44 results about "Questionnaire data" patented technology

The invention discloses a risk assessment method and system based on a Bayesian network and an evidence theory, and relates to the technical field of risk intelligent assessment, and the method comprises the steps: determining an assessment dimension and an assessment index of a high-investment low-income risk of an educational institution in MOOC learning according to a human-cargo-field model and an industry report; constructing a MOOC learning risk assessment index system according to the assessment dimensions and the assessment indexes; constructing a Bayesian network structure according to the MOOC learning risk assessment index system; obtaining questionnaire data and expert opinions according to the MOOC learning risk assessment index system, and determining Bayesian network parameters based on the questionnaire data and the expert opinions; and inputting the Bayesian network parameters into the Bayesian network structure to obtain an assessment result of the high-investment low-income risk, the assessment result including a risk prediction result, a key risk factor and a sensitivity analysis result. According to the method, the high-investment and low-income risk in MOOC learning can be accurately evaluated.

The invention discloses a processing method, system and device for intelligent questionnaire survey and a medium, and the method specifically comprises the steps: obtaining questionnaire data and evaluation parameter setting inputted by a user, calling a main model to carry out universal dimension inspection on a questionnaire, and obtaining a preliminary analysis result; according to a preliminary analysis result, distributing different types of problems to corresponding expert models for deep analysis; in combination with culture feature data inquired in real time, a culture suitability score is generated to supplement an analysis result of the expert model; based on the analysis results of the plurality of expert models, performing weighted fusion processing on the score of each dimension by using a weight coefficient dynamically adjusted through a reinforcement learning mechanism to obtain a comprehensive evaluation score; the comprehensive evaluation score is returned to the user interface, feedback data are collected after the user completes interaction, and the feedback data are used for iteratively updating model parameters and setting evaluation parameters. According to the invention, efficient and accurate examination of questionnaire contents is realized.

An information processing device according to one aspect of the present invention performs intervention using a negative incentive in a program, the information processing device comprising: an acquisition unit that acquires questionnaire data including a question allowing the measurement of the current bias of a user; a first determination unit that determines the degree of the current bias of the user on the basis of the questionnaire data; a second determination unit that determines the length of a term, a period in which a reward for the incentive is determined, on the basis of the current bias; and a calculation unit that calculates, on the basis of the term, an initial grant incentive granted at the start of the program.

The invention discloses a data analysis method and system based on questionnaire investigation, and particularly relates to the technical field of data analysis, and the method comprises the following steps: S1, collecting and preprocessing questionnaire data, and obtaining original questionnaire data; s2, questionnaire feature engineering: extracting core features from the standardized questionnaire data set based on a joint screening mechanism of semantic similarity and information gain, and obtaining low-dimensional feature vectors through a dimension reduction algorithm; s3, subject mining and user group division are carried out on the low-dimensional feature vectors; and S4, outputting a result based on the analysis model, and generating a targeted questionnaire analysis report which comprises topic distribution, group difference and potential demand association conclusions. According to the data analysis method and system based on questionnaire investigation, through a multi-strategy fusion preprocessing mechanism, a combined screening feature engineering method, a fusion modeling analysis strategy and a self-adaptive model optimization module, the accuracy and efficiency of questionnaire data analysis are improved.

Questionnaire completion systems and methodologies for a data platform. The data platform receives from a consumer an unstructured questionnaire to be completed based on structured database objects, semi-structured database objects, and unstructured database objects stored on the data platform by a provider. The data platform generates a secured completion of the unstructured questionnaire based on a questionnaire completion model and the unstructured questionnaire. The data platform determines a confidence score for the completion and in response to determining the confidence score does not exceed a threshold value, the data platform generates a structured query based on the unstructured questionnaire and a structured query model, and generates the secured completion based on querying the structured database objects using the structured query. The data platform applies a security function to the secured completion to generate a completion of the unstructured questionnaire and provides the completion to the consumer.

An object of a system according to an embodiment is to extract useful information from a large amount of questionnaire data and propose an appropriate measure.SOLUTION: A system includes a questionnaire data collection part, a preprocessing part, a classification analysis part, a comment extraction part, and an improvement plan proposal part. The questionnaire data collection part collects questionnaire data. The preprocessing unit preprocesses the questionnaire data collected by the questionnaire data collection unit. The classification analysis unit classifies and analyzes the questionnaire data preprocessed by the preprocessing unit. The comment extraction unit extracts a useful comment from the data classified and analyzed by the classification analysis unit. The improvement plan proposal unit proposes an improvement plan based on the comment extracted by the comment extraction unit.SELECTED DRAWING: Figure 1

This specification provides a multimodal emotion recognition index construction system and method, wherein the method includes: collecting first questionnaire data and first voice data of a user to be identified; preprocessing the first questionnaire data and the first voice data to obtain observed variables in the first questionnaire data and the first voice data; inputting the observed variables of the user to be identified into a trained emotion recognition model, wherein the emotion recognition model outputs values ​​corresponding to different emotion types for the user to be identified based on the correlation between the observed variables and different emotion types; and determining the true emotion type of the user to be identified based on the values ​​of the different emotion types. The method of this specification can improve the accuracy of prediction.

This invention discloses a graph mining-based questionnaire analysis method, system, electronic device, and medium, relating to the field of data processing. The method includes: acquiring questionnaire data to be analyzed; establishing a questionnaire matrix based on the questionnaire data; cleaning the questionnaire matrix to obtain a scoring matrix; calculating the similarity between different attribute scores based on the scoring matrix to establish a core attribute adjacency matrix; using attributes in the core attribute adjacency matrix as nodes in the network to establish a core attribute network; performing graph mining on the core attribute network to obtain a minimal core attribute network; and analyzing the influence of different core attributes based on the minimal core attribute network to obtain the questionnaire analysis results. This invention can reduce the influence of extreme data in questionnaires and improve the interpretability of the data in questionnaires.

The embodiment of the invention provides an anomaly detection method and system. The method comprises the steps that the electronic equipment responds to user operation and sends an NPS questionnaire to an anomaly detection platform; the anomaly detection platform obtains first data of an electronic device corresponding to the NPS questionnaire when the user source sound of the NPS questionnaire is fuzzy and unclear; the exception detection platform determines an exception field of the electronic equipment according to the first data, and determines exception data of the electronic equipment in the exception field; and the anomaly detection platform obtains second data of the electronic equipment, and determines anomaly detection data of the electronic equipment according to the second data and the anomaly data in the anomaly field. Therefore, the anomaly detection platform can determine the anomaly of the electronic equipment when the user source sound of the NPS questionnaire is fuzzy and unclear, so that the anomaly detection capability of the electronic equipment is improved, the problems that the NPS questionnaire with fuzzy and unclear user source sound is difficult to analyze and the equipment anomaly cannot be identified are solved, and the resource waste of NPS questionnaire data is avoided.

The invention provides a psychological questionnaire data analysis method and system based on a hidden variable model, and belongs to the technical field of data analysis. The method comprises the steps that a first questionnaire data set is acquired, the first questionnaire data set comprises a plurality of effective filling results about a preset psychological questionnaire, and the preset psychological questionnaire comprises a plurality of psychological evaluation question items and a plurality of grade score options corresponding to each psychological evaluation question item; performing standardization processing on the first questionnaire data set to obtain a second questionnaire data set; taking the plurality of psychological evaluation items as a plurality of observation variables and constructing an undirected graph, and separating the undirected graph according to the second questionnaire data set and a first preset transformation independent noise condition to form all single factor sets; and according to the second questionnaire data set and a second preset transformation independent noise condition, determining a causal direction among all hidden variables corresponding to all the single factor sets to form a causal structure diagram. The accuracy of identifying the causal structure between the psychological hidden variables can be improved.

The invention discloses an EV user psychological portrait identification guiding method and device based on hidden variable identification, and the method comprises the steps: obtaining the subjective evaluation data of a user through a Like seven-point scale, obtaining the four psychological hidden variables: perception information dependence, user friendliness, perception risk, and response enthusiasm through exploratory factor analysis, and carrying out the recognition of the psychological portrait of the EV user. Constructing a psychological hidden variable model; the reliability and validity of the model are tested through the measurement model, and a stable psychological hidden variable model is obtained through optimization; constructing a structural equation model, and obtaining an effective structural equation model through maximum likelihood estimation and fitting test; user questionnaire data are aggregated, hidden variable scores are calculated, score grades are divided through a quantile method and summed, five user response types are determined according to the total score, and a differentiation incentive strategy is matched. The method can improve the power grid demand response efficiency, assists the stable operation of the power system, and can be applied to a load aggregator system and other scenes.

The invention discloses a questionnaire index system construction method, a questionnaire index system construction device, equipment, a medium and a product, and relates to the field of questionnaire indexes. According to the questionnaire result, processing each option in each multi-choice question by adopting an improved multiple dichotomy to obtain a sparse matrix corresponding to each multi-choice question; performing data inspection on the codes corresponding to the options in the single-choice questions and the sparse matrixes corresponding to the multiple-choice questions, and correcting or eliminating the questions according to an inspection result; inputting the questions into a random forest model to obtain an initial index system; and R-type clustering is performed on the initial index system, and the index system of the target questionnaire is constructed according to the clustering result, so that human prejudice interference can be avoided, complex interaction among questionnaire data can be captured, the efficiency can be improved, the interpretability can be enhanced, and the situation of over-fitting or information loss can be avoided in the face of high-dimensional questionnaire data.

Various methods and processes, apparatuses / systems, and media for questionnaire data digitization and reconciliation are disclosed. A processor generates an autonomous program for continuously monitoring shared mailbox for unread emails having questionnaire data containing a plurality of line items filled out by a client; converts, by utilizing an OCR tool, the questionnaire data containing the plurality of line items into a machine-readable format data; reads, by utilizing an automated reconciliation tool, the machine-readable format data for each line item; compares, by utilizing the automated reconciliation tool, data for each line item against a corresponding predefined guidance data; identifies, based on comparing, missing response data, negative response data, and insufficient response data corresponding to the questionnaire data filled out by the client by applying predefined rules; and automatically reconciles the missing response data, negative response data, and insufficient response data.

The application discloses an intelligent teaching method fusing sound, meaning and object, and the method is characterized in that: initial course sets are matched by quantized scoring and ability grading matching through acquisition of evaluation questionnaire data, teaching path sequences are generated through a path planning algorithm, mapping is performed from five sensory perception dimensions and structured courseware sequences are assembled, real operation videos are received after the courseware is presented to a parent terminal, test result reports are generated through multi-modal three-level cascade evaluation, and it is judged whether to trigger path adjustment and update the ability vector to regenerate the adjusted path according to the test result report. The application solves the technical problems of single teaching dimension, weak generalization ability and lack of personalized adaptation in the prior art, and meets the strict quality requirements of family intervention for children with spectrum disorders.

We provide a system that integrates and manages survey data, behavioral data, and social media data collected from residents, and analyzes them. [Solution] A system comprising: means for managing questionnaire data collected from residents; means for connecting to sensors for collecting residents' behavioral data; means for collecting social media data to which residents have consented; means for analyzing this data and generating residents' digital profiles; means for generating avatars that mimic the residents' thought patterns based on the generated digital profiles; means for executing simulations in which the avatars operate on a digital twin; means for analyzing the simulation results and generating urban planning information; and means for providing local currency as an incentive based on the data provided by residents.

The application relates to the computer technical field and provides an evaluation data acquisition method, an evaluation data acquisition device and a storage medium. The evaluation data acquisition method comprises the following steps: a client acquires questionnaire data based on a target questionnaire under the condition that a user state evaluation condition is met; it is determined whether a first strategy determination condition of a question answering progress of the target questionnaire is met; a first data acquisition strategy is determined based on the questionnaire data under the condition that the first strategy determination condition of the question answering progress is met; client data of the client is acquired based on the first data acquisition strategy; and the questionnaire data and the client data are sent to a server. The problem that an evaluation data acquisition process occupies too many resources can be solved. Since the client data of the client is acquired based on the first data acquisition strategy under the condition that the first strategy determination condition of the question answering progress is met, the client data does not need to be acquired in full, the influence on the operation of the client and the server can be reduced, and therefore the resource amount occupied by the data acquisition process can be reduced.

The invention provides a questionnaire missing data filling method, system and device and a medium, and the method comprises the steps: firstly building a questionnaire logic rule base through association rule mining based on historical complete questionnaire data; then, for a to-be-filled missing questionnaire, utilizing the rule base to constrain a prediction boundary of the large language model, and generating a prediction value of a missing value by means of the semantic understanding capability of the large model; and finally, performing rule verification and correction on a prediction result to form a closed-loop filling mechanism. According to the method, external auxiliary data and expert priori knowledge are not needed, missing values of various question types such as single-choice, multi-choice, numerical values and texts can be adaptively and uniformly processed, the accuracy and logic consistency of filling results are remarkably improved, and the method has universal adaptation capability across different questionnaire scenes.

We provide the system. [Solution] Means for collecting survey results from customers or employees, A means of cleaning and preprocessing the collected questionnaire data, A method for passing pre-processed data to a generative artificial intelligence system to perform filtering, A means for aggregating filtering results and performing analysis based on them, A means of generating a report based on the analysis results and notifying administrators or relevant parties, A system that includes this.

The application provides a kind of intelligent inspection option exception identification method, device and electronic equipment, the method comprises: obtaining the questionnaire data to be analyzed of intelligent inspection system, the questionnaire data to be analyzed includes at least one by question and answer to be measured question and answer pair;Each question and answer pair to be measured is carried out semantic reasoning, obtains the sentiment tendency of question and answer pair to be measured, sentiment tendency is used to express the sentiment tendency expressed by question and answer pair to be measured is positive or negative;According to the sentiment tendency of each question and answer pair to be measured, determine the analysis result of each question and answer pair to be measured, analysis result is used to express whether the inspection project associated with question exists security risk.The method, device and equipment can be quickly analyzed for different formats, different content of questionnaire data, determine whether the inspection project associated with question in questionnaire data exists security risk, improve the efficiency and accuracy of questionnaire data analysis.

The application discloses a risk assessment method and system based on a Bayesian network and evidence theory, relates to the technical field of intelligent risk assessment, and comprises the following steps: determining an evaluation dimension and evaluation index of a high-investment low-yield risk in MOOC learning of an educational institution according to a person-goods-site model and an industry report; constructing a MOOC learning risk assessment index system according to the evaluation dimension and the evaluation index; constructing a Bayesian network structure according to the MOOC learning risk assessment index system; obtaining questionnaire data and expert opinions according to the MOOC learning risk assessment index system, and determining Bayesian network parameters based on the questionnaire data and the expert opinions; inputting the Bayesian network parameters into the Bayesian network structure to obtain an evaluation result of the high-investment low-yield risk, wherein the evaluation result comprises a risk prediction result, a key risk factor and a sensitivity analysis result. The application can accurately evaluate the high-investment low-yield risk in MOOC learning.

The objective is to provide an efficient method for obtaining responses from businesses to questionnaires regarding ESG evaluations. [Solution] A method for managing data related to a business operator's ESG evaluation, which is performed by a management terminal, wherein the control unit of the management terminal refers to questions included in questionnaire data related to the business operator's ESG evaluation, refers to the business operator's departmental information, and determines the department responsible for answering the questions.

This invention relates to the field of electronic digital data processing technology, specifically to a low-quality data filtering system and method for multi-source questionnaire data. The method includes: acquiring raw questionnaire data from target users, including questions and answers; analyzing the regularity of responses using answer sequences to obtain a regularity performance index for the target users; determining the necessity of consideration for target questions using the text length parameter of the target questions and the response time data for each user; determining the degree of carelessness in the target users' responses by combining the regularity performance index, the necessity of consideration for target questions, and the response time data for each question; determining the differences in the target users' responses to similar questions; and identifying and filtering out abnormal response data based on the degree of carelessness and the differences in responses to obtain filtered, valid questionnaire data. The technical solution of this invention significantly improves the accuracy and reliability of data quality identification.

The invention is suitable for the technical field of teaching evaluation, and provides a teacher intelligent teaching practice quality evaluation method based on an extreme learning machine algorithm. The method comprises the following steps: designing and issuing questionnaires based on an evaluation index system, collecting samples, and constructing a sample database containing multiple influence factors and comprehensive evaluation results; carrying out reliability and validity test on the questionnaire data and removing invalid and abnormal samples; feature screening is carried out by adopting decision tree feature importance ranking, redundancy elimination is realized by combining mutual information analysis and correlation threshold constraint, and an optimal feature subset is obtained; dividing the data set into a training set and a test set, determining model parameters in the training set by adopting hierarchical K-fold cross validation, and establishing an extreme learning machine classification model; and evaluating the performance of the model through the accuracy rate, the precision rate, the recall rate, the confusion matrix and the Kappa coefficient. Quantitative evaluation and decision feedback of intelligent teaching practice quality of college teachers can be realized, and reusable method support is provided for similar quality evaluation.

The application belongs to the technical field of restaurant service control, and particularly relates to a restaurant service control system and a control method thereof. The system comprises a service item planning control module and a dining service utility optimization module. The service item planning control module comprises a service item database, a service item evaluation component and a service item planning component. The service item planning control module comprises a service item database, a service item evaluation component and a service item planning component. The service item evaluation component is internally provided with an editable questionnaire database and a questionnaire interaction terminal. The service item planning component is used for establishing a service item interaction evaluation data flow and analyzing the priority of service items according to questionnaire survey data. The application is mainly used for providing an execution and optimization scheme for optimizing various service items in the restaurant service process to improve the customer service quality, and dynamically optimizing the customer dining utility and improving the restaurant dining experience by controlling food addition and service delay.

The invention discloses an enterprise digital level diagnosis report generation system based on a large language model, and belongs to the technical field of enterprise digital level diagnosis, and the system comprises a data input module, a cue word engineering module, a model reasoning module and a report generation module which work cooperatively in sequence; the data input module is used for receiving and analyzing the standardized questionnaire data submitted by the user and performing data type conversion and data standardization processing on the analyzed data; the cue word engineering module is used for constructing a dynamic cue word template, and the dynamic cue word template comprises a basic task description framework and processed questionnaire data context embedding and output format specification requirements; the model reasoning module is used for formatting the dynamic cue word template, configuring model reasoning parameters and inputting the formatted cue words into a large language model to obtain an initial reasoning result; and the report generation module is used for post-processing the initial reasoning result and generating a standardized diagnosis report.

Embodiments of the present application provide a data processing method, a server and a computer readable storage medium, wherein the method comprises: receiving a login request for a target user sent by a client, the login request comprising user attributes associated with a first questionnaire; the login request is generated by the client after obtaining questionnaire data of the first questionnaire from a data server; after obtaining first user information of the target user corresponding to the user attributes associated with the first questionnaire, generating a first user identifier of the target user; and sending the first user identifier of the target user to the client, so that the client sends the filled first questionnaire and the first user identifier of the target user to the data server, thereby ensuring the privacy and security of the user filling the questionnaire.

To provide a method for efficiently achieving an answer to a questionnaire related to ESG evaluation by an entrepreneur.SOLUTION: In a management method of data related to ESG evaluation of a business operator executed by a management terminal, a control unit of the management terminal receives an inquiry about questionnaire data related to the ESG evaluation of the business operator from a business operator terminal, transmits an answer to the inquiry, and guides contents related to the questionnaire data related to the inquiry.SELECTED DRAWING: Figure 11

The application discloses a high-risk game behavior prediction method and system based on multi-modal data. The method collects physiological monitoring data and psychological questionnaire data of a user simultaneously, extracts mean features and variance features, and forms a first multi-modal feature set. A cross-modal consistency residual tensor capable of quantifying the degree of psychological-physiological deviation is constructed, and a psychological-physiological difference threshold drift rate changing with time is further derived from the residual tensor to depict the non-synchronous relationship between the psychological fluctuation and the physiological load of the user. An adaptive trigger factor is generated according to the drift rate, and a second feature set composed of a drift rate interval identifier and the like is used to reflect the high-risk game tendency of the user. The second feature set is input into a trained high-risk game behavior prediction model, and finally, a prediction result of the high-risk behavior of the user is generated. The application can realize early identification of high-risk game behavior on the basis of multi-modal information fusion, and has higher accuracy and practical value.

The objective is to provide an efficient method for obtaining responses from businesses to questionnaires regarding ESG evaluations. [Solution] In a greenhouse gas emissions management system in which an administrator terminal and multiple business terminals are interconnected via a communication network, the method for managing data related to the ESG evaluation of businesses, which is performed by the administrator terminal, is as follows: The control unit of the administrator terminal receives questionnaire data from the business terminals, analyzes each of the multiple questions contained in the questionnaire data, and presents the necessary documents for each of the multiple questions.