54 results about "Verbnoun" patented technology

The invention relates to the technical field of intelligent question answering, in particular to a knowledge tracking and evidence labeling combined RAG question answering system which comprises a semantic analysis module, a statement positioning module, a knowledge path calibration module, an evidence index module and an enhanced question answering module. According to the method, through structural analysis of natural language input and extraction of clear verb semantics, index entities and time normalization expression, it is ensured that input statements have uniformity and processing consistency in the structural level, through a text segment screening strategy based on labels, the text scanning range is effectively limited, the index positioning precision and efficiency are improved, and the method is suitable for popularization and application. A causal node link with statistical significance in a text is clearly extracted, and index combination constraint and identification labeling are performed on key sentences in path nodes, so that the index cross coverage of candidate evidence fragments is enhanced, and the density of index integration in answers and the consistency of a logic sequence are improved.

The invention relates to the technical field of artificial intelligence education, in particular to a Russian spoken language practice personalized recommendation method and system based on artificial intelligence, and the method comprises the steps: 1, outputting a phoneme sequence with a timestamp through Russian automatic voice recognition; 2, collecting an exercise interruption position and repeated read-after behavior data; 3, generating a dynamic learner portrait; 4, mapping high-frequency errors in the learner portrait into abnormal path weights of map nodes; 5, a lattice tail error option and a non-matching body verb interference item are injected; 6, when the voice fluency attenuation of the learner exceeds a dynamic threshold value, the sentence complexity is reduced; and 7, calculating an error rate descent gradient based on the exercise completion data, and dynamically adjusting the abnormal path weight of the knowledge graph. Through audio stream analysis and syntax tree construction, the system can accurately identify errors of the learner in grammar, pronunciation and other aspects, and the learning efficiency is improved.

The invention relates to the technical field of natural language processing, in particular to an AIGC content safety monitoring system and method based on dynamic reasoning and context awareness, and the system comprises a semantic graph construction module which is used for extracting entity nouns and predicate verbs in a text according to a received AIGC interaction text flow, generating a semantic concept node set, and sending the semantic concept node set to a database; and performing directed connection and hierarchical nesting on the concepts in the semantic concept node set according to a logic direction according to a subject-predicate-object dependency relationship rule. According to the method, the curvature value of the semantic track is calculated, and the similarity between the direction vector and the center of the sensitive semantic cluster is combined for double verification, so that sudden turning of an intention in a dialogue process or progressive induction to a sensitive field can be perceived, and abnormal mutation can be recognized through a curvature pulse form; therefore, hostile attack behaviors are accurately captured in real time in dynamic interaction, and the defense capability for context dependent attacks and implicit induction behaviors is improved.

A method for generating a knowledge map includes: extracting, as main entities, words by applying a key-phrase-extraction language model to the document; extracting a verb representing a relationship between main entities as a relational verb by performing dependency parsing on a sentence including the main entities; clustering the extracted relational verb into clusters to generate a relational verb dictionary; generating a knowledge triplet including a first entity and a second entity among the main entities and a cluster identifier indicating a relationship between the first entity and the second entity based on the relational verb dictionary; and generating the knowledge map based on the knowledge triplet.

This invention relates to the field of intelligent question answering technology, specifically to a RAG question answering system combining knowledge tracking and evidence annotation. The system includes a semantic parsing module, a sentence localization module, a knowledge path annotation module, an evidence indexing module, and an enhanced question answering module. This invention extracts explicit verb semantics, indicator entities, and time-normalized expressions through structured parsing of natural language input, ensuring structural uniformity and processing consistency of the input sentences. A tag-based text filtering strategy effectively limits the text scanning range, improving the accuracy and efficiency of indicator localization. It clearly extracts statistically significant causal links from the text, and enhances the cross-coverage of indicator fragments by imposing indicator combination constraints and labeling key sentences in path nodes, thereby improving the density and logical order consistency of indicator integration in the answer.

The invention relates to the technical field of brand sentiment analysis, in particular to an artificial intelligence-based brand monitoring system, which comprises a brand word path extraction module, a verb target positioning module, a continuous chain construction module, a stand turning detection module and an intelligent fusion judgment module. According to the method, the dependency structure and the syntactic relationship are introduced into the semantic path, so that the semantic association between the brand word and the verb can be identified and modeled in a more targeted manner, the judgment of the verb target is guided to be more semantic hierarchy and context dependency, and the time sequence connection of brand behaviors is effectively realized; the recognition accuracy of continuous brand behavior nodes in a text is improved, dynamic tracking of emotional standing is achieved by recognizing standing turning features in sentences, and standing fusion phenomena in user emotion expression are captured through sequential change of verb and emotion combinations in a path structure and switching of pointing objects, so that the emotion expression efficiency is improved. The information insight effect of emotional expression steering and behavior continuity in the brand monitoring process can be improved.

This invention relates to the field of information retrieval structure technology, specifically to a method and system for monitoring data during the investment promotion process in industrial parks. The method includes the following steps: extracting investment promotion text, identifying combinations of verbs and resource nouns, analyzing word order and semantic features, filtering action-driven segments, dividing structural sequences and identifying connection relationships, establishing semantic jump paths, reorganizing sentence order, and generating a data monitoring structure template for investment promotion in industrial parks. In this invention, by extracting verbs and resource nouns to construct sentence content, combining word order features and semantic tags to classify and filter segments, dividing structural sequences based on the position of resource nouns and merging content with consistent semantic direction, mapping connectors to jump paths to construct task behavior sequences, and realizing the logical organization and sequential reorganization of sentences, this generates a data expression method with traceability and structured features, improving the semantic recognition efficiency and data monitoring capabilities during the investment promotion process in industrial parks.

The invention discloses a syntactic selection simulation method, system and equipment based on event structure and syntactic frequency interaction. The method belongs to the technical field of dynamic simulation of Chinese syntax generation, and comprises the following steps of: 1, analyzing a question element role relationship of an input event, and generating an event structure vector; 2, calling a syntactic frequency database, and obtaining the use frequency weight of the candidate sentence pattern; 3, calculating the verb semantic distance between the target event and the historical event; 4, dynamically generating a syntactic selection probability through interaction; 5, when the events are the same and verbs are multiplexed, the syntax selection probability is adjusted. Through multi-dimensional interactive modeling of the event structure, the syntactic frequency and the semantic information, more accurate and natural syntactic selection simulation conforming to human language behavior rules is realized, and the intelligent level and simulation authenticity of a language generation system are remarkably improved.

This invention discloses a slow-fast diversity-aware prototype learning method for egocentric action recognition. This method utilizes a part-to-prototype (P2P) module and a slow-fast contextualization (SFC) mechanism. In P2P, partial tokens obtained from each frame by the video converter are further interacted with several initial prototypes through diversity-aware attention, refining / extracting the semantic information of the interacting objects from the partial level to the prototype level. In SFC, slow and fast awareness attention is introduced to interact with the original prototypes to finely supplement semantic information. Three streaming features are aggregated using slow and fast gates, ultimately yielding classification results for nouns and verbs.

A system is provided.SOLUTION: A system comprising: means for acquiring a text from a web page; means for estimating a reference source of a pronoun based on a context and inserting the reference source instead of the pronoun; means for replacing a homophone with a synonym in accordance with the context; means for adjusting an order of a verb, an object, and a subject; means for recursively repeating the above to increase a degree of the text; and means for storing and outputting the converted text.SELECTED DRAWING: Figure 1

The application belongs to the technical field of scientific and technological information processing, and provides a method and system for determining a cause-effect relationship based on a scientific and technological information analysis knowledge graph. The method comprises the following steps: determining a first verb, a second verb and a scientific and technological information text segment to be processed, performing vector conversion to obtain a first verb embedding vector, a second verb embedding vector and a first sentence embedding vector, performing vector merging and attention operation to obtain a first transformation matrix, performing first transformation processing on the first transformation matrix to obtain a second sentence embedding vector; after performing second transformation processing on the first sentence embedding vector and the second sentence embedding vector, performing SVD decomposition processing, inputting the obtained left singular matrix into a verb cause-effect relationship prediction model, and outputting a cause-effect relationship analysis result of the first verb and the second verb. The application can focus on learning relevant key information of the first verb and the second verb, reduce information redundancy, and improve the classification accuracy of the cause-effect relationship.

The invention relates to the technical field of intelligent document review, in particular to an intelligent document review method and system based on large model fusion causal reasoning, and the method comprises the steps: collecting documents, extracting formats and null lines, recognizing roles and actions, retrieving nouns after verbs, processing semantic repetition, outputting a table, checking causal connections, comparing action sequences, screening and joining, ranking verbs, and pulling through actions. And outputting causal fragments, checking consistency, separating objects, calibrating behaviors, outputting chain fracture, splitting adverbs, sorting relationships, and outputting conflict paths and review paths. According to the method and the device, by extracting the paragraph formats, roles and actions of the documents, the meticulousness of review is improved. And analyzing a causal conjunction and an action relationship, and identifying a causal relationship and a semantic conflict. The method comprises the steps of calibrating an action sequence, identifying missing parts, sorting multiple actions and role changes, optimizing an examination path, reducing manual intervention and improving efficiency.

The invention discloses an English sentence generation method based on a continuation theory and an intelligent system thereof. The method belongs to the cross technical field of artificial intelligence and computer-aided language learning. The technical problems that an existing language generation model lacks bilingual learning theory guidance, so that generated sentences are low in communication validity, and the deep semantic relation cannot be intelligently reflected are solved. According to the technical scheme, the method comprises the steps of receiving verbs and context parameters input by a user; calling a large language model, and activating a mapping network containing nine adversities in three dimensions of materialization, rationalization and dialectization; a multi-modal optimization mechanism is adopted and comprises a corpus-based adversity position adjustment sub-module, an error prediction-cognitive enhancement cycle sub-module, a semantic association enhancement sub-module and a weight distribution optimization sub-module, and collaborative screening and optimization are carried out on adversity combinations; and outputting the English sentence with the enhanced communication function. The method is mainly used for core engine construction of intelligent writing assistance, a self-adaptive language teaching system and cross-cultural communication software.

A system and method are provided for explaining ontological sub-graphs. The system and method include querying an ontology to determine a match between a query graph and a portion of an ontology graph. When there is a match, a subgraph representing the match is first translated into a simple summary using a simple language (e.g., triplets which include a subject and object corresponding to pairs of connected nodes in the subgraph and a verb / predicate representing a relation / edge in the subgraph that connect the pair nodes). This simple summary is then fed, as part of a prompt, to a large language model (LLM) that generates a human-readable summary based on the prompt.

A computer device that manages privilege delegation is disclosed. The computing device can insert a custom verb command into a plurality of verb commands corresponding to a file. The computing device can intercept a request to execute the custom verb command on the file by intercepting a request to create a context menu. The computer device can obtain information related to the request to execute the custom verb command by obtaining a file identifier of the file from the request to create the context menu. The computer device can determine whether to execute the custom verb command on the file according to second privileges different from the first privileges based on the information related to the request to execute the custom verb command. The computer device can cause the custom verb command to be executed on the file according to the second privileges.

Methods and systems provide for extracting next step sentences from a communication session. In one embodiment, the system receives a transcript including sentences produced during a communication session. The system classifies, using a trained classification model configured to identify next step sentences, one or more sentences in the transcript as next step sentences. Each next step sentence includes a first-person pronoun and a verb having a lemma corresponding to a predetermined set of actionable verbs. The system determines, based on the one or more sentences classified as next step sentences, one or more analytics comprising a number of next step sentences associated with a participant of the communication session. The system displays, via a user interface, the one or more analytics.

The invention relates to the technical field of natural languages, and provides a semantic construction and execution method of a natural language, which comprises the following steps of: performing structured analysis on a natural language statement, identifying subject, action and object semantic units, and establishing logic relation mapping among the semantic units; calling a context adaptation strategy according to the application scene features, and adjusting the technical term expression precision of the semantic unit; selecting a matched action verb intensity level from a verb professional pedigree dictionary based on role attributes in a user portrait library; adding an action initiator prefix, an execution main body prefix or a state suffix through the relation explicit rule base; when the modification relation exists, a hierarchical assembly mode is adopted; when the main-object-object linear relation is adopted, a linear assembly mode is adopted; converting the assembled semantic units into recognizable executable statements, and executing the recognizable executable statements; when the execution fails, positioning an abnormal semantic unit; generating a correction statement according to the correction rule; and reassembling the corrected statement.

The invention relates to the technical field of text proofreading, in particular to an intelligent text proofreading method and system based on cognitive grammar, and the method comprises the following steps: collecting semantic expressions such as verb affairs, matching a standard graph expression for verification, executing word order reconstruction, limiting pronoun pointing, and automatically generating a proofreading result. According to the method, a semantic structure label system is established by collecting verbs, position words and grammatical relations, classification and integration of sentence pattern semantics are achieved, consistency verification is conducted by matching cognitive structure library standard graphic configuration, semantic mismatch structure structures can be recognized and recombined, potential fracture links can be positioned by tracking word semantic mutation points, and the recognition accuracy is improved. The word order is reconstructed and optimized to achieve ordered expression of the logic relation, the grammar defect position is defined through difference comparison between the reconstructed fragment and the correction item, the pronoun logic definition and sentence pattern expression accuracy are enhanced, the recognition and correction capacity of hidden semantic errors in diversified texts is improved, and the text proofreading effect is greatly improved.

The invention provides a personal information synonym library construction and information collection automatic understanding method in a Chinese privacy policy, which comprises the following steps: defining the type of personal information needing to be analyzed, appointing an initial synonym, constructing and training a Chinese text word vector model, and obtaining a Chinese text word vector model; constructing a personal information synonym library based on the similarity between each human information phrase and the word vector of the initial synonym; performing word segmentation, part-of-speech tagging and dependency syntactic analysis on a Chinese privacy policy to be analyzed by using a natural language processing technology, performing simplification based on verbs indicating personal information collection and a tagging result in the previous step, and extracting phrases describing personal information collection; and for each type of personal information in the personal information synonym library, generating a regular expression capable of covering the synonym expression of the personal information, matching the extracted phrases, and mapping the extracted phrases into uniform personal information representation. The method is helpful for analyzing the illegal collection behavior of the personal information in the application.

The invention discloses a self-adaptive action and object decoupling method and system for combined action recognition, and relates to the technical field of action recognition, and the method comprises the steps: obtaining video frames, carrying out the extraction of the video frames, obtaining video features, inputting the video features into a pre-established action encoder and an object encoder respectively, action semantic features and object semantic features are respectively output, and the semantic features comprise semantic-related motion features and semantic-independent motion features; performing feature optimization and alignment on the action semantic features and the object semantic features based on an adversarial independence constraint mechanism and a double-branch cross-modal alignment mechanism, and outputting the optimized action semantic features and object semantic features; and performing joint reasoning prediction on all candidate verb and object combinations based on the optimized action semantic features and object semantic features to obtain prediction results of the verb and the object, and fusing the prediction results of the verb and the object to obtain a final combination score.

Described are techniques for automated least privilege role definition. The techniques include enumerating access patterns including a subject, a verb, an object location, and an object type of respective Application Programming Interface (API) calls in source code associated with a binary program. For a first function call in the source code, the technique is configured to generate a first object type based on an API definition associated with the function call, a first verb based on an API-to-verb matching database, a first subject based on a program-to-subject mapping database and the binary program, and a first object location based on the API definition associated with the function call. The technique further includes generating a Role Based Access Control (RBAC) role definition based on the enumerated access patterns.

The invention relates to the technical field of archive data processing, in particular to an archive data processing method and platform based on cloud computing and electronic equipment, and the method comprises the steps: collecting and preprocessing enterprise task data and enterprise conference data; storing enterprise conference data and constructing a verb weight matrix to judge a verb type, and determining a verb confidence coefficient according to the verb weight matrix and the verb type; determining a time attenuation factor, a semantic similarity and a co-occurrence frequency factor according to the enterprise task data and the enterprise conference data; and according to the time decay factor, the semantic similarity, the co-occurrence frequency factor and the verb confidence coefficient, analyzing the conference association strength and the noun association strength, and according to the conference association strength and the noun association strength, constructing a conference association model to generate a conference tag. According to the invention, accurate classified storage processing of enterprise archive data is realized.

The invention relates to the technical field of illusion suppression, in particular to a language model illusion suppression dynamic decoding method based on a multi-dimensional contrast signal, which comprises the following steps of: acquiring a language model input condition, extracting a word group connection relationship and promoting word item output, identifying a grammar sequence and an attachment mode, extracting an entity attribute and comparing reference time. And judging a semantic sequence, analyzing an action connection relationship, screening paths with the same structural form, expanding to next statement action construction, and introducing guidance to obtain a dynamic control signal set. According to the method, a word order and grammar dependency are sorted by constructing a lexical item path, a dynamic contrast mechanism is established in combination with entity reference time and knowledge node updating time, an action sequence is promoted by relying on verb phrases and conjunctions, inter-sentence repeated main sentences and structural convergence fragments are recognized, and a language skeleton with stable features is screened; time and action signals are introduced to guide the generation process, and semantic organization coherence, inter-sentence structure collaboration and content time sequence consistency are enhanced.

The application relates to the technical field of archive data processing, in particular to an archive data processing method and platform based on cloud computing and electronic equipment, the method comprising the following steps: collecting enterprise task data and enterprise meeting data and preprocessing; storing the enterprise meeting data and constructing a verb weight matrix to determine the verb type, and determining the verb confidence according to the verb weight matrix and the verb type; determining a time attenuation factor, a semantic similarity and a co-occurrence frequency factor according to the enterprise task data and the enterprise meeting data; analyzing the meeting correlation strength and the noun correlation strength according to the time attenuation factor, the semantic similarity, the co-occurrence frequency factor and the verb confidence, and constructing a meeting correlation model according to the meeting correlation strength and the noun correlation strength to generate a meeting label. The application realizes accurate classified storage and processing of enterprise archive data.

The invention discloses a thinking training system and method based on semantic unit cross-language conversion, and belongs to the field of intelligent education technology and natural language processing cross technology. The system includes a semantic chunk divider, a conversion processor, and a cognitive adapter. The semantic chunk divider adopts a dual verification mechanism of dependency syntactic analysis and semantic role labeling, and a predicate verb is taken as a core to divide a complete semantic unit; the conversion processor constructs a semantic intermediate representation based on a graph structure, and maintains a logic relationship between semantic units in cross-language conversion; and the cognitive adapter monitors the cognitive load of the user in real time and dynamically adjusts the complexity of the semantic unit. Through triple technical means of semantic unit division, graph structure conversion and cognitive dynamic adaptation, visualization of the cross-language thinking conversion process and personalized adaptation of training content are achieved, and the black box problem and the language training rigidity problem of an existing machine translation system are effectively solved.

A computer device that manages privilege delegation is disclosed. The computing device can insert a custom verb command into a plurality of verb commands corresponding to a file. The computing device can receive a request to execute the custom verb command on the file selected from a context menu for the file, wherein the context menu comprises the plurality of verb commands. The computing device can obtain information related to the request to execute the custom verb command by obtaining a file identifier of the file from the request to create the context menu. The computing device can determine whether to execute the custom verb command on the file based on the information related to the request to execute the custom verb command. The computing device can cause the custom verb command to be executed on the file according to the privileges different from a current user account.

The application relates to the technical field of information retrieval, in particular to a Chinese language and literature database online query reading method and system, which comprises the following steps: extracting a word meaning item, a literature reference, a meaning length and a boundary mark, screening a candidate set, analyzing a subject pronoun and a verb collocation, positioning a paragraph and marking a word meaning item position, extracting a phrase structure comparison version offset, marking a keyword meaning number and a position, outputting a meaning, a source and a semantic path, and generating a comparison prompt; in the application, the positioning, display and structure alignment of the literature are optimized through semantic mapping, the accuracy and consistency of the target literature are improved, relevant content is accurately screened in combination with context information and version comparison, the structure offset between versions is automatically adjusted, the dependence on manual keyword setting is reduced, meanwhile, the generated word meaning comparison prompt group is optimized to improve the literature retrieval experience, the user can more quickly and accurately understand the word meaning and context relationship, and the information acquisition precision and efficiency are improved.

The goal is to provide methods and systems that enable children learning English for the first time to understand the language. [Solution] The English learning system 10 is characterized by comprising: a subject identification processing unit 12 that distinguishes words corresponding to the subject in an English sentence from other words using a first color; a general verb identification processing unit 14 that distinguishes words corresponding to general verbs in an English sentence from other words using a second color; a be verb identification processing unit 16 that distinguishes words corresponding to be verbs in an English sentence from other words using a third color; and a color English instruction unit 18 that uses the first, second, and third colors to help children visually understand the basic structure of English sentences.

A video manual generation device includes a document analysis unit, a video analysis unit, a link information generation unit to collect first sets each being a set of a noun and a verb from text information data, to collect second sets each being a set of an object and an action from object information data and action information data, to search those sets for a first set and a second set in which the noun and the object correspond to each other and the verb and the action correspond to each other, and to generate link information data indicating correspondence between a position in the work procedure where the first set obtained by the search is described and a scene in a video that includes the second set obtained by the search, and a video manual generation unit to generate video manual data based on the link information data.

The invention relates to a method for analyzing a language structure by using a language expression, which is suitable for analyzing structures of more than 7,000 languages on the earth. The method comprises the following steps of: analyzing a morphologic element and a syntactic structure of a target sentence by a morphologic element and syntactic analysis unit; and based on a pre-training language expression learning algorithm provided by a language expression learning algorithm unit, a language expression calculation unit generates a language expression for the morphologies and syntactic structures of the sentences. Wherein the language expression calculation unit is used for dividing a sentence into an upper left area, a lower left area, an upper right area and a lower right area by taking a sentence center symbol as a benchmark, a subject symbol is distributed in the upper left area, a core verb symbol is distributed in the lower left area, and a verb type symbol is distributed in the lower right area; non-predicate symbols representing remaining phrases other than subjects and verbs are assigned to the right upper region. Furthermore, symbolization specific information including marks (1-4) indicating a person and a character number mark (.) indicating the number of word characters such as nouns and adjectives is added to at least one of the left upper mark, the left lower mark, the right upper mark and the right lower mark of each symbol. By means of the method, the sentences in the specific language can be accurately analyzed into structured syntactic expressions, and therefore the efficiency of language processing such as sentence recognition, semantic understanding, translation and retrieval is improved.