43 results about "Position Descriptions" patented technology

The invention discloses a human resource intelligent management method and system based on man-post matching, and the method comprises the steps: receiving an unstructured post description text, extracting key information through a natural language processing technology, generating a structured multi-dimensional post portrait, and classifying the structured multi-dimensional post portrait; on the basis of historical recruitment data, predicting the number of future post demands by means of a time sequence analysis model; for the candidate resumes and the target post portraits, keyword correlation scores, depth semantic similarity scores and predictive stability scores are calculated in parallel; according to the post portrait classification application dynamic weight, performing weighted summation on the scores to generate a comprehensive matching score; and sorting the candidates according to the comprehensive matching scores, and outputting a sorted candidate list. According to the method and the system provided by the invention, the man-post matching accuracy and the recruitment efficiency are effectively improved, the core pain points of intelligent recruitment, man-post matching and demand prediction in human resource management are solved, and the method and the system are particularly suitable for the demands of human resource outsourcing and labor dispatching industries for stable service selection.

The invention discloses a personalized intelligent interview system, and relates to the technical field of artificial intelligence and recruitment interview, and the system comprises a position information analysis module which is used for inputting an original position description text, carrying out the analysis through employing a natural language processing NLP technology, and extracting structured position demand data containing skill items, characteristic items and quantification levels; the resume / position intelligent matching module is used for receiving the structured position demand data, receiving a job seeker resume text, performing intelligent matching analysis by constructing a skill semantic vector space, and outputting a multi-dimensional matching score matrix and an investigation key index set; according to the job demand and the job seeker resume, personalized interview topic screening and optimization are realized, and the interview pertinence and accuracy are improved; the job seeker is comprehensively evaluated, and the resume / position matching information is combined, so that a more comprehensive evaluation and scoring basis is provided, and an enterprise is helped to make a more accurate recruitment decision.

The invention relates to the technical field of text data processing, in particular to a resume matching method and device, electronic equipment and a storage medium. Performing structure analysis on the position description text to obtain sub-statements bearing skills, experiences or qualification conditions; extracting skill keywords, experience keywords and qualification keywords from the sub-statements by using a named entity recognition model; performing semantic extension on the skill keywords, the experience keywords and the qualification keywords by using a word vector model to obtain a keyword list; and generating a position tag based on the keyword list. According to the method, key capability requirements can be accurately extracted by performing structural analysis on the position description text and using the named entity recognition model, the keyword coverage rate and the matching precision are remarkably improved in cooperation with a semantic extension technology, the automation degree and the intelligent level of a resume matching process are remarkably improved, and the matching efficiency is improved. And the limitation of manually maintaining the tag library traditionally is avoided.

The invention provides an equipment access method and device, electronic equipment and a storage medium, and relates to the technical field of Internet of Things. The method comprises the steps that point table information of current equipment to be accessed is acquired, point location description information of the equipment to be accessed is generated according to the point table information, and the point location description information comprises related configuration information of the equipment to be accessed to a target system; updating currently configured device point location description information of the target system according to the point location description information of the to-be-accessed device to obtain updated device point location description information; and generating a target gateway execution code according to the updated device point location description information and running the target gateway execution code so as to access the current device to be accessed to the target system, and performing data acquisition on the device accessed to the target system. According to the scheme, the point table information of the to-be-accessed device is obtained and converted to generate the point position description information of the to-be-accessed device, rapid compatibility of information of the new device is realized based on the point position description information of the to-be-accessed device, and the development cost is reduced.

The invention discloses a position publishing platform based on artificial intelligence and electronic equipment, and the position publishing platform executes the following processing after being started: carrying out the reasoning analysis of enterprise business data and market data of a target enterprise through an AI position mining large model, and determining a list of positions needing to be recruited by the target enterprise; in response to a target position selected by the target enterprise from the recommended positions, calling an AI position generation large model to perfect multiple contents of the target position according to basic information of the target position and recruitment requirements of a knowledge base in the reference enterprise and / or historical position description information of the target position, and generating target position description information; and performing reasoning analysis on the position features in the target position description information and the target recruitment crowd through an AI position publishing and tracking large model, and selecting a target recruitment publishing channel to publish a target position. According to the invention, automation of the position release process is realized, and the recruitment efficiency and quality of enterprises are improved.

The invention discloses a position information auditing method and device based on multi-modal information. Comprising the steps of converting a position description text and enterprise entity information into a predefined structured data format, and generating a system cue word matched with the position description text to be audited based on structured enterprise information and structured position information, the system cue word comprises an auditing rule used for performing association analysis between the structured position information and the structured enterprise information on N target position auditing dimensions; the N target position auditing dimensions at least comprise consistency verification between structured position information and enterprise qualification text information, enterprise credibility evaluation based on enterprise historical release position records, and compliance identification of position description texts; and inputting the system cue word into a pre-trained large language model to obtain an audit result for the position description text to be audited. According to the invention, the identification accuracy of false recruitment positions can be improved.

The present application discloses a method, device and equipment for describing and correcting the spatial position of satellite positioning points. The method includes the following steps: obtaining the longitude and latitude coordinates and elevation coordinates of each positioning device located in the blasting area through satellite positioning and converting them into corresponding grid coordinates; obtaining the quantity threshold of satellite positioning points in the grid according to the satellite positioning time interval, the operating speed of the positioning device and the satellite positioning error; counting the number of satellite positioning points in each grid, and outputting the grid coordinates whose number of satellite positioning points is greater than or equal to the quantity threshold as the final grid coordinates of each positioning device. The present application uniformly describes the positioning point data falling within the grid with grid coordinates, which can greatly reduce the amount of data, improve positioning efficiency, and has strong applicability, meeting the positioning needs under different working conditions. At the same time, using the quantity threshold to correct the coordinate points can effectively overcome the influence of satellite positioning errors, thereby further improving positioning accuracy.

The invention discloses a person and post matching method, device and system and a storage medium. The person and post matching method comprises a first stage and a second stage, wherein the first stage is pre-matching, quantitative evaluation pre-matching is carried out based on structured information extracted from resumes and position description, and candidates basically meeting position conditions are screened out; the second stage is a model training and application stage, firstly, a mixed deep learning architecture of a double-tower model and a cross encoder is adopted to construct a resume coding tower, a position coding tower and a cross encoder model, so that deep semantic matching analysis and vector similarity matching are performed on candidate resumes passing pre-matching, and then the candidate resumes are obtained. The candidate resumes with the highest similarity of the TOPK are obtained, then the candidate resumes of the TOPK are finely arranged, and finally a matched result list is output.

The invention discloses an intelligent resume screening method, system and device based on a large language model and a medium, and the method specifically comprises the steps: based on an initial weight, analyzing position description through the large language model, and extracting key skill requirements; analyzing the matching degree of each resume, and generating a matching degree score through key skill requirements; determining a resume screening result according to the matching degree score, and collecting an adjustment operation and a labeling reason of the HR on the resume screening result; dynamically optimizing weight distribution through a reinforcement learning model according to the adjustment operation and the marking reason; automatically adjusting the skill priority according to a post demand prediction model by using the optimized weight; and based on the skill priority, identifying the deep matching relationship between the candidate skill and the post demand in the resume screening result, and evaluating the potential index of the candidate to adapt to the new post according to the deep matching relationship and the industry talent flow data. According to the invention, efficient, accurate and dynamically adaptive intelligent resume screening is realized, and the recruitment quality and efficiency are improved.

The invention relates to the technical field of medical intelligent informatization, and discloses a thyroid cancer electronic medical record processing method and system based on multi-modal data, and the method comprises the steps: obtaining a thyroid image and an associated electronic medical record text containing lesion position description; extracting a text orientation semantic vector representing a relative spatial relationship from the text, and extracting a focus morphology feature vector representing a visual morphology and an image spatial relationship vector representing a spatial position relative to a preset anatomical structure from the image; respectively calculating an orientation semantic consistency score and a morphological neighborhood consistency score, and fusing to obtain a comprehensive consistency score; and finally, comparing the comprehensive consistency score with a preset threshold value to determine whether the text description corresponds to the focus in the image. According to the method, cross-modal accurate matching is realized, the diagnosis and treatment data utilization rate and the judgment accuracy are improved, the high efficiency and accuracy requirements of clinical diagnosis and treatment are met, and meanwhile, the method is adaptive to a medical teaching scene.

The application discloses a recruitment service resource recommendation method, device and equipment based on a recruitment scene. The method comprises the following steps: obtaining recruitment data of each position published in history; training a pre-training model based on the recruitment data under a single evaluation dimension to obtain a recommendation model associated with the single evaluation dimension; inputting position description information of a current position into N recommendation models respectively, so that each recommendation model matches a first resource ID for the current position from each resource ID under the single evaluation dimension based on the position description information, evaluates a service effect of a recruitment service resource of the first resource ID on the current position, and obtains a service effect index value; taking the first resource ID and the service effect index value thereof as a recommendation result to obtain N recommendation results; screening a second resource ID in combination with the service effect index values in the N recommendation results, and determining a recruitment service resource corresponding to the second resource ID as a recommended recruitment service resource of the current position.

The invention discloses a network clue data change analysis method and system based on a knowledge graph, particularly relates to the technical field of data processing, and is used for solving the problem that a clue coordinate mapping result does not conform to an actual geographical current situation due to dependence on a static geographical entity knowledge graph in the prior art. The method comprises the following steps: describing and identifying spatial differences by aggregating multi-platform clue positions, and generating a change pre-check instruction when the differences relate to geographic entities in a preset range; performing topological manifold embedding analysis on the text in combination with the initial coordinates to generate a manifold embedding distance, and detecting a conflict rate of a spatial reference system; when the distance or the conflict rate exceeds a threshold value, triggering knowledge graph updating; and finally, re-matching based on the updated map to obtain a target geographic entity and coordinates. Real-time perception of geographic entity change and dynamic map correction are realized, and the accuracy and reliability of natural resource clue space positioning are effectively improved.

The invention relates to the technical field of wireless communication networks, and discloses a method for quickly establishing an indoor positioning system, which comprises the following steps of: among wireless communication nodes without position calibration, dynamically establishing a topological logic relationship based on Pearson's correlation coefficients of entropy change among the nodes by periodically calculating and broadcasting entropy representing signal environment fluctuation; according to the method, the node proximity relation is verified through entropy change synchronism, dependence of traditional positioning on physical coordinate calibration is avoided, and instantaneous self-organization of the topological network is achieved; environmental disturbance is reversed into a natural beacon for verifying a topological relation, so that the system endogenously maintains structural consistency in dynamic change; the terminal location description directly anchors environmental physical nodes, providing intuitive and robust relative location awareness.

The invention discloses a person and post matching method and system based on a fusion graph neural network, and electronic equipment, and belongs to the technical field of natural language processing and graph neural network crossing. The method comprises the following steps: acquiring position description text data and job seeker resume text data, and preprocessing the position description text data and the job seeker resume text data; performing semantic coding on the preprocessed position description and resume text to generate a high-dimensional text feature vector; constructing graph structure data; performing node information propagation and fusion on the graph structure by using a graph neural network, and updating node features through a multilayer graph convolution operation; a deep learning matching degree calculation module is combined to calculate the comprehensive matching degree of the position and the job seeker; and outputting a matching result of the position and the resume. According to the method, complex position and job seeker information can be efficiently processed, and the precision and efficiency of position description and resume matching are remarkably improved.

The embodiment of the invention belongs to the technical field of artificial intelligence, and particularly relates to an intelligent recommendation method and device for insurance products, computing equipment and a storage medium, and the method comprises the steps: extracting key information of the insurance products from an insurance product poster through an OCR technology and a large language model; enterprise information of the insurance applicant and personal information of the insured person are extracted, the enterprise information comprises enterprise names, unified credit codes, belonging industries, regions and operating ranges, and the personal information comprises employee names, position names, ages, genders and births; performing standardization processing on position names provided by enterprises and supplementing position description information; and carrying out region matching, occupational matching, age matching and number matching on the key information of the insurance product, the enterprise information of the insurance applicant and the personal information of the insured, and outputting an insurance product recommendation set for the insurance applicant by combining matching results.

The invention discloses a position description generation method and device based on a large model and a storage medium. The method comprises the steps of receiving a recruitment demand text input by a user; inputting the recruitment demand text into a position description generation model to obtain a plurality of candidate position descriptions; scoring each candidate position description according to a preset scoring strategy to obtain a scoring result; and determining the candidate position description with the highest score as the optimal position description according to the scoring result, and outputting the optimal position description. According to the invention, when the position description is generated, the plurality of candidate position descriptions are firstly generated, and then the optimal position description is selected from the plurality of candidate position descriptions, so that the generation quality of the position description is prevented from being uncontrollable, the generation quality of the position description is improved, a recruiter does not need to carry out manual verification and modification, and the efficiency of the recruiter is improved. And the generation efficiency of the position description is improved.

The application discloses a data synchronization method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining position information; determining a first target model according to the difference between the position information and historical position information recorded in a feature database, and version update data of a position feature generation model used by the historical position information, wherein the historical position information comprises a historical position identifier and historical position description information corresponding to the historical position identifier; calling the first target model, and analyzing first field data in first position description information through the first target model to obtain target position feature information corresponding to the first position description information; storing the first position description information and the target position feature information in the feature database corresponding to the first position identifier, so as to provide consumption data to a data consumer through the feature database. The embodiment of the application can improve the synchronization efficiency of recruitment information.

The application provides a region sound field adjustment method based on an inductive directional sound source, a server and a medium, a position description of a target object is acquired by an inductor, and a directional sound source is controlled to output associated first audio content; in a playing process, semantic paragraph division mark points pre-implanted in the audio are parsed, a remaining output duration of a nearest semantic breakpoint is determined according to a current output progress, and second audio content is pre-fetched from a preset audio content library to an output cache in combination with the position description; meanwhile, a position description sequence of the target object is continuously acquired and position fluctuation analysis is performed, a description representing a residence tendency strength degree is generated; when the residence tendency reaches a preset reference and playing reaches any semantic breakpoint, the first audio content tail and the second audio content starting end are continuously spliced into an uninterrupted connection audio stream and output; then the second audio content is continuously cycled as new first audio content until the inductive signal disappears. The application can avoid abrupt sound jumps.

The invention provides a resource adaptation method and a related device, and relates to the technical field of Android development, and the method comprises the following steps: scanning a to-be-translated item in an item file according to a preset mark, and extracting a key attribute of the to-be-translated item, the key attribute comprising a source language text, a semantic scene and a position description; translating the source language text based on the semantic scene to obtain a target language text and a resource identifier of the to-be-translated item; and generating a resource file of the target language text through resource writing, and replacing the source language text in the project file with the resource identifier by using the position description so as to call the resource file by using the resource identifier when the project file runs. According to the method, full-process automation of automatic extraction of the to-be-translated item, multi-language translation, generation of the resource file and code reference and replacement can be automatically realized, and the development efficiency and the multi-language adaptation accuracy are improved.

The application discloses a kind of map geographic position information processing method and system, receive the geographic position data to be handled that user uploads, the latitude and longitude information in it is converted into string, and according to string query geographic position cache service, if the query result is not existing position description information, latitude and longitude information is converted into position description information, and string, latitude and longitude information and position description information are written into geographic position cache service, if the query result is existing position description information, return position description information, to this will the position description information cached storage obtained by conversion, need not again through network call third party conversion interface, effectively reduce the request number of times through network with third party map interface, and avoid the problem that conversion efficiency is not high due to the instability that network transmission can exist, to improve map geographic position conversion efficiency, and avoid the waste of network transmission flow.

The invention discloses a training method of a semantic analysis model for recalled positions and resumes. The training method of the semantic analysis model used for recalled positions and resumes comprises the steps that delivery behavior data, user resume data and position description data of a user are obtained, and the delivery behavior data comprise positions where the user delivers the resumes; based on the positions of the resumes delivered by the user, constructing matching samples of the positions of the resumes; based on a pre-configured language analysis model, identifying the delivery behavior data, the user resume data and the position description data corresponding to the matching samples, and screening out the matching samples corresponding to the user resume data which does not meet the position constraint requirements to obtain positive matching samples; in the samples which do not meet the position constraint requirements, negative matching samples are extracted; and performing fine tuning training on a pre-constructed semantic analysis model based on the positive matching sample and the negative matching sample to generate a semantic analysis model of the position and the resume.

The invention discloses a display method and electronic equipment. The method comprises the steps that first information is displayed in a first area; the first information at least comprises a three-dimensional model; displaying the second information in the second area; the second information at least comprises point position description of the three-dimensional model; the point position description at least can reflect a hierarchical structure and / or point position attributes between model point positions of the three-dimensional model; and in response to the display change of any one of the first area and the second area, adjusting the display of the other area, so that the model point locations displayed in the first area are in one-to-one correspondence with the point location descriptions displayed in the second area.

The invention provides a controllable multi-mode perception model for a space-time agent and the space-time agent, and relates to the technical field of agents. The multi-modal encoder encodes the multi-modal data and converts the multi-modal data into encoding features; the input projector projects the coding features of the multi-modal data to the same feature space, and the geographic space encoder aligns the coding features of the multi-modal data; the multi-layer Transform neural network carries out reasoning according to the aligned coding characteristics; the output projector converts the reasoning result into instruction features suitable for being used by the multi-mode generator; and the multi-modal generator executes different commands according to the instruction characteristics and outputs data of multiple modals. The problem of position description identification deviation is effectively solved, spatio-temporal data modes such as moving tracks and vector maps are supported, the time sequence prediction accuracy is improved, the sensing accuracy and reliability of geographic space tasks are improved, and multiple spatio-temporal data modes are supported.

The invention relates to the technical field of natural language processing, and discloses a recruitment information and resume matching method, which comprises the following steps: firstly, converting a position description text and a resume text into vector sequences, respectively inputting the vector sequences into a recurrent neural network for encoding, aggregating position side codes into position vectors, and extracting a hidden state sequence from a resume side; segmenting the hidden state sequence according to window parameters, and obtaining collapse measurement in each segment through state derivative calculation and matrix operation; generating a time weight according to collapse measurement and adjustment parameters, and performing weighted aggregation on the hidden state sequence to obtain a resume vector; and finally, calculating the similarity between the resume vector and the position vector to obtain a matching score, comparing the matching score with a threshold parameter, and outputting a resume matching or resume mismatching result to realize inhibition and high-precision semantic matching of the resistant resume.

The invention provides a resume processing method and system based on multi-modal semantic matching, and the method comprises the steps: obtaining a resume document of a candidate, and processing the resume document to obtain a candidate portrait; semantic analysis is carried out on the position description of the target position, and a position portrait is constructed; and performing semantic matching on the candidate portrait and the post portrait based on a double-tower deep neural network model to obtain a person-post matching degree score of the resume document and the target post, and generating a candidate recommendation report based on a large language model. According to the method, the resume screening efficiency is improved, and meanwhile, the resume analysis accuracy is improved, so that the man-post matching is more accurate.

The invention discloses a resume screening method and device, electronic equipment and a storage medium. The method comprises the following steps: determining key features and weights of the key features according to data of alternative resumes; determining a key vector of the alternative resume according to each key feature and the weight of each key feature; determining an output vector of each primary capsule according to a key vector of the alternative resume, a primary coefficient in trained weight coefficients and at least one primary capsule in the primary capsule layer; according to the output vector of each primary capsule, a high-level coefficient in the weight coefficient and at least one high-level capsule in the high-level capsule layer, determining the output vector of each high-level capsule; determining the matching probability of the alternative resumes according to the output vector of each high-level capsule; and screening out a target resume corresponding to the position description information from the alternative resumes. According to the technical scheme, the resume screening accuracy can be improved.

The present invention provides a method and system for employee position matching and allocation based on artificial intelligence, which relates to the field of artificial intelligence technology and includes: generating an optimized employee ability feature vector based on historical employee work data, extracting the employee ability development trend, combining team collaboration data, obtaining an employee comprehensive ability vector by using a cross-modal contrastive learning network, calculating a development potential index, constructing a position skill knowledge graph based on position description data and historical recruitment data, generating a position skill feature matrix and a team structure feature vector through a dynamic heterogeneous graph neural network and an adaptive graph attention network, combining the employee comprehensive ability vector, calculating an employee-position matching degree score matrix, inputting the matching degree score matrix and the development potential index into a distributed multi-agent reinforcement learning model, constructing a reward function, generating and evaluating a deployment plan through hierarchical task decomposition and Monte Carlo tree search, and finally outputting a deployment execution plan.

The invention belongs to the technical field of artificial intelligence recruitment, and provides an automatic resume recommendation system and method based on artificial intelligence. The system comprises a resume processing unit, a position processing unit, an artificial intelligence matching engine and a recommendation generation unit. According to the method, text semantics and structural features are extracted by analyzing resume and position description, deep semantic comprehension and vectorization expression are performed by using a pre-trained Transform model, and a semantic matching degree score is calculated; key rule features such as working experience / educational background / skill / geographic position are fused, and a final matching score is generated through weighted calculation or threshold filtering; generating a recommendation list according to the matching score sequence, and outputting an interpretability description based on an attention mechanism; and meanwhile, designing a feedback driving mechanism, and continuously collecting user operation behavior iterative optimization model parameters. According to the method, deep semantic matching and rule constraint collaboration are achieved, the adaptive evolution capability is achieved, and the problems of semantic understanding deficiency and rule stiffness in traditional screening are solved.

Embodiments of the described technologies receive, via a user interface, an input associated with a first user of a user connection network. The input identifies first position data related to a position capable of being filled by a hiring of a person. In response to validating the first position data, second position data different from the first position data is extracted from the user connection network, based on the first position data. A first prompt is formulated based on the first position data and the second position data. The first prompt is sent to a generative language model. A first piece of writing is received from the generative language model. The first piece of writing includes a position description output by the generative language model based on the first prompt. The position description is sent to the user interface in response to the input.

The invention discloses an NLP-based recruitment behavior skill data encryption protection system and method, and relates to the technical field of data encryption protection, and the system comprises a skill extraction module which is used for carrying out the behavior skill extraction of obtained position description data through a natural language processing model, and obtaining a behavior skill index; the skill quantification module is used for performing skill effect quantity analysis on the acquired behavior data to obtain a behavior skill quantification benchmark; the encryption protection module is used for performing encryption processing on the obtained recruitment data to obtain behavior encryption data; and the skill matching module is used for carrying out behavior skill encryption analysis on the behavior encryption data to obtain a skill radar map, and carrying out matching analysis on the skill radar map and the behavior skill quantification reference to obtain a skill matching degree. According to the method, the quality and efficiency of enterprise recruitment decision making are remarkably improved, and the bottleneck of subjectivity and low efficiency of a traditional manual definition post standard is broken through.