CN110610002B - Questionnaire information processing method and device, computer equipment and storage medium - Google Patents
Questionnaire information processing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention relates to a questionnaire information processing method, a questionnaire information processing device, computer equipment and a storage medium. The method comprises the following steps: collecting questionnaire information, and converting questionnaire original data into structured standard data with predefined semantic tags; establishing an evaluation process object and constructing a mapping relation linked list among the evaluation process objects, wherein the evaluation process object is a data object containing different types of evaluation attribute information, and the evaluation process object comprises a questionnaire, a calculation model and an index system; and inputting the structured standard data into an associated calculation model according to the mapping relation linked list to acquire evaluation information. By adopting the method for processing the questionnaire information by constructing the mapping relation linked list among the evaluation process objects, the multiplexing of an index system, a calculation model and the questionnaire and the automatic processing of the evaluation process can be realized.
Description
Technical Field
The present invention relates to the field of information processing technologies, and in particular, to a method and an apparatus for processing questionnaire information, a computer device, and a storage medium.
Background
In everyday life, it is often involved to have users fill out questionnaires to evaluate a certain index by means of the questionnaires. In the related technology, usually, an assessment expert researches a set of index system, designs a corresponding questionnaire and a calculation model, an evaluator sends the questionnaire to a user in an electronic or paper mode for filling, and summarizes the paper questionnaire and/or the electronic questionnaire in different third-party data statistical analysis software in a manual mode for assessment according to the related calculation model.
For example, when evaluating the informatization level of traditional digital campus education, firstly, experts in the field study out a set of index system, and design a set of questionnaire and a calculation model which can be used for reflecting the informatization level of a school; and then the assessment staff sends the questionnaire to each school in an electronic and/or paper form to fill in, manually collects the paper questionnaire and/or the electronic questionnaire into different third-party data statistical analysis software, calculates according to a relevant calculation model, and finally obtains and displays the education informatization level index of each school.
However, the conventional evaluation method has a problem that: due to the adoption of the index system, the calculation model and the questionnaire which are designed in advance, when the evaluation content changes, a new index system, a new calculation model and a new questionnaire have to be redesigned. The coupling degree of the index system, the calculation model and the questionnaire is too high, so that one set of index system can only be evaluated by one set of questionnaire, and one set of questionnaire can only be calculated by one set of calculation model. Not conducive to the reuse of the index system, the calculation model, and the questionnaire.
Disclosure of Invention
In view of the above defects or improvement requirements of the prior art, the present application provides a method, an apparatus and a storage medium for processing questionnaire information, which can implement multiplexing of an index system, a calculation model and a questionnaire.
According to one aspect of the present application, a questionnaire information processing method of the present invention includes:
acquiring questionnaire information, and converting questionnaire original data into structured standard data with predefined semantic tags;
creating an evaluation process object and constructing a mapping relation linked list among the evaluation process objects, wherein the evaluation process object is a data object containing attribute information and comprises a questionnaire, a calculation model and an index system;
and inputting the structured standard data into an associated calculation model according to the mapping relation linked list to acquire evaluation information.
By the method for creating the evaluation process objects and constructing the mapping relation linked list among the evaluation process objects, flexible association of the index system, the calculation model and the questionnaire in the evaluation process can be supported, and multiplexing of the index system, the questionnaire and the calculation model is realized.
As a further improvement of the present application, the evaluation process object may further include one or more multidimensional analysis objects, which are data objects for implementing multidimensional association analysis.
By adopting the method for processing questionnaire information by using the evaluation process objects comprising one or more multi-dimensional analysis objects, multi-dimensional correlation analysis can be performed according to the correlation information among the evaluation process objects, so that the evaluation has the characteristic of multi-dimensional comprehensive analysis, different multi-dimensional evaluation requirements can be flexibly met, and evaluation results can be displayed in a multi-dimensional visual mode.
As a further improvement of the present application, the multidimensional analysis object includes an area object and a school object, and the creating an evaluation process object and constructing a mapping relationship linked list between the evaluation process objects specifically includes:
creating an evaluation process object, wherein the evaluation process object comprises a questionnaire, a calculation model, an index system, a region object and a school object;
creating an evaluation process object attribute;
and constructing a mapping relation linked list among the evaluation process objects.
As a further improvement of the present application, the calculation model includes a problem score calculation model, a primary index original score calculation model, a dimensionless calculation model, and a weight calculation model, and the step of inputting the structured standard data into the associated calculation model according to the mapping relation linked list to obtain the evaluation information includes the steps of:
inputting the structured standard data into an associated problem score calculation model according to the mapping relation linked list, calculating the score of the questionnaire problem, inputting the obtained questionnaire problem score into an associated primary index original score calculation model, and acquiring primary index original score information;
inputting the primary index original score information into the dimensionless calculation model according to the mapping relation linked list to obtain primary index score information;
inputting the primary index score information into the weight calculation model to obtain primary index weight information;
and acquiring index evaluation information according to the primary index weight information and the primary index score information.
As a further improvement of the present application, when the evaluation process object includes a multidimensional analysis object, the calculation model object further includes a multidimensional evaluation calculation model, and the obtaining of the index evaluation information according to the primary index weight information and the primary index score information includes the steps of:
and inputting the primary index score information and the primary index weight information into the multi-dimensional evaluation calculation model according to the mapping relation linked list to obtain multi-dimensional index evaluation information.
As a further improvement of the present application, the acquiring questionnaire, converting the raw questionnaire data into structured standard data, includes the steps of:
establishing a semantic conversion model of the questionnaire answers;
establishing a semantic conversion model of the questionnaire options;
collecting data and converting the data into structured standard data, establishing a mapping relation among the questionnaire numbers, the question numbers and the question option numbers, and establishing a mapping relation among the questionnaire numbers, the question option numbers and the question answers.
As a further improvement of the present application, after the step of inputting the structured standard data into the associated computation model according to the mapping relation linked list to obtain the evaluation information, the method further includes the steps of:
and matching the evaluation information push content according to the user type, and sending the matched evaluation information push content to the user.
According to another aspect of the present application, the present invention provides a questionnaire information processing apparatus comprising:
the data acquisition processing module is used for acquiring the questionnaire and converting the original data of the questionnaire into structured standard data;
the system comprises a mapping relation linked list construction module, a calculation module and a calculation module, wherein the mapping relation linked list construction module is used for creating evaluation process objects and constructing a mapping relation linked list among the evaluation process objects, the evaluation process objects are data objects containing attribute information, and the evaluation process objects comprise questionnaires, calculation models and index systems;
and the execution module is used for inputting the structured standard data into the associated calculation model according to the mapping relation linked list to acquire the evaluation information.
According to another aspect of the application, the invention provides a computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.
According to another aspect of the application, the invention provides a computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 7.
In summary, the questionnaire information processing method, the apparatus, the computer device and the storage medium provided by the present application support flexible association of the index system, the calculation model and the questionnaire in the evaluation process by adopting the method of creating the evaluation process object and constructing the mapping relation linked list between the evaluation process objects, and when the evaluation requirement changes, can flexibly change the association information between the index system, the calculation model and the questionnaire, and can re-evaluate to meet the new evaluation requirement without re-designing the new index system, the questionnaire and the calculation model, thereby realizing multiplexing of the index system, the questionnaire and the calculation model. Further, according to the method and the device, multi-dimensional association analysis can be carried out according to the association information among the evaluation process objects, and evaluation results can be displayed in a visual mode from multiple dimensions. Furthermore, the questionnaire data can be more accurately entered, and the problems that data are wrong and lost easily due to the fact that a mode that questionnaires are manually entered and gathered into third-party software in a traditional evaluation method are solved. In addition, the evaluation content can be pushed in a personalized mode according to the user type.
Drawings
Fig. 1 is a schematic diagram of a questionnaire information processing method provided in embodiment 1 of the present application;
fig. 2 is a schematic diagram of a questionnaire information processing method provided in embodiment 2 of the present application;
fig. 3 is a schematic diagram of a data acquisition and formatting processing method provided in embodiment 2 of the present application;
FIG. 4 is a schematic diagram of an information network for establishing an object association of an evaluation process provided in embodiment 2 of the present application;
FIG. 5 is a schematic diagram of evaluation according to an evaluation process object relationship provided in embodiment 2 of the present application;
fig. 6 is a schematic diagram of personalized push service provided in embodiment 2 of the present application;
fig. 7 is a schematic diagram of a mapping relationship of questionnaire answer information provided in embodiment 2 of the present application;
FIG. 8 is an exemplary diagram of the evaluation of attributes, relationships and extensions between process objects provided in embodiment 2 of the present application;
fig. 9 is a schematic diagram of pushing an evaluation result message provided in embodiment 2 of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. In addition, the technical features described in the embodiments may be combined with each other as long as they do not conflict with each other.
The scheme provided by the embodiment of the application can be applied to a scene of acquiring evaluation information in a questionnaire, index and calculation model manner, for example, can be applied to education informatization level evaluation and can also be applied to insurance risk evaluation. According to the scheme provided by the embodiment of the application, the evaluation process objects can be created, the mapping relation linked list among the evaluation process objects can be constructed, and the structured standard data can be input into the associated calculation model according to the mapping relation linked list to obtain the evaluation information. By adopting the method, the evaluation process objects can be flexibly established and the mapping relation linked list among the evaluation process objects can be constructed for different evaluation requirements, so that one set of index system, questionnaire and calculation model questionnaire can be realized, different evaluation requirements can be met, a new index system, questionnaire and calculation model do not need to be redesigned, and the multiplexing of the index system, the questionnaire and the calculation model is realized.
Example 1:
the present embodiment provides a questionnaire information processing method, as shown in fig. 1, the method including the steps of:
s11: and acquiring questionnaire information, and converting the questionnaire original information into structured standard data with predefined semantic tags.
The questionnaire may be a paper questionnaire or an electronic questionnaire, or a collection of both. There are several alternative implementations in the prior art for how to collect questionnaires and convert them into structured standard data.
The data after standard formatting can be conveniently subjected to subsequent data processing and evaluation by a computer and software, so that the consistency of questionnaire data is realized from the source, and a data basis is provided for subsequent data integration and data processing which are evaluated based on the associated information.
S12: creating an evaluation process object and constructing a mapping relation linked list among the evaluation process objects, wherein the evaluation process object is a data object containing different types of evaluation attribute information, and the evaluation process object comprises a questionnaire, a calculation model and an index system.
The evaluation process object is a series of independent and interrelated data objects which contain specific category attribute information and abstract questionnaire data and related information participating in an evaluation process, and specifically comprises a questionnaire, a calculation model and an index system. The mapping relation linked list is a metadata list of the evaluation process objects directly or indirectly participating in the questionnaire data evaluation process, and comprises associated attribute information among the evaluation process objects, trigger conditions and constraint information participating in the evaluation process, mapping information of the storage space of the evaluation process objects and the like.
In order to obtain the evaluation score information of the index, the evaluation process object comprises a questionnaire object, a calculation model object and an index system object.
When the evaluation requirement information comprises multi-dimensional correlation analysis requirement information for evaluation, the evaluation process object can also comprise one or more multi-dimensional analysis objects. The multidimensional analysis object is a data object for realizing multidimensional correlation analysis. For example, when the evaluation requirements include associative analysis requirements for regional dimensions, the evaluation process objects also include regional objects. When the evaluation requirements include correlation analysis requirements for a time dimension, the evaluation process object also includes a time object. When evaluating requirements includes correlating analysis requirements for management dimensions, evaluating process objects also includes managing dimension objects. When the evaluation process object comprises a multi-dimensional analysis process object, multi-dimensional correlation analysis of an evaluation result can be realized, and visualization modeling can be performed to realize visualization of multi-dimensional evaluation.
Evaluating a linked list of mapping relationships between process objects may be understood as evaluating mapping relationships between process objects. For example, the questionnaire includes a plurality of questions, namely question 1 and question 2 … …, question N, a plurality of indicators, namely indicator 1 and indicator 2 … …, indicator M, and a plurality of calculation models, namely calculation model 1 and calculation model 2 … …, indicator L. It can be determined which of the problems the index 1 and the index 2 … … index M can be associated with, respectively, according to the evaluation requirement information, which of the calculation models the problem 1 and the problem 2 … … problem N can be respectively scored by, and which of the calculation models the index 1 and the index 2 … … index M can be evaluated by, according to the problem type. When the indexes comprise multi-level indexes, the method can also determine which primary indexes are associated with the parent indexes, which problems are associated with the primary indexes, and which calculation models the primary indexes and the parent indexes are respectively associated with.
When the evaluation requirement information is changed, a mapping relation list among evaluation process objects can be flexibly constructed without redesigning a questionnaire, a calculation model and an index system.
S13: and inputting the structured standard data into an associated calculation model according to the mapping relation linked list to obtain evaluation information.
The evaluation information may be understood as evaluation result information obtained by inputting the structured standard data to the associated calculation model. The question score can be calculated according to the correlation information between the questionnaire object and the calculation model; and obtaining evaluation information according to the correlation information between the index system object and the questionnaire object and the calculation model.
By adopting the method for evaluating based on the correlation information among the evaluation process objects, the flexible correlation of the evaluation process objects in the evaluation process is supported. When the evaluation requirement is changed, the mapping relation linked list among the index system, the calculation model and the questionnaire can be flexibly changed, so that the new evaluation requirement can be met, a new index system, the questionnaire and the calculation model do not need to be redesigned, and the multiplexing of the index system, the questionnaire and the calculation model is realized. And a calculation model can be predefined to realize automatic processing of evaluation.
Furthermore, when the evaluation process object comprises a multi-dimensional analysis object, multi-dimensional correlation analysis can be performed according to the correlation information among the evaluation process objects, so that the evaluation has the characteristic of multi-dimensional comprehensive analysis, different multi-dimensional evaluation requirements can be flexibly met, and the evaluation result can be displayed in a visual mode from multiple dimensions. For example, when the evaluation process object includes a region object, a correlation analysis may be performed on a certain indicator of a certain region or a different region. When the evaluation process object includes a time object, a correlation analysis may be performed on an indicator at a certain time or at a different time. When the evaluation process object comprises a management dimension process object, a correlation analysis may be performed on a certain index of a certain management layer or different management layers.
Step S14 may also be included after step S13: matching the evaluation information push content according to the user type, and sending the matched evaluation information push content to the user.
Defining user types, establishing a subscribeable evaluation content push mechanism, establishing an evaluation content recommendation model, and providing personalized evaluation content push service for different user types.
Example 2:
the present embodiment provides a questionnaire information processing method for education informatization level assessment, as shown in fig. 2, comprising the following steps:
s21, collecting questionnaire information, and converting the original questionnaire information into structured standard data;
s22, creating an education informationization evaluation process object and constructing a mapping relation linked list among the education informationization evaluation process objects, wherein the evaluation process object is a data object containing attribute information and comprises a questionnaire, a calculation model and an index system;
and S23, inputting the structured standard data into a related calculation model according to the mapping relation linked list, and acquiring education informatization evaluation information.
Step S24 may also be included after step S23: and matching the evaluation information push content according to the user type, and sending the matched evaluation information push content to the user.
In the above embodiment, the steps S21-24 can refer to the steps S11 to 14 in embodiment 1, which are not repeated, and only the differences will be described.
The evaluation process object in step S22 may include two multidimensional analysis process objects in addition to the questionnaire process object, the calculation model process object, and the index system process object: school objects, zone objects. And establishing five types of evaluation process objects of questionnaires, calculation models, index systems, areas and schools and associated information among the evaluation process objects. The method comprises the steps that a questionnaire, a calculation model and an index system are used for evaluating process objects to obtain education informatization level evaluation information. The three types of process objects of the questionnaire, the school and the area are used for multi-dimensional correlation analysis and visualization of education informatization levels, for example, the informatization levels of different schools or the informatization levels of different areas can be transversely compared and analyzed, and correlation analysis and visualization of different levels among schools and areas can be carried out.
As shown in fig. 3, in an alternative implementation, the step S21 includes the following steps:
s2101: and establishing a semantic conversion model of the questionnaire answers. And establishing a semantic conversion model for acquiring questionnaire answer data, wherein the semantic conversion model is used for converting the answer information of the semi-structured/unstructured electronic/paper questionnaire into structured data. The semantic conversion content of the answer information of the questionnaire may include a choice question and a blank question. Wherein, the option status of the selected question is marked as 0 or 1, 0 represents that the selected question is not selected, 1 represents that the selected question is selected, and the option marked as 1 is the answer input by the questionnaire filling person; and selecting the blank filling content identifier of the blank filling question as CT, and using the CT as the blank filling content identifier.
S2102: and establishing a semantic conversion model of the questionnaire options. And establishing a conversion model of the questionnaire options according to the semantic conversion model of the questionnaire answers in the step S2101. The single-choice question is identified as "S", the multiple-choice question is identified as "M", the non-question is identified as "R", the quantity question is identified as "D", and the blank-filling question is identified as "T". The data rule of various question type option information is defined, wherein the length of the blank filling question data is 1, the length of the option of the non-question is 1/2 (namely 1 in 2), the length of the option of the single choice question and the quantity table question is 1/N (namely 1 in N), and the length of the option of the multiple choice question is N/N (namely N in N). The semantic conversion method of the questionnaire options is shown in table 1:
table 1: questionnaire options semantic conversion examples
| Question type | Question type mark | Option data rules | Example of an option Structure | |
| Problems of | S | 1/N | 0-1-0-0 | |
| Multiple choice question | M | n/N | 0-1-1-0-CT, supplemental content " | |
| Is a question of | |
1/2 | 0||1 | |
| | D | 1/N | 0-1-0-0 | |
| Filling in the | T | 1 | "Contents" |
S2103: collecting questionnaire information, converting the original questionnaire information into structured standard data, establishing a mapping relation among questionnaire numbers, question numbers and question option numbers, and establishing a mapping relation among the questionnaire numbers, the question numbers and the question option numbers and question answers. And establishing a model according to the semantic conversion model of the questionnaire answers and the semantic conversion of the questionnaire options, and converting the acquired data into formatted data. Based on the conversion model of the questionnaire options established in step S2102, it is determined that when the option identifier is 1 or the blank content is not empty, the questionnaire number, the question number, the questionnaire answer information, and the question option number are associated, and a schematic diagram of the mapping relationship of the questionnaire answer information is shown in fig. 7. The questionnaire number, the question number and the question option number, and the mapping relation between the numbers and the question answers can be recombined and put in storage in a JSON format.
By adopting the data acquisition and formatting processing mode, the questionnaire data entry is more accurate, and the problems that data errors and data loss are easily caused by a mode of manually entering and summarizing the questionnaire into third-party software in the traditional evaluation method are solved.
As shown in fig. 4, in an alternative implementation, the step S22 includes the following steps:
s2201: and creating an educational informationized level evaluation process object, wherein the evaluation process object comprises a questionnaire, a calculation model, an index system, an area and a school.
S2202: an educational informationized level evaluation process object attribute is created. The questionnaire process object attributes may include questionnaire name, question, option, answer, evaluation object, filling time; the index system process object attributes can comprise an index system name, an index level, an index weight, a parent index name and a primary index; the calculation model process object attributes can comprise a problem score calculation model, a primary index original score calculation model, a non-dimensionalization calculation model, a weight calculation model and a multi-dimensional comprehensive evaluation calculation model. The school object key attributes can comprise school names, profiles, belonging areas, coordinates, campus models and digital data; the zone object key attributes may include zone name, spatial extent, school distribution information.
The definitions of data input, method call and data output of the education informatization level evaluation calculation model are shown in table 2:
table 2: calculation model
S2203: and establishing a mapping relation linked list among the objects of the education informatization level evaluation process. The correlation information of the primary indexes, the questionnaire question types and the question score calculation models and the weight calculation models and the primary index weights in the questionnaire question number and index system can be established for supporting index evaluation calculation. Association information between the evaluation object and the multidimensional analysis process object can also be established. The association information between the questionnaire evaluation objects and the schools and between the areas and the schools can be established for supporting the visual analysis and the association query of the evaluation results, and the association information and the attribute expansion among the evaluation process objects are shown in fig. 8.
As shown in fig. 5, in an alternative implementation, the step S23 includes the following steps:
s2301: and inputting the structured standard data to an associated problem score calculation model according to the mapping relation linked list, calculating the problem score of the questionnaire, inputting the obtained problem score of the questionnaire to an associated primary index original score calculation model, and acquiring primary index original score information.
Firstly, obtaining a problem corresponding to a primary index according to the associated information between the primary index and the problem number; then, calculating the score of each question corresponding to the primary index according to the question score calculation model corresponding to each question type; then, calculating a model according to the problem score and the primary index original score, and calculating the primary index original score; and finally, traversing all the primary indexes to obtain the original scoring matrix IS of all the primary indexes.
For example: calculating a primary evaluation index score with the name of '111', calling a problem score calculation Model Q _ Model defined in the step (22), and inputting a problem category, wherein the method comprises the following steps: the method comprises the following steps of selecting a single question (S), selecting multiple questions (M), measuring a question (R), judging a question (D) and filling a blank question (T), calling different calculation formulas according to the question types, and outputting a question score QS. And calling a primary index original score calculation Model PREV _ Model calculation Model to perform traversal summation on the problem score QS and averaging to obtain a primary index '111' original score.
S2302: and inputting the primary index original score information into the non-dimensionalization calculation model to obtain primary index score information. And constructing a data matrix of the evaluation indexes and the original scores of all the questionnaire primary indexes. And traversing the evaluation indexes, and importing the data matrix into a dimensionless calculation model to obtain a primary index score matrix covering all questionnaires.
For example, the implementation procedure of the non-dimensionalized calculation Model NEXT _ Model is as follows: traversing an original score matrix IS of the primary indexes for the first time, calculating the maximum value of the original scores of the same primary indexes under different questionnaire numbers, multiplying the maximum value by 100, and assigning the calculation result to M, namely M IS Max (IS) 100; and continuously traversing the original scoring matrix IS of the primary index for the second time, dividing each element in the IS array by M, and storing the calculation result into the primary index scoring matrix NS after non-dimensionalization.
S2303: and inputting the primary index score information into the weight calculation model to obtain primary index weight information. And calculating the weight of the primary index by using an entropy weight algorithm, summing, logarithm-solving and data normalization processing the primary index scoring matrix NS, and calculating to obtain the weight value of the primary index. The weight calculation algorithm is shown in Table 3 (wherein i is a questionnaire number, and j is an index number)
Table 3: primary index weight calculation algorithm
S2304: and acquiring index evaluation information according to the primary index weight information and the primary index score information.
Further, the primary index score information and the primary index weight information can be input into a multi-dimensional evaluation calculation model, and evaluation information of different dimensional analyses can be determined. Multi-dimensional comprehensive evaluation can be performed based on a recursive algorithm. The method comprises the steps of constructing an evaluation index tree structure, constructing a primary evaluation index score matrix by taking provinces, cities and schools as space ranges, calculating by using a recursive algorithm to obtain evaluation index scores of different levels, and combining a multi-dimensional evaluation calculation model to obtain education informationized evaluation information of different space ranges.
For example, when the education informationization evaluation of a certain school is evaluated by the education informationization evaluation questionnaire information processing method of the present invention, the primary index score (NS) and the primary index weight data (W) are introduced into the multidimensional comprehensive evaluation calculation model in units of schools, and the education informationization comprehensive score of the school is calculated. The specific implementation process of the MULTI _ Model calculation Model is as follows: firstly, constructing an evaluation index tree graph for the school, wherein each node information in the tree graph comprises primary index scores NS [ i ] and W [ i ], and i is a variable and represents the serial number of each node; secondly, introducing a recursion algorithm, traversing from a leaf node at the bottom layer to a root node, multiplying NS [ i ] by W [ i ] to calculate each level of evaluation index score, traversing to the root node, returning a calculation result, and ending recursion; and finally, the calculation result is the comprehensive score of the school.
As shown in fig. 6, when the education informationization level personalized push is performed by using the education informationization assessment questionnaire information processing method of the present invention, in an alternative implementation, the above step S24 includes the steps of:
s2401: defining user types and establishing an evaluation result pushing mechanism. The users are divided into education management mechanisms, school users and expert users, the education management mechanisms concern the development condition of the informatization water leveling bodies of the education in the jurisdiction area, the school users concern the self informatization development condition of the school, and the expert users concern the objectivity of the evaluation result. Through authority management, push data templates of different users are established, and through a publish/subscribe message mechanism, message push based on subject and based on content is provided for different user roles.
S2402: and constructing an evaluation content recommendation model. Fig. 9 is a schematic diagram of an evaluation result message push model. Pushing all school information with comprehensive scores and 5% of all school information before each evaluation index score in the region range of school users; pushing characteristic dimensions, spatial distribution, development trend and evaluation suggestions of the informatization construction of schools in the range of the jurisdiction of education management institutions; and pushing difference ranking information of subjective and objective evaluation results for expert users.
S2403: and matching the evaluation information push content according to the user type by using the evaluation content recommendation model, and sending the matched evaluation information push content to the user.
It should be understood that although the steps in the flowcharts of fig. 1 to 6 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise.
Example 3:
the present embodiment provides a questionnaire information processing apparatus, the apparatus including:
the data acquisition processing module is used for acquiring the questionnaire and converting the original data of the questionnaire into structured standard data;
the system comprises a mapping relation linked list construction module, a calculation module and a calculation module, wherein the mapping relation linked list construction module is used for creating evaluation process objects and constructing a mapping relation linked list among the evaluation process objects, the evaluation process objects are data objects containing attribute information, and the evaluation process objects comprise questionnaires, calculation models and index systems;
and the execution module is used for inputting the structured standard data into the associated calculation model according to the mapping relation linked list to acquire the evaluation information.
For specific limitations of the questionnaire information processing device and the module, reference may be made to the above limitations of the questionnaire information processing method, and details thereof are not repeated here. The respective modules of the above questionnaire information processing apparatus can be entirely or partially realized by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or be independent from a processor of the computer device, and can also be stored in a memory of the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
The present application is not limited to the above embodiments, and any other products in various forms can be obtained by anyone in the light of the present application, but any changes in form or structure, which have the same or similar technical solutions as the present application, fall within the protection scope of the present application.
Claims (8)
1. A questionnaire information processing method characterized by comprising:
collecting questionnaire information, and converting the original questionnaire information into structured standard data with predefined semantic tags;
establishing an evaluation process object and constructing a mapping relation linked list among the evaluation process objects, wherein the evaluation process object is a data object containing different types of evaluation attribute information, and the evaluation process object comprises a questionnaire, a calculation model and an index system;
inputting the structured standard data into an associated calculation model according to the mapping relation linked list to obtain evaluation information;
the acquiring of the questionnaire information and the converting of the original questionnaire information into structured standard data with predefined semantic tags specifically comprises:
establishing a semantic conversion model of the questionnaire answers;
establishing a semantic conversion model of the questionnaire options, giving different question type identifications according to which question type is a single-choice question, a multiple-choice question, a non-question, a quantity table question and a blank filling question, and defining different option structures;
collecting data and converting the data into structured standard data with predefined semantic labels, establishing a mapping relation among a questionnaire number, a question number and a question option number, and establishing a mapping relation among the questionnaire number, the question option number and a question answer;
the attributes of the questionnaire object comprise questionnaire name, question, option, answer, evaluation object and filling time; the index system process object attributes comprise index system names, index levels, index weights, parent index names and primary indexes;
the calculation model comprises a problem score calculation model, a primary index original score calculation model, a dimensionless calculation model and a weight calculation model, and the method for inputting the structured standard data into the associated calculation model according to the mapping relation linked list to obtain the evaluation information specifically comprises the following steps:
inputting questionnaire data in a standard format into an associated question score calculation model according to the mapping relation linked list, and calculating the question score of the questionnaire;
inputting the obtained questionnaire question score to an associated primary index original score calculation model according to the mapping relation linked list to obtain primary index original score information;
inputting the original score information of the primary index into the dimensionless calculation model to obtain the score information of the primary index;
inputting the primary index score information into the weight calculation model to obtain primary index weight information;
and acquiring index evaluation information according to the primary index weight information and the primary index score information.
2. The questionnaire information processing method of claim 1, wherein the evaluation process object further comprises one or more multidimensional analysis objects, and a multidimensional analysis object is a data object for implementing multidimensional correlation analysis.
3. The questionnaire information processing method of claim 2, wherein the multidimensional analysis object comprises an area object and a school object, and the creating an evaluation process object and constructing a mapping relationship linked list between the evaluation process objects specifically comprises:
creating an evaluation process object, wherein the evaluation process object comprises a questionnaire, a calculation model, an index system, a region object and a school object;
creating an evaluation process object attribute;
and constructing a mapping relation linked list among the evaluation process objects.
4. The questionnaire information processing method of claim 1, wherein when the evaluation process object includes a multidimensional analysis object, the calculation model further includes a multidimensional evaluation calculation model, and the acquiring of the index evaluation information from the primary index weight information and the primary index score information specifically includes:
and inputting the primary index score information and the primary index weight information into the multi-dimensional evaluation calculation model according to the mapping relation linked list to obtain multi-dimensional index evaluation information.
5. The questionnaire information processing method of any one of claims 1, 2, or 3, wherein after the step of obtaining evaluation information by inputting the structured standard data to an associated computation model according to the mapping relation linked list, the method further comprises:
and matching the evaluation information push content according to the user type, and sending the matched evaluation information push content to the user.
6. A questionnaire information processing apparatus characterized by comprising:
the data acquisition processing module is used for acquiring questionnaire information and converting the original questionnaire information into structured standard data with predefined semantic tags;
the system comprises a mapping relation linked list construction module, a calculation module and a calculation module, wherein the mapping relation linked list construction module is used for creating evaluation process objects and constructing a mapping relation linked list among the evaluation process objects, the evaluation process objects are data objects containing attribute information, and the evaluation process objects comprise questionnaires, calculation models and index systems;
the execution module is used for inputting the structured standard data into an associated calculation model according to the mapping relation linked list to acquire evaluation information;
the acquiring of the questionnaire information and the converting of the original questionnaire information into structured standard data with predefined semantic tags specifically comprises:
establishing a semantic conversion model of the questionnaire answers;
establishing a semantic conversion model of the questionnaire options, giving different question type identifications according to which question type is a single-choice question, a multiple-choice question, a non-question, a quantity table question and a blank filling question, and defining different option structures;
collecting data and converting the data into structured standard data with predefined semantic tags, establishing mapping relations among questionnaire numbers, question numbers and question option numbers, and establishing mapping relations among the questionnaire numbers, the question option numbers and question answers;
the attributes of the questionnaire object comprise questionnaire name, question, option, answer, evaluation object and filling time; the index system process object attributes comprise index system names, index levels, index weights, parent index names and primary indexes;
the calculation model comprises a problem score calculation model, a primary index original score calculation model, a dimensionless calculation model and a weight calculation model, the structured standard data are input into the associated calculation model according to the mapping relation linked list to obtain evaluation information, and the method specifically comprises the following steps:
inputting questionnaire data in a standard format into an associated question score calculation model according to the mapping relation linked list, and calculating the question score of the questionnaire;
inputting the obtained questionnaire question score to an associated primary index original score calculation model according to the mapping relation linked list to obtain primary index original score information;
inputting the original score information of the primary index into the dimensionless calculation model to obtain the score information of the primary index;
inputting the primary index score information into the weight calculation model to obtain primary index weight information;
and acquiring index evaluation information according to the primary index weight information and the primary index score information.
7. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program performs the steps of the method according to any of claims 1 to 5.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
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| CN112905715A (en) * | 2021-02-08 | 2021-06-04 | 长沙冉星信息科技有限公司 | Multi-dimensional evaluation method based on questionnaire and method thereof |
| CN112925901B (en) * | 2021-03-23 | 2022-07-19 | 华中师范大学 | Evaluation resource recommendation method for assisting online questionnaire evaluation and application thereof |
| CN113159629A (en) * | 2021-05-13 | 2021-07-23 | 平安国际智慧城市科技股份有限公司 | Questionnaire statistical method, device, equipment and storage medium |
| CN115953261A (en) * | 2023-03-14 | 2023-04-11 | 中化现代农业有限公司 | Questionnaire analytic system based on configuration |
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