378 results about "Word group" patented technology

To improve efficiency of idea proposal support.SOLUTION: A proposal support system executes: acquiring a specific first word from a co-occurrence network in which each first word of a first word group in a first sentence group including a first field name in at least one information source out of a first information source related to a first field and a second information source related to a second field different from the first field is a node, and a co-occurrence relation between two first words is a link connecting the nodes; extracting company names in the second field relating to the specific first word, from a second sentence group including a second field name and the specific first word from the at least one information source; associating the specific first word, a specific second word, and the company names in the second field, based on appearance information related to the specific second word that co-occurs with the specific first word in a second word group in the second sentence group; and performing output processing of outputting an analysis result in a displayable manner.SELECTED DRAWING: Figure 5

The invention provides a cross-modal retrieval model training method and a remote sensing image text retrieval method, and is applied to the technical field of remote sensing cross-modal retrieval. The remote sensing image text retrieval method comprises the following steps: performing feature extraction on a preprocessed remote sensing image by utilizing a trained cross-modal retrieval model to obtain image global features and image local features, and performing feature extraction on a preprocessed target text to obtain text global features and phrase global features; calculating the global similarity between the image global features and the text global features by using the trained cross-modal retrieval model, and calculating the local similarity between the image local features and the word group global features; and carrying out weighted calculation on the global similarity and the local similarity by utilizing the trained cross-modal retrieval model, and screening a matching result between the remote sensing image and the target text based on the weighted similarity to obtain a retrieval result between the remote sensing image and the target text.

The invention relates to the technical field of digital data processing, in particular to an intelligent triage and guide analysis method, device and system based on a large language model.The method comprises the steps that symptom information of a patient is collected in a text input or voice input mode, and the symptom information and patient identity information are associated; cleaning the collected symptom information and extracting a symptom keyword group; matching the extracted symptom keywords with data in a knowledge graph to determine a to-be-selected disease group; generating a corresponding recommended department table according to the to-be-selected disease group, and arranging the departments according to the priority; and correcting the arrangement sequence of the departments based on the historical treatment records of the patients. Through the steps, the symptom information of the patient can be efficiently collected and processed, and accurate and personalized medical suggestions can be provided. According to the method, the efficiency and the quality of medical services are greatly improved, and meanwhile, the medical experience of the patient is also improved.

The invention relates to a visual-language model cue word evolution generation method based on a genetic algorithm, which comprises the following steps of: randomly generating different cue words under a target task to construct an initial cue word set, preprocessing the randomly generated cue words, and reserving N groups of cue words as an initial population; and designing a multi-dimensional fitness evaluation function to evaluate the performance quality of each group of cue words in a vision-language task, and selecting high-quality cue word individuals based on an elitism strategy. Performing crossover and mutation operation on the selected high-quality cue word individuals by referring to a genetic algorithm to generate a new-generation cue word population; and finally, carrying out iterative optimization for multiple times until a preset termination condition is met, and outputting an optimal cue word set. By the adoption of the visual-language model cue word evolution generation method based on the genetic algorithm, high-quality and diversified cue words can be automatically generated, the performance of a visual-language model is remarkably improved, and meanwhile the visual-language model cue word evolution generation method has good interpretability and adaptability.

The invention relates to the technical field of speech recognition, in particular to a man-machine interaction method and system for speech recognition, and the method comprises the steps: obtaining the frequency spectrum information of a user speech segment, generating a speech spectrogram, constructing a speech library of a user, and carrying out the word segmentation processing, thereby obtaining a sequence of word units; dividing word groups by using a clustering algorithm, and calculating a segmentation coefficient and a stop coefficient of each word group according to a mapping function of an upper envelope line and a lower envelope line of the spectrogram so as to determine an optimal clustering result; real-time input voice segments are compared with reference word groups, and a user confirmation coefficient between the spectrogram of the real-time word groups and the spectrogram of the reference word groups is calculated; and judging whether the real-time input voice segment and the reference voice segment are the same user or not according to the user confirmation coefficient, and completing the human-computer interaction process of voice recognition. According to the method, the user voice library is constructed, and the spectrogram analysis and clustering algorithm is utilized, so that efficient voice recognition and user confirmation are realized, and the user interaction experience is improved.

The invention discloses an intelligent volume adjusting method and system based on environment sound, and the method is applied to a wireless earphone, and comprises the steps: determining a target prompt word according to an initial prompt word registration form submitted by a user; environment sound sampling data collected by wireless earphones are divided into environment noise data and human voice data, and the wireless earphones comprise a left earphone worn on a left ear and a right earphone worn on a right ear; dividing the human voice data into a plurality of groups of character voice data in one-to-one correspondence with the plurality of groups of characters according to voice features in the human voice data; determining target character sound data corresponding to the phrase whose similarity with the target prompt word is greater than a preset threshold value when identifying that the phrase whose similarity with the target prompt word is greater than the preset threshold value exists in the plurality of groups of character sound data; determining the orientation of human voice data corresponding to the target human voice data; and reducing the volume of the left earphone or the right earphone according to the orientation. According to the invention, the use convenience of the wireless earphone is improved.

The invention relates to the technical field of cross-culture translation, in particular to a cross-culture translation method and system based on context perception fusion, and the method comprises the steps: recognizing a text data set and an image data set, carrying out the paragraph division of the text data set, obtaining a text paragraph set, recognizing an image description text of image data, carrying out the word segmentation of the image description text, and obtaining a text paragraph set; calculating the matching similarity of the text paragraphs and the image description phrases, judging whether the matching similarity is greater than a standard matching similarity or not, if so, recording the matching similarity as a target matching similarity to obtain a target matching similarity set, and obtaining a plurality of associated text paragraph sets according to the target matching similarity set; and translating the associated text paragraph set to obtain an associated translated text, extracting an unassociated text paragraph set from the text paragraph set, and translating the unassociated text paragraphs to obtain an unassociated translated text. According to the invention, the accuracy and efficiency of cross-culture translation can be improved.

The invention relates to the technical field of data processing, and discloses an intellectual property information analysis and matching system based on big data, comprising: an acquisition unit acquiring user demands and a historical demand set, performing semantic analysis on the user demands to extract demand keywords, and determining importance; sequencing the demand keywords according to the importance to form a current keyword group; the judgment unit is used for comparing the keyword group with a historical demand set and judging whether a historical matching catalog is taken or not; when the historical matching catalogue is judged to be used, determining a current matching catalogue according to the historical matching catalogue and the current keyword group; when it is judged that the historical matching catalogue is not used, determining a current matching catalogue according to the current keyword group; the processing unit performs clustering analysis on the matching catalog to determine a matching display result; and the storage unit stores the current keyword group and the matched display result. According to the invention, the matching efficiency and accuracy are improved, and the problems of low efficiency, low accuracy and the like in traditional intellectual property matching are solved.

The invention relates to the technical field of computers and artificial intelligence, in particular to an industrial economy query word segmentation retrieval method, system and equipment based on context enhancement, large model fine tuning and a vector library and a medium. Firstly, a user inquiry data set is used for performing fine tuning operation on a large model after corpus training is completed, so that the large model can learn and master the context understanding and multi-modal fusion process, and a fine-tuned large model capable of obtaining key phrases from user questions is obtained; the method comprises the steps that firstly, a fine-tuned large model is obtained, then semantic analysis and context completion are conducted on a new question input by a user through the fine-tuned large model, a plurality of new keywords are obtained, finally, a database is inquired according to the new keywords, and an inquiry result is returned to the user. Therefore, an automatic, efficient and accurate database query scheme is provided, the method has the advantages of being low in cost, easy to implement and capable of achieving dynamic self-adaptive optimization, a brand new solution is provided for database query, and practical application and popularization are facilitated.

The invention relates to the technical field of natural language processing, in particular to a dynamic intention chain modeling and causal cleaning method and system under a multi-round dialogue scene. According to the method, through multi-round dialogue data collection and preprocessing, one-hot codes are allocated to each sub-word or word group, intention recognition and sequence modeling are carried out based on the codes, and the intention of the user can be accurately recognized; quick mapping for directly obtaining user intentions from voice input data by skipping text data conversion is established, so that the intention recognition efficiency is improved; according to the method, the causal relationship graph is constructed based on the user intention sequence, the Bayesian network is utilized to perform causal modeling, the causal relationship between intentions is derived, and the probability of reasoning the next intention through the previous intention is calculated, so that the next intention of the user and the interactive operation to be executed are accurately reasoned; and collecting user feedback data to calculate a satisfaction score, and correcting the priority ranking rule of the rule engine based on the score.

The invention relates to the technical field of data identification, in particular to a data security identification method covering physics, semantics and sensitive points, and the method comprises the following steps: processing an obtained first industry review document set and a second industry review document set to generate an industry semantic feature lexicon; performing semantic analysis on each sensitive point information sentence to generate a sensitive point information phrase sequence, taking the sensitive point information phrase sequence as input, performing training through a professional field document to generate a word vector model, and performing similarity calculation on the word vector model to generate a sensitive feature lexicon; based on the industry semantic feature lexicon and a word segmentation tool, keyword segmentation is carried out on the target document, and a semantic security identifier is generated; and performing word segmentation on a target sentence in the target document based on the inactive word bank and the industry semantic feature word bank, and generating a sensitive security identifier in combination with the sensitive feature word bank. By applying the method, effective identification can still be realized under the condition of data adjustment, and semantic representation of the body is enhanced.

The embodiment of the invention discloses a physical examination report standardized storage method and device, electronic equipment and a medium. A specific embodiment of the method comprises the following steps: carrying out image enhancement processing on an obtained user physical examination report image set, and then carrying out physical examination item classification processing to obtain a first physical examination item report image set and a second physical examination item report image set; generating an image detection text information set; performing image text recognition on the user physical examination text region image set to obtain a physical examination report text recognition information set; performing text calibration on the physical examination report text identification information set to obtain a physical examination report text calibration information set; generating a report standardized prompt word group set; performing content extraction on the physical examination report text calibration information set to obtain a report extraction information set; and matching and storing the report extraction information set to a user physical examination report storage system. According to the embodiment, the extraction accuracy and effect of the physical examination report information can be improved, the extraction time is shortened, and waste of storage resources is reduced.

The utility model discloses a word spelling teaching aid for Chinese learning, and relates to a Chinese learning tool, in particular to a Chinese polyphonic polysemy word spelling learning tool. The card splicing box comprises a storage box (1), a card splicing box (2) and cards (3), each group of cards comprises a certain polyphonic polysemy, a character card (31) respectively printed with polyphonic polysemy pinyin, a pronunciation card (32) respectively printed with pronunciation different from that of the character card, and a word group card (33) corresponding to the pronunciation card; the storage box is arranged above the card splicing box; a cavity for storing the card (3) is arranged in the storage box (1); and a group of character cards, pronunciation cards and word group cards which are arranged side by side can be accommodated in the card splicing box. The device is a polyphone spelling practice device, and solves the problems that an existing similar device is complex in structure, depends on electric power in use, and is inconvenient to popularize and use.

Gender bias assessment techniques that are available currently only consider two genders viz male and female and is not inclusive of lesbian, gay, bisexual, transgender and queer (LGBTQ) genders. Present disclosure provides method and system for assessing gender fairness of large language models (LLM). The system first receive context aware prompt comprising context and prompt and then converts names present in the context using name anonymization technique. The system then convert many-to-many pronouns present in no-name-context into many to one pronouns which are then used to create counterfactual context for each gender pronoun group. Thereafter, system queries LLM with counterfactual prompt created using counterfactual context to obtain counterfactual response which is then used to create embedding data frame. Further, system trains Gaussian Mixture Model using embedding data frame which is then utilized to calculate cluster distances. Finally, system assess gender bias based on cluster distances and predefined distance threshold.

The invention belongs to the technical field of data mining, and particularly relates to a social media data mining method based on user behavior analysis. The method comprises the following steps: collecting user multi-source behavior data in real time, analyzing unstructured data through natural language processing, extracting key phrases and mapping the key phrases to structured fields; after abnormal data is removed through data cleaning, a behavior sequence is constructed in a time window, a time perception embedded vector is introduced to generate time sequence feature representation, and meanwhile, BERT is utilized to extract behavior content semantic vectors, and features such as behavior types and strength are fused to generate uniform content representation vectors; and finally, fusing the two types of features through a BiGRU-Attention network, and predicting a future behavior probability value of the user to drive personalized recommendation. According to the method, the problems of insufficient behavior semantic motivation capture, difficulty in data isomerism processing, weak dynamic modeling capability and the like in the prior art are solved, and the social media data mining precision is improved.

The invention relates to a voice instruction execution method, system and device, vehicle end control equipment and a storage medium, and relates to the technical field of voice recognition. The method comprises the following steps: identifying a single voice instruction to obtain at least two key phrases, creating a plurality of corresponding sub-tasks based on the key phrases, and adding the sub-tasks into the same to-be-executed task queue; when it is recognized that the to-be-executed task queue comprises the sub-tasks, triggering a preset executor to execute the sub-tasks so as to obtain execution data corresponding to the sub-tasks, and storing the execution data of the sub-tasks to a completed task queue; triggering the associated application to output a task execution result based on the execution data when it is identified that the completed task queue comprises the execution data of the at least two sub-tasks; the number of times of input and recognition of the voice instruction of the user is reduced, the intelligent level of the vehicle end control equipment carrying the voice recognition system is improved, and therefore the use experience of the user on the voice recognition function in the vehicle is improved.

The invention relates to the technical field of legal consultation services, in particular to an intelligent question and answer matching method based on machine learning, which comprises the following steps of: acquiring legal consultation text recognition subject behavior objects and articles, analyzing and carding statement logic in sections, generating a semantic hierarchical table, extracting key phrases and integrating semantic units, and constructing a semantic network to generate a mapping table. Comparing question answer semantic logic to generate a matching corresponding set, reviewing offset revised text to generate a revised set, and rechecking consistency arrangement to generate an intelligent matching result set. According to the method, legal text logic relations are analyzed and processed through semantic layering, question and answer matching precision is optimized, keyword extraction and semantic network construction are combined, semantic consistency recognition and matching flexibility is enhanced, semantic offset and logic inconsistency are corrected, result connection coherence is ensured, mismatching is reduced compared with the prior art, question and answer accuracy is improved, and the method is suitable for popularization and application. Legal consultation is more intelligent and accurate, and a reliable matching result is provided.

The invention relates to the technical field of natural language processing, in particular to a customer service work order classification method and device based on natural language processing and a storage medium, and the method comprises the steps: obtaining a customer service work order of a target product in real time, obtaining historical customer service work order data of the target product, and classifying the customer service work order based on the historical customer service work order data; extracting a demand feature set of the target product in a natural language processing mode, extracting a second demand word group according to the customer service work order of the target product, matching the second demand word group with each demand feature set, preliminarily classifying the customer service work order according to a matching result, and collecting operation data of the target product; and performing secondary classification on the customer service work order according to the preliminary classification result of the customer service work order and the operation data of the target product, matching the secondary classification result of the customer service work order with the demand feature set, and generating a processing result of the customer service work order according to the matching result. According to the invention, the classification efficiency of the customer service work order is effectively improved.

The invention relates to an interaction method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving a first reference image, and displaying the identification information of the received first reference image in a guide language input region; the number of the first reference images is multiple; receiving a text cue word, and displaying the text cue word in the guide word input area; the text cue word comprises an object description word group, and the object description word group corresponds to the first reference image; the object description phrases are used for describing objects in the first reference image corresponding to the object description phrases; the identification information of the first reference image is interspersed in the text cue word; the number of characters between the position of the object description phrase in the text cue word and the position of the identification information of the first reference image corresponding to the object description phrase in the text cue word is less than a preset number of characters; a first video is generated based on the content in the guide language input area. The demand that a user hopes to generate a video based on a plurality of first reference images can be met.

A mobile computing device can be configured, with an improved user interface, to synchronously play audio (or video) and text associated thereto, such as text stored in a synchronization index. Using the synchronization index, the device can periodically compare the current track time with that time associated to a word or range of words, such as a line (or segment) in a plurality of lines of text (or segments of text). Improved navigability of content using an improved mobile computing device and user interface is provided, because a user of the device can scroll through the lines of text associated with the audio or video to find a target word or range of words. If the user selects a particular word or range of words, by making a gesture on the mobile computing device, the device can identify a start time for the selected text. The device can then play the audio or video at the identified start time of the selected text. The improved user interface is a practical application for navigating audio (or video) and text associated thereto on a mobile computing device, providing bimodal reading on mobile computing devices and ease of navigability.

The invention relates to a power document intelligent writing method and system based on an extraction and generation hybrid model, and the method comprises the following steps: S1, carrying out the preprocessing of key phrases or short sentences which are inputted by a user and need to generate a document, then carrying out the discrimination of sentences in documents of related official documents and reports through a BGA extraction type sub-module in a state grid power brilliance large model, and carrying out the recognition of the sentences in the documents of related official documents and reports; extracting sentences which are highly matched with key information input by a user and have a threshold value to form a candidate sentence set; s2, according to the candidate sentence set, obtaining related background knowledge from a power time sequence knowledge graph by using a state grid power brightness large model KG-PGN deep learning network; and S3, according to the candidate sentence set and the related background knowledge, completing automatic document generation through a Transform encoder in the state grid electric power bright large model, and checking generated vocabularies during decoding in combination with a cover tool provided by the bright large model to avoid repeated generation of the same vocabularies. According to the method, the automation and intelligence level of power document generation is greatly improved.

The invention discloses a semantic prompt automatic labeling method in a building construction scene, and relates to the technical field of intelligent construction, and the method comprises the steps: collecting a construction plan, on-site surveying and mapping data and real-time environment information, dividing a construction site into construction operation units, and extracting task features to generate a task priority coefficient Kt and a scene state vector Ei; calculating a semantic prompt priority index SPI based on Kt and Ei, sorting prompt words, and mapping the prompt words into feature vectors through BERT; extracting image global features by using a visual model, performing weighted fusion on the image global features and semantic prompt features, and outputting a detection region set; through comparative analysis of a semantic consistency coefficient Ssem and a threshold value Qsc, optimal prompt phrases are optimized and combined to generate a multi-granularity labeling structure; and calculating a semantic anomaly coefficient SAI by adopting cross-modal cosine similarity, comparing the semantic anomaly coefficient SAI with a threshold value Qsai to judge whether the annotation is abnormal or not, and realizing anomaly correction, history comparison and responsibility judgment by recording and tracking the whole process of the annotation link.

The embodiment of the invention discloses a data processing method and device based on a large language model. According to the method, a to-be-scored question group is obtained, the to-be-scored question group comprises questions, answers of answering parties and reference answers, and according to the to-be-scored question group and key words, a prompt template, a false question generation prompt template and an evaluation generation prompt template are extracted, respectively constructing a keyword extraction prompt statement, a pseudo question generation prompt statement and an evaluation generation prompt statement, respectively inputting the constructed statements into a large language model to obtain corresponding keyword groups, question groups and global evaluation, determining text similarity of answers of answering parties and reference answers, and determining the similarity of the answers of the answering parties and the reference answers; and inputting the keyword group, the question group, the global evaluation and the text similarity into a pre-trained comprehensive scoring model to obtain a score corresponding to the answer of the answering party. According to the method, the advantages of the large language model and the comprehensive scoring model are combined, the generalization generation capability of the large language model is exerted, and the vertical domain scene learning capability of the comprehensive scoring model is utilized.

The present invention proposes a dialogue assembly method and device based on skeleton guidance, which belongs to the field of natural language technology. The skeleton words covering key information are extracted from the original dialogue to form a dialogue skeleton; the components and skeleton words in the original dialogue are combined in different ways to obtain multiple candidate assembled sentences; the probability of generating each candidate assembled sentence is calculated according to the original dialogue skeleton as a fluency feature; the number of words that do not belong to the skeleton words contained in each candidate assembled sentence is counted as the number of irrelevant words to obtain a semantic consistency feature; each candidate assembled sentence is spliced ​​with the original dialogue, input into a classifier to predict the probability, and obtain an information coverage feature; by combining the above three features, each candidate assembled sentence is evaluated to obtain the best assembled sentence. The present invention can generate assembled sentences that are fluent, have high information coverage, and are semantically consistent with the original dialogue using only a small amount of annotated data, thereby alleviating the problem of scarce annotated data.

The invention discloses a key value cache sharing method and device for a large language model, equipment and a product. The method comprises the steps that request content input to the large language model by a first user is acquired; determining a first segmented word group corresponding to a first part of a shared key value cache of the large language model in the request content, wherein the shared key value cache of the large language model does not have a matched key value; determining an attention score between every two segmented words in the first segmented word group to obtain an attention matrix, determining at least one second segmented word group based on the attention matrix and the first segmented word group, and adding a corresponding key value to a shared key value cache; wherein the attention score between the segmented words in the second segmented word group is greater than the attention score between the segmented words in the second segmented word group and the segmented words outside the second segmented word group. Continuous updating of the shared key value cache is realized, and the hit rate and the utilization rate of the cache key value are remarkably improved.

The invention discloses a geographic information vocabulary sensitivity determination method and device. The method comprises the steps of obtaining a target geographic information vocabulary; whether the target geographic information vocabulary hits a pre-established geographic information vocabulary database or not is determined, if not, a pre-established geographic information phrase database is obtained, the geographic information phrase database comprises a plurality of geographic information phrases and label information thereof, and the geographic information phrases can form the geographic information vocabulary; the tag information of the geographic information phrase is used for representing the probability that the geographic information vocabulary comprising the geographic information phrase is a sensitive vocabulary or a non-sensitive vocabulary; and performing word segmentation on the target geographic information vocabulary to obtain a plurality of segmented words, matching each segmented word in the plurality of segmented words with the geographic information phrases in the geographic information phrase database, and determining the sensitivity of the target geographic information vocabulary based on the tag information of each geographic information phrase successfully matched with the segmented word in the geographic information phrase database.

The present invention relates to the field related to language information processing, and discloses a structured information retrieval method and system based on a large language model, which are used in speech recognition information retrieval based on the large language model to realize personalized recognition model iteration effect, achieve the purpose of language understanding with high-precision recognition rate, obtain correctly matched retrieved keyword groups through retrieval feedback based on conventional big data language models, and obtain individual pronunciation features based on the deviation amount between the user voice of these phrases and the standard retrieval features provided by the large language model, and use them for personalized correction of the big data language model to realize a language retrieval scheme with high recognition rate based on individuals.

The invention belongs to the technical field of intelligence, and discloses an intellectual property operation management system based on big data, comprising: acquiring behavior data and basic data of intellectual property; carrying out missing value and abnormal value processing on the behavior data of the intellectual property to obtain a preprocessed data set; predicting value index data of the intellectual property by using an SVR model based on the preprocessed data set; an ETL tool is used for extraction, conversion and loading, a TF-IDF technology is used for processing the application name, a keyword group B is extracted, and the keyword group B serves as a new field to be stored in a target database; based on a text input by a user, obtaining a keyword A by using a TF-IDF technology; matching with the keyword group B to obtain comprehensive matching degree data; based on the comprehensive matching degree data, a threshold value is set, and whether recommendation is carried out or not is judged; and the intellectual property operation management efficiency and accuracy are improved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an emergency perception method containing semantic extraction, which comprises the following steps of: S1, constructing a historical word library about emergencies, and forming an association weight between a vocabulary group and a user through historical data training; s2, constructing an entity variant word expansion model based on a double-layer model to realize generation of a variant word bank, wherein the double-layer model comprises a proper noun expansion layer and a historical word bank expansion layer; s3, collecting text data on a network, performing classification processing on the text data based on a text classification rule, and preliminarily extracting entity words; s4, inputting the extracted entity words into the variant word expansion model to obtain a corresponding variant word group, and completing identification and extraction of the entity words; and S5, carrying out situation analysis based on the knowledge graph, and predicting the occurrence and development situation of the emergencies. According to the method, the variant word bank suitable for the whole network is mined on the basis of the incidence relation of different users to different similar words, and the reliability of vocabulary expansion is improved.