47 results about "Keyword analysis" patented technology

The invention discloses a resource mining method based on big data, and the method comprises the steps: receiving a retrieval picture keyword of a current user, updating the historical behavior data and picture resource data of the user in real time, carrying out the clustering of the retrieval keyword of the user, and carrying out the classification of the retrieval keyword. The method comprises the following steps: acquiring a retrieval keyword, adding a corresponding retrieval spatio-temporal index for the retrieval keyword, capturing the dynamic change of the retrieval intention of a user, analyzing the feature preference of the user and the current retrieval intention of the user based on historical behavior data and the retrieval picture keyword, and retrieving a related picture from a picture resource library. The method comprises the following steps: obtaining a picture, carrying out feature extraction and classification on the picture, carrying out intention scoring analysis, carrying out descending order arrangement display on screened picture resources based on an intention scoring result, feeding back a retrieval result based on a user, and optimizing a retrieval model. According to the method, the problems of low user intention matching accuracy and picture resource waste are solved.

The invention relates to the technical field of semantic processing and knowledge maps, and provides an AI-based intelligent question-answering method and system, and the method comprises the steps: collecting a knowledge map of an intelligent question-answering library, and obtaining an inquiry text of a user; performing word segmentation on the inquiry text to obtain a plurality of vocabularies; obtaining a reply design scale of the inquiry text; determining the number of analysis queues and establishing a plurality of analysis channels; obtaining the semantic intensity of each marked vocabulary and obtaining a high-intensity semantic vocabulary sequence; quantizing the analysis contribution of each mark vocabulary at each moment and the initial analysis limit at each moment, and further obtaining the buffer semantic integrity retention degree at each moment; judging and establishing a buffer space in real time, adjusting an analysis process, and finally outputting a semantic weight of each vocabulary; and screening a plurality of core vocabularies, obtaining a relation path in combination with the knowledge graph, and further generating a reply text. The invention aims to solve the problem that semantic weight acquisition is inaccurate due to word order interference in text keyword analysis.

The invention relates to the field of data analysis, in particular to a database information acquisition and analysis method for pharmacological analysis of heat stroke, which comprises the following steps: determining a data state according to data diversity and data stability of rat input data, and determining a data processing mode according to the data state; in analog data supplementation, determining a supplementation mode according to a comparison result of the effective standard index proportion and a preset effective standard index proportion; in the keyword analysis, a use state is determined according to the matching frequency and the spacing distance of the effective keywords, and a corresponding search mode is determined according to the use state; in the effective keyword search process, determining a page distribution state according to the page similarity and the information relevancy of the target website, and determining an acquisition adjustment mode as track simulation adjustment or search simulation adjustment according to the page distribution state; the searching and matching efficiency of database information acquisition and analysis in pharmacological analysis related to heat stroke is improved.

The invention relates to the field of data analysis, in particular to an information collecting and processing method for heat stroke pathology data integration based on deep learning, which comprises the following steps: determining the data state of user analysis data according to the data richness of the user analysis data and the image conversion completion degree; when the keyword selection mode is associated phrase selection generation, determining the number of the selected keywords according to the phrase influence coefficient, and selecting the keywords according to the sensitivity coefficient from large to small; when the keyword selection mode is image conversion supplementary generation, determining that a keyword generation mode is generated according to a median point or an outlier according to the feature representation degree of the divided paragraph; under the condition that the initial search is completed, optimization analysis is conducted, the search optimization mode is determined to be combined search or sequential search according to the repeated keyword analysis state, and the pathological data integration search efficiency is improved.

A wearable multifunction device or earpiece or a pair of earpieces includes one or more processors, at least one microphone coupled to the one or more processors, a biometric sensor coupled to the one or more processors, and a memory coupled to the one or more processors, the memory having computer instructions causing the one or more processors to perform the operations of sensing a remaining battery life and based on the sensing, prioritizing one or more of the functions of always on recording, biometric measuring, biometric recording, sound pressure level measuring, voice activity detection, key word detection, key word analysis, personal audio assistant functions, transmission of data to a tethered phone, transmission of data to a server, transmission of data to a cloud device.

The invention relates to the technical field of foreign trade information processing, and provides a multi-language semantic aggregation and automatic quotation system which comprises a multi-language keyword analysis module, a data acquisition module, a semantic aggregation and clustering module, a visual display module, a quotation generation and editable module and an output and mail arrival module. The system has the advantages of high automation, accurate semantics, multi-format output, flexible editing, safety and compliance, easy maintenance and the like, and is suitable for multiple industry fields such as mothers and infants, consumer electronics, pet supplies, industrial equipment and the like.

There are provided systems and methods for sentence level dialogue summaries using unsupervised machine learning for keyword selection and scoring. A service provider, such as an electronic transaction processor for digital transactions, may provide computing services to users, which may be used to engage in interactions with other users and entities. When utilizing these services, memoranda may be generated that includes text from different online interactions. To provide summarization and searching of the memoranda, the service provider may implement an unsupervised machine learning framework that utilizes machine learning models to perform text preprocessing, keyword extraction, and keyword weighting when ranking and outputting relevant keywords. Once extracted and ranked, the keywords may be used to provide different insights to the memoranda. The keywords may be selected based on domains and tasks and the framework may be made pluggable and customizable for different systems and search operations.

The invention relates to the technical field of contract intelligent auditing, in particular to an international trade contract intelligent auditing system based on natural language processing, which comprises a data acquisition preprocessing module, a key vocabulary extraction module, a key vocabulary analysis screening module and a text similarity association module, the data acquisition preprocessing module carries out word segmentation and segmentation on a contract text and a regulation standard text, then the key word extraction module extracts a key word set in each text segment through a word frequency statistical method, and in order to prevent the situation that the key word set extracted by the key word extraction module is inaccurate, the key word set is extracted by the key word extraction module. The key vocabulary analyzing and screening module analyzes the paraphrases of the key vocabularies in the corresponding words, removes the key vocabularies which are not nouns in the key vocabulary set, provides a paraphrasing basis for the vocabulary same paraphrasing mapping unit, unifies same paraphrasing word vectors, and transmits the same paraphrasing word vectors to the key vocabulary same paraphrasing mapping unit; and the contract and the regulation text are deeply associated in terms of vocabulary semantics.

The invention relates to the technical field of data analysis, and particularly provides a keyword-based alarm analysis method and device, a medium and equipment, and the method can comprise the steps: obtaining the occurrence frequency of a keyword in a to-be-processed data stream in a preset time period; obtaining an abnormal parameter of the keyword based on the average frequency of the keyword in the corresponding historical preset time period and a pre-constructed target model; wherein the target model is a distribution class model based on probability statistics; and determining whether alarm information is generated or not according to the abnormal parameters and the occurrence frequency. According to some embodiments of the invention, accurate and automatic monitoring of keyword abnormity can be realized, false alarm and missing alarm of alarm are effectively reduced, and alarm precision is improved.

An information processing device comprises: a keyword extraction unit that extracts a keyword from acquired information; an analysis target trend data generation unit that generates analysis target trend data quantitatively indicating the trend of an analysis target keyword by analyzing the trend of the analysis target keyword from a predetermined viewpoint; and a specific keyword determination unit that, on the basis of the analysis target trend data and past case trend data on past case keywords concerning past cases in which laws or standards were established or revised, determines whether or not the analysis target keyword corresponds to a specific keyword which can be used for predicting the trend of establishment or revision of a law or a standard.

The present invention discloses a method and system for generating a technical trade measure questionnaire based on big data, including obtaining and preprocessing information text data and web traffic data of a trade service platform, performing keyword analysis on the information text data to obtain keyword semantic importance, performing interest analysis on the web traffic data to obtain user interest, constructing a bias analysis function based on the keyword semantic importance and user interest, constructing a question sequence model, embedding the bias analysis function into the question sequence model, simulating the question sequence model, calculating the contribution degree of questions based on the simulation results, determining a questionnaire generation scheme according to the contribution degree of questions, and generating a questionnaire based on the questionnaire generation scheme. This method can not only improve the generation efficiency and quality of the questionnaire, but also has good interpretability and can be directly applied to the technical trade measure questionnaire evaluation system.

The invention discloses a method for establishing an entity object relationship of urban governance elements. The method comprises the following steps of: firstly, dividing urban governance multi-source data into spatial data and non-spatial data; giving spatial codes to the spatial data according to a spatial grid where a central point of the spatial data is located; especially for the planar elements, a tolerance calculation mechanism is introduced, when spatial overlay analysis is carried out, only when the geometric overlapping relation between the planar elements and other spatial elements meets the preset tolerance calculation condition, it is judged that the planar elements have the inclusion relation and correlation is established, and therefore boundary overflow errors caused by surveying and mapping precision are corrected. And for non-spatial data, accurately mounting the non-spatial data to the established spatial entity through address standardization matching of place name address objects or keyword analysis. And finally, on the basis of a unique space code formed by combining the professional identification code, the space identification code and the time identification code, constructing an urban governance element entity object. According to the method, the problems of inaccurate spatial logic judgment and difficult association of non-spatial data in traditional data fusion are effectively solved, and accurate fusion and efficient indexing of urban governance data are realized.

A method and system for automatically labeling training data for cultural resource entity recognition, the method first converts a keyword dictionary into a prefix set through a prefix set construction module; then matches keywords in the original text through a keyword matching module and obtains its position interval information; then solves the problem of keyword position interval inclusion or intersection through an interval merging module and constructs keyword analysis information and writes it into the analysis text; secondly, identifies common entities in the original text through a tool calling module and writes the analysis information into the analysis text; finally, converts the original text into a labeled text with label information through a format conversion module. The system and method can significantly improve the labeling efficiency and greatly reduce the error rate and labeling cost.

The application provides a text abstract generation method, device and system and a storage medium, and belongs to the field of language processing.The method comprises the following steps: preprocessing an original text dataset to obtain title word data and body word data; performing keyword analysis on the title word data and all the body word data by using a trained model to obtain keyword vectors, body word vectors and hidden state data; and performing analysis on the keyword vectors, body word vectors and hidden state data to obtain a text abstract generation result.The application can pay more attention to important information in the original text, can ignore other redundant information, can make the generated abstract cover the key content of the original text to the greatest extent, can reduce the loss of useful information, can fully play the strong semantic information of the document theme and the context information of the document, and thus a text abstract with better quality can be generated.

The invention relates to the technical field of product marketing, and discloses a method and device for analyzing product market characteristics and electronic equipment, and the method comprises the steps: determining an analysis task of a target product, the analysis task comprising a screening target and an analysis target; according to the screening target, screening to obtain target social media data of the target product on the social media platform; based on a large language model, performing keyword analysis on the target social media data according to the analysis target to obtain keyword information; and performing analysis according to the keyword information to obtain market characteristics of the target product. The analysis task can be customized according to different screening targets and analysis targets, so that the analysis result better meets specific business requirements. The big language model is used for carrying out deep text analysis on the social media data, manual intervention is reduced, deeper user intentions and emotional tendencies can be mined, richer market insight is provided, and the analysis efficiency and the analysis depth of product market features are improved.

Embodiments of the present application disclose an interpretable text semantic matching method and device, electronic equipment and a storage medium. The method comprises: obtaining a text to be recognized; performing feature extraction on the text to be recognized and a first candidate text to obtain a plurality of first candidate text segments and a plurality of first sentences, a plurality of second candidate text segments and a plurality of second sentences; performing keyword analysis on each first candidate text segment and each second candidate text segment to obtain a plurality of first target text segments and a plurality of second target text segments; obtaining a plurality of first similarities corresponding to each first target text segment according to each first target text segment and each second target text segment; determining a target text according to the plurality of first similarities, the plurality of first sentences and the plurality of second sentences; and determining each first target text segment and a second target text segment associated with each first target text segment in the target text as explanation information.

This invention relates to the field of intelligent office technology, specifically a BI intelligent voice knowledge graph algorithm. This invention pre-inputs data into a knowledge graph, and operators input data via voice. A speech-to-text converter and keyword analyzer convert the speech into text and extract keywords. By traversing these keywords, corresponding data is found within the knowledge graph, and then the appropriate chart is selected and displayed based on the data type. This process is simple, fast, and requires no training; users can quickly generate data charts simply through voice, offering high timeliness.

The present invention discloses a method, apparatus, and storage medium for realizing efficient regression. The method includes running and loading a first-level control file and storing the test excitation results in a simulation folder; after the test excitation starts, every first preset time period, traversing the simulation folder to view the log file generated by executing the first-level control file; monitoring the excitation process, and switching and loading a second-level control file to re-test the excitation simulation when an error occurs; extracting keywords in the first-level control file that has completed the excitation in the simulation folder, analyzing the passing situation of the test excitation for executing the first-level control file, and outputting a first table of the final simulation results. In the present invention, when an error occurs in the test excitation, it pauses, loads and runs a second-level control file for controlling the simulation to generate a waveform file for re-simulation, and only generates a waveform file for the erroneous test excitation, replacing the traditional storage method of storing a complete waveform file, and reducing the memory pressure caused by the amount of stored data.

The invention discloses an instruction processing method based on command recognition and a related device, and relates to the technical field of computers.The method comprises the steps that agent program information is determined based on capture parameter information, and command line information is captured based on the agent program information; creating a content container, and performing operation instruction analysis and keyword analysis on the command line information in the content container to obtain a plurality of pieces of operation instruction information and target keywords corresponding to the command line information; command identification is carried out based on the operation instruction information and the target keyword, and a plurality of pieces of initial command information are obtained; performing command score analysis on the plurality of pieces of initial command information to obtain a target command score of each piece of initial command information, determining target command information based on the target command score, determining an instruction execution mode based on the target command information, and performing instruction processing and instruction recording based on the instruction execution mode. According to the invention, high-reliability identification and recording of command line operation data can be realized.

The invention provides a multi-platform-based copywriting keyword recognition and analysis method, which is used for quantifying keywords so as to provide a basis for operation decision making, and comprises the following steps: acquiring copywriting data of a plurality of platforms and metadata associated with the copywriting data, performing word segmentation processing on each piece of copywriting data to obtain each segmented word; performing multi-dimensional scoring on each segmented word based on the metadata to obtain a comprehensive score result corresponding to each segmented word; and generating a word segmentation ranking bottom table based on the comprehensive score result, wherein the word segmentation ranking bottom table is a quantification result of each keyword. According to the method and the device, the copywriting keywords of the plurality of platforms are acquired, and the keywords are subjected to multi-dimensional scoring based on the metadata of the plurality of different platforms, so that when the keywords are analyzed, the keyword commercial value ranking meeting the actual operation requirement can be generated from the dimension analysis of the plurality of platforms; and the keyword analysis is more accurate and comprehensive.

The present application discloses a content search method and apparatus, a storage medium, and a computer device, the method comprising: receiving search input information; obtaining target keywords that match the search input information from candidate keywords, wherein the candidate keywords are obtained by performing initial keyword analysis on candidate display content and screening the initial keywords based on the semantic relevance between the initial keywords and the candidate display content; obtaining target display content from the candidate display content based on the target keywords, and displaying search results based on the target display content. The present application extracts keywords based on candidate display content, which helps to obtain richer and more comprehensive candidate keywords used to describe candidate search objects, so that when a user searches, these candidate keywords can be used to recall results, which helps to obtain richer search results and improve the accuracy and comprehensiveness of search results.

The invention discloses a multi-storage medium grammar generation method and system based on a grammar analyzer, and relates to the technical field of grammar construction.The method comprises the steps of 1, statement obtaining, 2, normal statement word screening, 3, normal statement type analysis, 4, normal statement keyword analysis and 5, target statement generation. According to the method, the statement type of the normal statement is judged by analyzing the position and the byte number of each fixed word of the normal statement, and each key word of the normal statement is further screened into a table name word, each field word, each data type word and each constraint word, so that the reference statement for database conversion is quickly positioned, and the database conversion efficiency is improved. The syntactic analyzer can conveniently carry out statement conversion of multiple databases, the operation duration of a computer is shortened, the working efficiency is improved, and therefore economic benefits are brought to companies.

According to the context sensitive pointer analysis method provided by the invention, dependency and access relationships among modules are analyzed through keywords in the modules, modeling is carried out according to the dependency and access relationships, and a method calling statement for calling an interface is analyzed, so that the problem of completeness loss caused by the fact that interface access among the modules cannot be captured in a traditional pointer analysis method is solved. Secondly, an algorithm is designed, so that construction and updating of an object distribution graph and a module depth graph are completed in the statement analysis process, the pointer analysis efficiency is effectively improved, finally, key information is selected based on module depth information stored in the module depth graph to construct a context, the number of elements in the context is limited to be 1, and the algorithm is more efficient. Unnecessary analysis context elements are removed, and high precision of an analysis result is kept, so that the efficiency of an analysis process is remarkably improved.

The invention provides an automatic generation method and system for an expected function security scenarized test case, and the method comprises the steps: constructing an SOTIF real scene library based on an AI model, and the real scene library comprises scene metadata, an environment parameter template, an interference variable template and a security criterion template; a scene keyword input by a user is received, keyword analysis, scene library matching, parameter instantiation and case assembly are carried out through an AI model, and a scene test case is automatically generated; and scene logic verification is carried out according to the generated test cases, in response to meeting the scene logic verification, the priority score of each test case is calculated based on a pre-constructed priority ranking model, and the sequence of the test cases is determined according to the priority scores. According to the method, the test coverage rate is improved, the research and development period is shortened, the generated use case meets the ISO21448 standard, the method can be directly used for expected function safety test verification, and safe development and landing of intelligent driving products are supported.

The invention discloses a project name recommendation method based on an NLP and a knowledge graph, and relates to the technical field of artificial intelligence and data mining, and the method comprises the steps: 1, collecting multi-dimensional data of related projects, and carrying out the preprocessing of the multi-dimensional data to construct a project name corpus; 2, constructing a project knowledge graph according to the project name corpus; 3, performing core keyword identification, potential keyword identification and trend keyword prediction according to the project knowledge graph and the project name corpus to obtain a keyword cluster; and 4, updating the project name corpus according to the keyword cluster, training the constructed project name generation model by using the updated project name corpus, collecting user input information, and inputting the user input information into the trained project name generation model to obtain a recommended project name. According to the method, multi-dimensional data processing is fused, and project subsidization keyword analysis with keyword identification and application landing is realized, so that technical and data support is provided for scientific research project establishment.

The embodiment of the invention discloses a self-adaptive testing method and device based on an instant messaging tool, a medium and a product. The method comprises the following steps: acquiring input information of a tester in an instant messaging tool, and verifying the input information; if verification is passed, the input information is sent to an artificial intelligence platform for keyword analysis, and a keyword set and a keyword set type are obtained; determining a target test resource based on the keyword set and the keyword set type; and the target test resource executes a test task based on the keyword set, and feeds back a test result to the instant messaging tool. According to the method, the intellectualization of the test process can be realized, and the test threshold is reduced, so that the test personnel can participate in the test work more easily.

The application relates to the technical field of computers and networks, in particular to a transaction processing method and device for a distributed system, equipment and a medium. The method performs keyword analysis on a to-be-processed transaction request to determine a keyword, maps the keyword to a transaction category through a mapping table, compares the keyword with a transaction category keyword set to determine a target transaction category, and further determines a target processing model. If a server loaded with the target processing model does not exist in the distributed system, an idle server in the distributed system is selected as a target server, the target server is called to preload the target processing model, the to-be-processed transaction request is sent to the target server, a transaction processing result is obtained, the to-be-processed transaction request is dynamically distributed in the distributed system, frequent switching of processing models is avoided, the processing model is preloaded, the redundant waiting time is shortened, and the transaction processing efficiency is improved.

The invention discloses an intelligent advertisement recommendation management system based on internet keyword search, and relates to the technical field of advertisement putting, the system comprises an information extraction module, a keyword analysis module, a keyword combination module, an advertisement putting module and a real-time adjustment module, the keyword combination module comprises a user intention unit and an overall trend unit, the advertisement putting module puts the first recommended advertisement and the second recommended advertisement to the user according to preset resources, the real-time adjustment module comprises a value analysis unit and an advertisement adjustment unit, and the system has the advantages that short-term and long-term behavior data of the user are combined through the keyword analysis module, outdated content and short-term fluctuation interference are avoided, user requirements are accurately mastered, and user experience is improved. The keyword combination module generates two types of recommended advertisements through double units of user intention and overall trend, personalization and market trend are considered, attraction is enhanced, and the advertisement adjustment module dynamically distributes budget and optimizes resource configuration according to advertisement value scores, so that conversion efficiency is comprehensively improved.

The invention relates to the technical field of robots, and discloses a robot memory bank retrieval method, which comprises the following steps of: receiving a user instruction, analyzing a cue word and a large language model through a pre-configured keyword, and analyzing the user instruction to obtain a keyword corresponding to the user instruction; inputting the keyword into a multi-modal coding model, generating a semantic vector corresponding to the keyword, and retrieving in a memory bank according to the semantic vector to obtain at least one data node related to the keyword; and based on a pre-configured first screening prompt word, a second screening prompt word and a large language model, performing duplicate removal processing on the historical memory information of the at least one data node to obtain historical memory information related to the user instruction. According to the method and the device, the retrieval efficiency and accuracy are improved.

The invention discloses an intelligent evaluation method and system for graphic design, and relates to the technical field of intelligent evaluation. The system comprises an element division and keyword analysis module, a demand analysis and keyword matching module, a key element identification and evaluation index calculation module and an evaluation result judgment and suggestion module. The element division and keyword analysis module is responsible for element division, description information analysis and keyword analysis; the demand analysis and keyword matching module is responsible for analysis of demand information and intelligent matching between demand keywords and design elements; the key element identification and evaluation index calculation module is responsible for identifying key elements according to a matching result and calculating an evaluation index; and the evaluation result judgment and suggestion module judges whether adjustment is needed or not according to the evaluation index and generates corresponding prompt information. Through intelligent and automatic design element analysis, demand matching and evaluation index calculation, intelligent evaluation of the graphic design scheme is realized.