dispatching automation system, which comprises the following steps of: constructing a fixed depth analysis tree through historical log data, and extracting a log template based on word segmentation similarity; converting knowledge in the power dispatching field into vectors and storing the vectors into a knowledge base; retrieving knowledge base associated domain knowledge of the log template, inputting the large model to carry out abnormity judgment and marking a template label; after real-time log preprocessing, a template label is inherited through a parse tree matching template library and a self-adaptive threshold strategy, and online template updating is triggered for unmatched logs; and the context and high-frequency parameters of the abnormal log are aggregated, a dynamic cue word is constructed in combination with a retrieval result and a template feature weight, a large model is input for multi-dimensional root cause analysis, and template mechanism optimization is driven based on the cue word. The problems that in the prior art, manual maintenance is difficult, the generalization ability is weak, and the detection speed is low are solved, and the purposes of efficient detection, high accuracy and self-adaption are achieved.

Methods and systems for generating a symbolic model from a markup document, and instantiating a model instance from a symbolic model are described. A markup document containing human language content and mathematical content is parsed into a symbolic model that contains only symbolic code representing an optimization problem. The markup document is parsed to extract a markup declaration, the markup declaration is then processed to a math content span, any metadata entity and any relationship between any metadata entity and the math content span. The math content span is processed into a math content parse tree. The math content parse tree is converted into symbolic code of the symbolic model using any relationship between the metadata entity and the math content span. The symbolic model can be instantiated using data definitions.

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 intelligent question answering, and particularly relates to an experimental question answering method and system based on a knowledge graph. The method comprises the following steps of: generating a candidate combination category grammatical analysis tree for an input experimental question statement, and when vocabularies outside a preset dictionary are encountered, assigning a temporary combination category in combination with word vectors and adjacent entity types; calculating the syntactic probability of the analysis tree and the node intensity of the entity subgraph in the tree, determining a target syntactic analysis tree, and converting the target syntactic analysis tree into a logic expression; extracting an anchor point entity and a semantic relationship, determining a search depth according to sub-graph intensity, and constructing an initial graph query statement by utilizing bidirectional breadth-first search; if the query result does not exist, differential query reconstruction is carried out according to an intensity threshold value, when the intensity is high, only the semantic relation is replaced with a parent class, otherwise, the parent class and brother class relation is considered at the same time, and a sub-graph or an entity obtained through query is output as an answer. According to the method, the suitability, accuracy and fault tolerance of the experiment question-answering system can be improved, and the query efficiency and the recall rate are balanced.

The present application relates to a method, device, system, and storage medium for determining a water supply price reference index based on a large language model. The method comprises obtaining a first water supply price language data sample; grouping individuals, deleting the first water supply price language data sample corresponding to invalid individual groups, and obtaining a second water supply price language data sample; parsing each second water supply price language data sample to obtain a parse tree; grouping the second water supply price language data samples according to the parse tree; calculating and sorting the group weights; calculating the influencing parameters of the parse tree and using the influencing parameters to correct the group weights, and using the corrected group weights as the water supply price reference index. The method, device, system, and storage medium for determining a water supply price reference index based on a large language model disclosed in the present application organize and analyze massive amounts of collected data and obtain results by cleaning and normalizing the collected data.

The application discloses a large language model log analysis method based on relationship inference, comprising: taking a prefix parsing tree as the core, pre-processing the input log, and then traversing the prefix tree to realize template matching. If the matching is successful, the structured log is output, if the matching is unsuccessful, the relationship between the unmatched log and other logs is evaluated from the syntax and semantics. The syntax similarity between the unmatched log and the candidate log set is calculated at the syntax level, the causality strength and the number of shared entities between the unmatched log and the logs in the historical log window are evaluated through LLM at the semantic level, and the semantic correlation log is screened out by combining the semantic composite score; the screened syntax similar and semantic related log is taken as an example to construct a complete prompt containing a task instruction, a demonstration example and a log to be parsed, and a large language model is called to generate a structured template of the unmatched log; the newly generated template is adapted to the prefix parsing tree, the tree structure is perfected through dynamic updating, and more comprehensive template support is provided for subsequent log analysis.

Arrangements for optimization of database queries having multiple views are provided. A query defining multiple views may be received. A parse tree may be generated based on the query. The query may be preprocessed using the parse tree. The parse tree may be traversed to identify the multiple views. View unfolding may be executed to generate a view subtree. The view subtree may be attached to the parse tree and a view query compile tree may be generated. It may be determined whether there is another view defined by the query. In response to determining that there is not another view, the parse tree may be traversed to calculate tree depth. In response to determining that there is another view defined by the query, calculation of the tree depth may be skipped.

The invention belongs to the technical field of biomedical information extraction, and particularly relates to a recurrent neural network multi-tree fusion method in biomedical event extraction. Parsing results of different rule parsers are fused, a syntactic parse tree-based union method is provided, and sub-tree post-processing is carried out for a merging result to ensure the structure simplification and grammar rationality of a sub-tree. The invention provides an isomer branch cutting and node distillation method aiming at redundant subtrees and nodes existing in a combined tree structure. Meanwhile, branch cutting and node distillation operation are adopted, the subtree structure is further simplified, and the effect on binding and regulating complex events is good.

The present application relates to a method, apparatus, computer equipment, storage medium and computer program product for generating a code service call relationship. By traversing the syntax parse tree corresponding to the source code to be detected, the first relationship between the method declaration code module and at least one method call code module in its child node in the syntax parse tree, the second relationship between the method call module and its class and at least one method declaration code module in the corresponding parent class and child class, and the service party to which each code module belongs are obtained, and based on the first relationship and the second relationship, the call relationship table between the code modules in the source code to be detected is determined, and the corresponding service party identifier is added to the code module in the call relationship table to obtain the corresponding code service call relationship table. Compared with the traditional method of obtaining the call relationship between services through the service registration center, this solution obtains the service call relationship in the code by traversing the syntax tree before the code is run, thereby improving the maintainability of the code.

To improve a filtering-type example sentence-driven analysis unit forming one input sentence analysis tree with using, as one input, an OR tree obtained by expressing a plurality of analysis trees obtained through analysis of an input sentence with use of grammar rules in the form of one tree structure and also with using, as the other input, a temporarily exclusive tree obtained by the example sentence or an exclusive three pre-equipped by the apparatus.SOLUTION: In a common word sequence acquisition between an input sentence and an example sentence, a method according to the present invention includes the steps of: acquiring a plurality of common word sequences; designating the minimum number of common words; determining a common word start position in an example sentence tree; and replacing the common word with a common part of speech.SELECTED DRAWING: Figure 1

The invention relates to an automatic interpretation method for security technology specification provisions, which comprises the following steps of: decomposing the specification provisions into single-constraint pair provisions by utilizing a large language model according to a syntactic structure of the specification provisions on the basis of a few-sample thinking chain prompt, and then performing information extraction on the specification provisions on the basis of a prompt project to form a provision dependency graph as an intermediate representation structure; and finally, automatically converting the clause dependency graph structure into a clause parse tree through a clause parse tree generation algorithm, and the automatic interpretation method comprises the following steps: S1, obtaining standard clauses, and hierarchically decomposing the standard clauses based on few-sample thinking chain prompts; s2, performing information extraction on the standard provisions based on the prompt project; s3, generating a clause analysis tree; according to syntactic characteristics of the security technical specification terms, automatic interpretation of the security technical specification is realized by using the large language model, the term parsing tree is generated as a structured representation form of the security technical specification terms, and accurate conversion and efficient application of the security technical specification terms are promoted.

The invention relates to the technical field of natural language processing, in particular to a hierarchical semantic analysis method and system based on a semantic schema, comprising the following steps: automatically acquiring a semantic schema, the semantic schema being composed of a left meaning result, a right grammar component and a semantic component, the right comprising grammar semantic components such as a subject, a predicate, an object and the like, and the semantic component being a semantic component; the left part represents the meaning result of the right part, the left meaning result and the right part jointly form a meaning structure, and semantic nesting is realized based on the meaning structure; performing layer-by-layer matching on the input text based on the semantic pattern library, generating candidate parse tree nodes and constructing a hierarchical semantic structure; and converting the hierarchical semantic structure into a predicate logic expression to form a reasonable logic expression. According to the method, the dependence of a traditional method on domain knowledge is broken through, the robustness, flexibility and interpretability of semantic analysis are remarkably improved, efficient support is provided for tasks such as chapter understanding, ambiguity resolution and causal reasoning, and meanwhile the data and computing power cost is reduced.

This invention relates to the field of electrical digital data processing technology and discloses a method for detecting log anomalies in power dispatch automation systems. The method includes: constructing a fixed-depth parse tree using historical log data and extracting log templates based on word segmentation similarity; converting power dispatch domain knowledge into vectors and storing them in a knowledge base; retrieving knowledge related to the log templates from the knowledge base, inputting it into a large model for anomaly detection, and labeling the templates; after real-time log preprocessing, inheriting template labels by matching the template library with the parse tree and using an adaptive threshold strategy, triggering online template updates for unmatched logs; aggregating the context and high-frequency parameters of the abnormal logs, constructing dynamic prompt words based on the retrieval results and template feature weights, inputting them into a large model for multi-dimensional root cause analysis, and optimizing the template mechanism based on the prompt words. This method solves the problems of difficult manual maintenance, weak generalization ability, and slow detection speed in existing technologies, achieving efficient detection, high accuracy, and adaptability.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an exit scenario output that characterizes an exit scenario for a business enterprise. In one aspect, a method comprises receiving, at an execution engine, data that represents ownership of assets by multiple participants and source code that defines distribution rules of distributing the assets over one or more steps among the multiple participants using a programming language; receiving, at the execution engine, an exit scenario input; automatically parsing, by the execution engine, the distribution rules defined in the source code into a parse tree; and interpreting, by the execution engine, the parse tree to produce an exit scenario output.

A method for training a machine learning model is disclosed, comprising obtaining a training set including multiple sentences and their labeled sets; generating parse trees and label trees for the sentences; determining the total loss of the sentence, which is equal to the weighted sum of the parse tree generation loss and the label tree generation loss; and training the machine learning model using the training set to minimize the total loss. This application also relates to systems, apparatus, and media for training machine learning models and for processing sentences using such machine learning models.

The present invention provides an encoding device that accepts input of an input symbol sequence to be encoded and outputs an output codeword corresponding to said input symbol sequence, wherein: a codebook or parse tree Tk (where k = 0, 1, ..., K-1) included among a plurality of codebooks or parse trees {Tk}k=0 K-1 (where K is an integer equal to or greater than 2) to be used for encoding is formed from the triplet of a symbol sequence, a codeword of given length, and the codebook or parse tree to be used next, and is assigned a mode, which is a set of symbol sequences; and an expanded symbol sequence of said parse tree Tk or codebook satisfies the condition that any symbol sequence included in the mode assigned to said codebook or parse tree Tk is the beginning of a word.

The application discloses a WAF rule evaluation method based on a regular analysis tree, relates to the technical field of WAF rule evaluation, and collects regular expression protection rules of an open source WAF as seeds, analyzes and constructs an expression library based on a regular analysis tree, then performs SQL syntax word recognition on a sent test expression, matches all related expressions in the rule expression library through SQL syntax words, traverses the sent expression request, judges whether the target site WAF protection rule is bypassed according to site feedback information, and further evaluates the rule protection capability of the target WAF system. The application can quickly and accurately deduce the target site WAF protection rule, and can reliably and accurately evaluate the protection capability of the target site WAF system.

One aspect of the present application provides a method for determining check results of scripts, the check results of scripts comprising error detection results in scripts and consistency matching results of scripts, the method comprising the steps of: determining a plurality of data units in each of a plurality of scripts, constructing an analytic tree structure of each script based on the plurality of data units in each script; performing layer sequence traversal detection on each layer in the analytic tree structure of each script by utilizing a preset detection rule to obtain an error detection result in each script; and obtaining at least on the basis of matching partial data subunits in the data unit corresponding to each hierarchy in the parse tree structure of one of the plurality of scripts with partial data subunits in the data unit corresponding to the corresponding hierarchy in the parse tree structure of another of the plurality of scripts, according to the matching result, the consistency matching result of one script and the other script is determined.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an exit scenario output that characterizes an exit scenario for a business enterprise. In one aspect, a method comprises receiving, at an execution engine, data that represents ownership of assets by multiple participants and source code that defines distribution rules of distributing the assets over one or more steps among the multiple participants using a programming language; receiving, at the execution engine, an exit scenario input; automatically parsing, by the execution engine, the distribution rules defined in the source code into a parse tree; and interpreting, by the execution engine, the parse tree to produce an exit scenario output.

In an embodiment, a computer stores and operates a logic encoder that is an artificial neural network that infers a fixed-size encoded logic from textual or tokenized source logic. Without machine learning, a special parser generates a parse tree that represents the source logic and a fixed-size correctly encoded tree that represents the parse tree. For finetuning the logic encoder, an encoded tree generator is an artificial neural network that accepts the fixed-size encoded logic as input and responsively infers a fixed-size incorrectly encoded tree that represents the parse tree. The neural weights of the logic encoder (and optionally of the encoded tree generator) are adjusted based on backpropagation of error (i.e. loss) as a numerically measured difference between the fixed-size incorrectly encoded tree and the fixed-size correctly encoded tree.

The application relates to an ANTLR4-based code generator design method and belongs to the field of code generation. The application generates a lexical analyzer and a syntax analyzer corresponding to an IDL syntax rule file; an IDL file is pretreated, the pretreated IDL file is generated into a syntax analysis tree through the lexical analyzer and the syntax analyzer, and the syntax analysis tree is further generated into structured data; a public interface file for generating C / C++, JAVA files is defined; the C / C++, JAVA public interface file reads a project template file, and structured data in the template file is replaced with structured data in step S2 to generate C / C++, JAVA project files. The application realizes the application of cross-platform and cross-language data distribution services.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an exit scenario output that characterizes an exit scenario for a business enterprise. In one aspect, a method comprises receiving, at an execution engine, data that represents ownership of assets by multiple participants and source code that defines distribution rules of distributing the assets over one or more steps among the multiple participants using a programming language; receiving, at the execution engine, an exit scenario input; automatically parsing, by the execution engine, the distribution rules defined in the source code into a parse tree; and interpreting, by the execution engine, the parse tree to produce an exit scenario output.

This decoding device decodes a plurality of codewords included in an input codeword sequence using a plurality of codebooks or parse trees in which correspondence between symbol sequences and codewords is recorded. At the same time, the decoding device verifies the correctness of the codebooks or the parse trees used for the decoding on the basis of the decoding result obtained on the basis of a process of decoding at least one of the plurality of codewords while switching, in accordance with a predetermined rule, between the codebooks or the parse trees to be used for decoding.

A device may trigger a resolvable object that requires a resolution responsive to an event detected in a managed information technology environment and obtain a masked title from a title of the resolvable object by applying text processing rules to the title to obtain the masked title that includes at least one variable part that replaces a portion of the title. A device may obtain, using the masked title, a title template for the resolvable object using a machine learning model by traversing a fixed depth parse tree organized based on numbers of token positions in a masked title. A device may obtain, using the title template, a type for the resolvable object and responsive to determining that the resolvable object is of the frequent type and not of the rare type or of the novel type: identifying and automatically executing a runbook of tasks associated with the title template.

The present application discloses a knowledge extraction method, system, device and storage medium, which are applied to the field of data processing technology, including: determining a text corpus and annotating it, constructing an index to obtain an annotated corpus; setting seed data for representing relationship information and retrieving corresponding sentences to determine the sentence's search term distance, the search term's grammatical parse tree distance, and the verb phrase's grammatical parse tree distance; and based on the determined sentence distances, determining the weighted values ​​of each verb phrase in the sentence according to a weight rule; obtaining the K target verb phrases with the highest sum of weighted values ​​by summing up; retrieving each sentence including the target verb phrase from the annotated corpus, and verifying it according to a preset rule; summarizing each sentence after verification into knowledge extraction content corresponding to the seed data. Applying the solution of the present application, knowledge extraction can be effectively performed, and it has high versatility and high recall rate, and can obtain high-quality knowledge extraction content.

A database management system (DBMS) receives an input query and parses the received input query to generate an abstract parse tree. Next, the DBMS traverses the abstract parse tree to detect any parameterized structured query language (SQL) views. If a first parameterized SQL view is detected in the abstract parse tree, the DBMS generates a first view parse tree if a first search of a first cache for the first parameterized SQL view results in a miss. Otherwise, the DBMS retrieves, from the first cache, a previously generated view parse tree if the first search of the first cache results in a hit. Then, the DBMS generates a first query compile tree if a second search of a second cache for the first parameterized SQL view results in a miss. Finally, the DBMS generates and executes a query execution plan based on the first query compile tree.

The invention relates to computing. An information leakage prevention system comprises a server, wherein an intercept subsystem is set up for each data transfer channel, and each intercepted message transfer event or document access event is transmitted to a data extraction subsystem which constructs a parse tree of the event. The root of said parse tree is comprised of the intercepted document, and the other nodes contain information transmitted in the intercepted document, the information in which is in text or image form. The result obtained by the event data extraction subsystem is transmitted to an event data analysis subsystem which analyzes the received data using analysis technologies. The result obtained by the event data analysis subsystem is transmitted to a security policy application subsystem, where security policies apply a security policy configuration to the properties of the intercepted data by comparing policy values with the data analysis result and other event attributes. The technical result consists in reducing the time taken to identify a complete scenario of the development of events that are potentially capable of leading to the leakage of sensitive information.