23 results about "Keyword analysis" patented technology

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 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.

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.

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.

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 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.

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 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.

Embodiments of the present specification provide a data classification method, a professional category identification method and a data classification system, wherein the data classification method comprises: performing keyword analysis on to-be-processed data to obtain at least one keyword in the to-be-processed data; searching for candidate category information and multi-level weights corresponding to each keyword through a pre-constructed keyword library, wherein the candidate category information comprises at least one candidate category, the keyword library comprises a plurality of sample keywords, sample category information and sample multi-level weights corresponding to each sample keyword, and the sample multi-level weights are weights of the sample keywords under different classification granularities; and filtering at least one candidate category corresponding to each keyword according to each keyword and the multi-level weights corresponding to each keyword to obtain a target category of the to-be-processed data. Since the weights are multi-level weights obtained according to different classification granularities, each keyword can be accurately represented, and thus the target category can be accurately obtained.

The embodiment of the application provides a kind of full link performance test method and device, it is related to software testing field, it can also be used in financial field, method includes: to all server nodes are pre-released pressure multiple times, the performance change of each server node in each pre-released pressure process is monitored, the server node belonging to target link is determined by preset density clustering algorithm and the performance change;Keyword analysis is carried out on the application log of the server node belonging to the target link, and the server node not belonging to the target link is removed according to the result of the keyword analysis;Performance monitoring tool is deployed on each server node on the target link and pressure test operation is started, and server performance data of the each server node is collected;The application can effectively improve the efficiency of full link performance test.

The embodiment of the invention provides a travel information processing method and device, a storage medium and a program product. In the scheme, the normal form transformation from static keyword analysis to dynamic multi-modal semantic understanding is realized by constructing a multi-modal encoder and double-big-model cooperation mechanism, and the fundamental defect that a traditional travel assistant lacks context perception and memory ability is overcome. Single-modal coding is combined with a fusion module, a first large model analyzes demand integrity, a second large model recall related historical abstracts for supplementation based on travel demand category suitability, and iterative optimization is driven through an integrity threshold, so that the system can accurately extract multi-modal deep semantics and can also accurately extract multi-modal deep semantics. And associated historical information can be intelligently screened instead of mechanically fusing all abstracts. Finally, collaborative improvement of multi-modal information deep fusion and multi-round dialogue contexts is achieved in the same link, the relevancy between travel recommendation and real demands of a user is greatly improved, and more accurate, intelligent and coherent travel planning service is provided for the user.

The application relates to the technical field of data analysis, and particularly provides a keyword-based alarm analysis method, device, medium and equipment. The method can comprise the following steps: acquiring the occurrence frequency of a keyword in a preset time period in a data stream to be processed; acquiring an abnormal parameter of the keyword based on the average frequency of the keyword in a corresponding historical preset time period and a target model constructed in advance; the target model is a distribution model based on probability statistics; and whether to generate alarm information is determined based on the abnormal parameter and the occurrence frequency. Some embodiments of the application can realize accurate and automatic monitoring of keyword abnormalities, effectively reduce false positives and false negatives of alarms, and improve alarm accuracy.

This invention provides a doctor recommendation method based on demand keyword parsing and multi-dimensional doctor influence assessment. It extracts semantic information such as user symptom entities and modifiers through sliding window segmentation and deep learning models to generate a confidence-based intent representation. It adaptively detects user intent drift using cosine distance variation and outputs the intent evolution strength. It integrates data such as doctor clinical behavior flow and patient evaluations, and uses time-weighted convolution to measure doctor dynamic influence. It dynamically gates and adjusts the doctor influence weights based on intent drift strength, achieving an organic combination of behavior and historical reputation. Combining real-time doctor influence, expertise vectors, and resource supply, it calculates a comprehensive matching score, and then outputs a personalized list of top ten doctor recommendations, generating corresponding demand-focused explanation tags. This invention improves the sensitivity of the recommendation system to changes in user needs and enhances the timeliness and fairness of doctor ranking.

This application relates to a multimodal image retrieval system and method based on multi-granularity keyword parsing. The system consists of a language parsing module, a multimodal retrieval module, and a semantic reordering module connected in sequence. First, multi-granularity keywords are extracted from the query text through multi-granularity analysis in the language parsing module. Then, the CLIP model in the multimodal retrieval module is used to filter relevant images for each keyword from a large-scale image and use them as candidate images. Next, the candidate images and the complete query text are input into the LLM model in the semantic reordering module for semantic reordering. The most relevant image of the query text is output. After the LLM model outputs the most relevant image, a similarity threshold is used to judge. If the confidence of the LLM output result is insufficient, it automatically switches to CLIP global retrieval, which can ensure the reliability of the final output retrieval results, ensure a high degree of matching between the target image and the query text, and improve the accuracy of multimodal image retrieval.

The application provides a traditional Chinese medicine auxiliary diagnosis and treatment method, system, device and storage medium, which comprises the following steps: performing keyword analysis on symptom information text describing the symptoms of a patient to obtain symptom words; if the symptom words exist, a prescription associated with the symptom words is obtained; performing correlation degree analysis on medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials associated with the symptoms; and the recommendation degree of the prescription is obtained according to the correlation degree of the associated medicinal materials, so that a target prescription is output according to the recommendation degree. The technical scheme of the application can improve the intelligent degree of the traditional Chinese medicine auxiliary diagnosis and treatment system.

The invention discloses a ChatGPT-based secondary job cross-border e-commerce content optimization system and optimization method, and mainly relates to the technical field of cross-border e-commerce content optimization. Comprising a Listing optimization module, a keyword analysis optimization module, a product improvement suggestion module, a message reply module, a rapid customer evaluation extraction module and an analysis QA module. The method has the advantages of high precision, higher ranking, accurate improvement suggestion, high customer satisfaction, timely collection and feedback, quicker problem solving and the like, and is of great significance in solving the problem of cross-border e-commerce platform optimization.

The invention relates to the technical field of data processing and computers, and discloses a semantic segmentation and recombination method and device for complex query, electronic equipment and a medium, and the method comprises the following steps: generating a logic structure tree of a to-be-converted query statement; performing label blocking on each node in the logic structure tree to obtain a structured block; and generating a target query statement according to the structured block. According to the method, on one hand, the accuracy of complex query statement reconstruction is improved, and the validity and accuracy of query are further improved; on the other hand, the problem that business semantics are lost due to the fact that keyword analysis is separated from power grid scene knowledge in the prior art is solved.

The present application relates to the field of data analysis, especially to a heat stroke pathological data integration information collection processing method based on deep learning, comprising: determining the data state of user analysis data according to the data richness and image transformation completion degree of the user analysis data; when the keyword selection mode is the association group selection generation, determining the number of selected keywords according to the group influence coefficient, and selecting the keywords according to the order from large to small of the sensitive coefficient; when the keyword selection mode is the image transformation supplement generation, determining the keyword generation mode according to the feature representative degree of the divided paragraph, which is to generate keywords according to the median point or outlier point; under the initial search completion condition, optimization analysis is carried out, and the search optimization mode is determined to be combination search or sequential search according to the repeated keyword analysis state, which improves the pathological data integration search efficiency.