CN110147953B - Automatic questionnaire generation method - Google Patents
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Abstract
The invention discloses an automatic questionnaire generating method, which belongs to the technical field of Internet questionnaires and comprises a question bank generating step, a questionnaire type forming step, a questionnaire question number determining step and a questionnaire generating step, wherein the questionnaire automatic generating technology is mainly used for assisting the development of an investigation project aiming at the offline investigation project, and the method mainly aims to provide an efficient tool for questionnaire designers and questionnaire recovery work and reserve certain autonomy for users.
Description
Technical Field
The invention relates to the technical field of Internet questionnaires, in particular to an automatic questionnaire generation technology.
Background
A questionnaire typically consists of a series of questions, survey items, alternative answers, or written descriptions. The primary goal is to collect project-related statistics from respondents. The questionnaire is used as a tool for collecting research data, can acquire a large amount of statistical data, and can carry out deep analysis on the information, thereby verifying research hypothesis and scientifically explaining and explaining the researched problems. In practical research, in order to collect research data with high efficiency and high reliability through a questionnaire, questionnaire design is one of key points for ensuring that a research result is effective. When designing a questionnaire, a designer often needs to consider the problems of determining the structure of the questionnaire, compiling and sequencing test questions, selecting answer options and a scale, and describing the relationship between test questions and survey objects, and the like, and meanwhile, the questionnaire cannot be quickly adjusted according to currently collected information. Therefore, effective automatic questionnaire generation and automatic survey data acquisition can bring great convenience, reduce the workload of related personnel and reduce the possibility of manual errors.
Since questionnaire items usually involve many research aspects, a systematic index system is required to guide questionnaire work. The number of indexes related to mature questionnaire survey items is huge, and each index needs to have certain data support. Therefore, the questionnaire should cover all indexes, and simultaneously, different importance degrees of different indexes need to be reflected.
The population of individuals under investigation had limited patience when asked. When the questionnaire questions are too many, the probability that the examinee gives up the survey is greatly increased, so that resources are wasted, and the obtained effective data are reduced. How to design questionnaires according to the patience degree of different people has become one of the problems to be solved urgently in the prior art.
In order to solve the contradiction between the demand of a large amount of data and the limited tolerance degree and budget of a population to be investigated, some automatic questionnaire generation technologies are provided.
For example, in the prior art, as disclosed in chinese patent application publication No. CN107194743A, publication date of 2017, 9 and 22, entitled "a method and apparatus for generating a network questionnaire", a method and apparatus for generating a network questionnaire are disclosed, which are used to collect more data in as few problems as possible, and improve data recovery efficiency and network resource utilization rate of the questionnaire. The network questionnaire survey method comprises the following steps: receiving a response message submitted by user equipment and accepting the network questionnaire invitation; aiming at optional problems contained in a problem library, determining the weight corresponding to the optional problems according to preset evaluation parameters; selecting a preset number of selectable questions according to the sequence of the weights from large to small; generating a network questionnaire according to the selected optional questions and the optional questions contained in the question bank; and returning the generated network questionnaire to the user equipment.
However, the technical scheme only aims at the on-line questionnaire, can not realize the automatic generation of the off-line questionnaire, can not solve the problems in the aspects of fault tolerance rate, completion rate, efficiency and the like in the existing questionnaire survey, and is limited by survey audiences to on-line users and insufficient in breadth.
Disclosure of Invention
The invention aims to automatically generate a questionnaire automatic generation technology which is adaptive to requirements by using a questionnaire generation algorithm under a limited budget, dynamically adjusts a questionnaire structure according to the patience degree of a person group to be investigated and collects survey data as much as possible.
The purpose of the invention is realized by the following technical scheme:
an automatic questionnaire generation method is characterized in that: the method comprises the steps of question bank generation, volume type construction, questionnaire question number determination and questionnaire generation;
in the step of generating the question bank, questionnaire survey work usually needs a systematic index system as guidance, the sum of indexes at the bottommost layer in the index system is the total number of the indexes, each bottom-layer index is associated with one or more test questions, and the test questions jointly form the questionnaire question bank;
the volume type constructing step, namely determining the total number S of questionnaires according to the budget of a certain questionnaire, wherein the total number S of questionnaires is positively correlated with the budget of the questionnaire; setting the quantity L of questionnaire types according to questionnaire requirements;
the step of determining the number of the questionnaires, namely determining the number L of the questionnaire types and setting the total number M of the questionnaires, wherein the total number of the questionnaires is at least not less than the total number of the indexes and at most equal to the total number of the questionnaires in the whole question bank; calculating the number X = M/L of the test questions of each questionnaire according to the total number M of the test questions of the questionnaire and the number L of the types of the questionnaire; the product of the number of the test questions of each questionnaire and the type number of the questionnaires is the total number of the test questions;
and in the questionnaire generating step, according to the questionnaire type and the questionnaire number m of each questionnaire determined in the questionnaire type forming step and the questionnaire question number determining step, a questionnaire generating algorithm is called to generate the questionnaire, the questionnaire generating algorithm processes numbered questions in the question bank to obtain a question numbering sequence, and the questions are extracted from the question bank according to the question numbering sequence to form the questionnaire.
In the step of forming the quantity of the questionnaires, the total quantity S of the questionnaires and the quantity L of the types of the questionnaires; after the total number S of the questionnaires is determined, the type number L of the questionnaires is specified according to the requirement, and the number of the questionnaires in the same type is recorded as C i The total number S of questionnaires is the sum of the number of questionnaires for all questionnaire types, i.e.
Where i ∈ N + (ii) a The quantity of questionnaires C in the same type is increased when the quantity of questionnaire types L is increased i Reduction; the above formula can determine the relationship between the number of types of questionnaires and the number of questionnaires under each type.
In the step of determining the number of the questionnaires, setting the total number M of the questionnaires, the total number Z of the indexes, the total number T of the questions in the whole question bank and the number X of the questions in each questionnaire; and is
Wherein X ∈ N + ，N + Is an integer, from which the number of questions X per questionnaire can be determined.
In the questionnaire generating step, the questionnaire generating algorithm includes the following steps:
step 1, numbering the test questions in the question bank according to the relevance between the test questions and the bottom layer indexes;
step 2, generating a test question numbering matrix, taking a test question numbering set associated with each index as a column in the test question numbering matrix, and if the number of rows of the matrix is not equal, filling the missing part of the column with less quantity with the test question numbering of the column to obtain a test question numbering matrix with the total number of the indexes and the equal rows;
step 3, firstly, randomly arranging the serial numbers of each row in the row to obtain a new test question serial number matrix, and then sequentially putting the serial numbers of each row into a new set to obtain a test question serial number sequence for generating a questionnaire;
step 4, generating questionnaires according to the test question numbering sequence, extracting test questions according to the numbering sequence in the step 3, namely taking X test questions as a new questionnaire, circulating until the total number M of the set test questions is obtained, and if the number of the last test question is not less than X, selecting the numbers from the sequence again in sequence for completion, so that the generated questionnaires can cover all indexes; when each questionnaire is generated, the number of each questionnaire is also required to be recorded, the test question number of each test paper is also required to be recorded, and meanwhile, a timestamp is added, so that subsequent questionnaire recovery and survey result input are facilitated.
According to the using state, the process of numbering the test questions in the question bank according to the relevance with the bottom layer indexes can be started in the question bank generating step, the test questions are numbered for the bottom layer indexes firstly, then the test questions relevant to each bottom layer index are numbered, and the test questions are numbered in the ways of prefix and suffix and the like.
In the step 1, indexes are numbered and marked as Z j And j ∈ N + (ii) a Each index Z j All have corresponding question banks, and the question bank corresponding to the index is the test question number, such as index Z 1 The associated test question number set is { Z (1，1) ,Z (1,2) ,Z (1,3) ,...,Z (1，n) }。
And the questionnaire recycling step is also included, after the questionnaire is recycled, the questionnaire number and the questionnaire result are automatically obtained by utilizing the scanning technology, the information is sent to the system, and the system automatically scores the questionnaire and brings the questionnaire into statistics.
The system scores the questionnaires recovered in the questionnaire recovery step, collects survey data, and takes the questionnaires with too few answers as invalid data; if the target amount of data is not collected, the structure of the questionnaire is adjusted according to the data condition, the number of questionnaire questions is reduced, and the data is supplemented. Preferably, if the number of the answers of the subject in one questionnaire test question is less than 70% of the number of the test question, the result of the questionnaire is considered invalid, and the system automatically records the number of the invalid questionnaire and the number of the answers; after the statistics is completed, if the data volume of a certain type of questionnaire is insufficient, adjusting the number X of the questionnaire questions of each questionnaire according to the condition of invalid questionnaires to generate a new supplementary questionnaire. Finally, the new questionnaire results recovered are used as supplementary data and are recorded into the system in the same way.
Compared with the prior art, the invention has the following advantages:
according to the method for automatically generating the questionnaire, the test question numbering sequence is generated by a mathematical method, and the questionnaire is automatically generated according to the sequence, so that the types of the questionnaire are enriched, and great convenience is provided for questionnaire design; in the questionnaire generating process, a random test question numbering sequence is generated, and the sequence covers indexes of the questionnaire and all question banks at the same time. And the questionnaire generated by the test question sequence avoids the repeated appearance of the same index in the questionnaire, solves the problem that the index and the question bank cannot be considered in the questionnaire design process, and ensures that the generated questionnaire is more scientific and efficient.
The method for automatically generating the questionnaire provided by the invention can be used for supplementing and collecting the data with unqualified quantity, namely deducing the patience degree of the examinee according to the obtained data, and supplementing the data after adjusting the quantity of the test questions of each questionnaire, so that the obtained data is sufficient in quantity and high in effectiveness.
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The foregoing and following detailed description of the invention will be apparent when read in conjunction with the following drawings, in which:
FIG. 1 is a logic diagram of a preferred embodiment of the method for automatically generating questionnaires of the present invention;
FIG. 2 is a logic diagram of a preferred embodiment of the questionnaire generating algorithm of the present invention.
Detailed Description
The technical solutions for achieving the objects of the present invention are further illustrated by the following specific examples, and it should be noted that the technical solutions claimed in the present invention include, but are not limited to, the following examples.
Example 1
As a most basic embodiment of the present invention, this embodiment discloses an automatic questionnaire generating method, as shown in fig. 1, including a question bank generating step, a volume type constructing step, a questionnaire question number determining step, and a questionnaire generating step;
in the step of generating the question bank, questionnaire survey work usually needs a systematic index system as guidance, the sum of indexes at the bottommost layer in the index system is the total number of the indexes, each bottom-layer index is associated with one or more test questions, and the test questions jointly form the questionnaire question bank;
the volume type constructing step, namely determining the total number S of questionnaires according to the budget of a certain questionnaire, wherein the total number S of questionnaires is positively correlated with the budget of the questionnaire; setting the quantity L of questionnaire types according to questionnaire requirements;
the step of determining the number of the questionnaires, namely determining the number L of the questionnaire types and setting the total number M of the questionnaires, wherein the total number of the questionnaires is at least not less than the total number of the indexes and at most equal to the total number of the questionnaires in the whole question bank; calculating the number X = M/L of the test questions of each questionnaire according to the total number M of the test questions of the questionnaire and the number L of the types of the questionnaire; the product of the number of the test questions of each questionnaire and the type number of the questionnaires is the total number of the test questions;
and in the questionnaire generating step, the questionnaire generating algorithm is called to generate the questionnaire according to the questionnaire type and the questionnaire number m of each questionnaire determined in the questionnaire type forming step and the questionnaire number determining step, the questionnaire generating algorithm processes numbered questions in the question bank to obtain a question numbering sequence, and the questions are extracted from the question bank according to the question numbering sequence to form the questionnaire.
According to the method for automatically generating the questionnaire, the test question number sequence is generated by a mathematical method, and the questionnaire is automatically generated according to the sequence, so that the types of the questionnaire are enriched, and great convenience is provided for questionnaire design; in the questionnaire generating process, a random test question numbering sequence is generated, and the sequence covers indexes of the questionnaire and all question banks at the same time. And the questionnaire generated by the test question sequence avoids the repeated appearance of the same index in the questionnaire, solves the problem that the index and the question bank cannot be considered in the questionnaire design process, and ensures that the generated questionnaire is more scientific and efficient.
Example 2
As a preferred embodiment of the present invention, on the basis of the technical solution of example 1, this example further discloses that in the questionnaire quantity composing step, the total number S of questionnaires, the number L of questionnaire types; after the total number S of the questionnaires is determined, the type number L of the questionnaires is specified according to the requirement, and the number of the questionnaires in the same type is recorded as C i The total number S of questionnaires is the sum of the number of questionnaires for all questionnaire types, i.e.
Wherein i ∈ N + (ii) a The quantity of questionnaires C in the same type is increased when the quantity of questionnaire types L is increased i Reduction; the relation between the number of questionnaire types and the number of questionnaires under each type can be determined by the formula.
In the step of determining the number of the questionnaires, the total number M of the questionnaires, the total number Z of the indexes,the total number of the test questions T of the whole question bank and the number of the test questions X of each questionnaire; and is
Wherein X ∈ N + ，N + Is an integer, from which the number of questions X per questionnaire can be determined.
The system scores the questionnaires recovered in the questionnaire recovery step, collects survey data, and takes the questionnaires with too few answers as invalid data; if the target amount of data is not collected, the structure of the questionnaire is adjusted according to the data condition, the number of questionnaire questions is reduced, and data supplement is performed. Preferably, if the number of the answers of the subjects in one questionnaire test question is less than 70% of the number of the test questions, the system automatically records the number of the invalid questionnaire and the number of the answers if the result of the questionnaire is invalid; after the statistics is completed, if the data volume of a certain type of questionnaire is insufficient, adjusting the number X of the questionnaire questions of each questionnaire according to the condition of invalid questionnaires to generate a new supplementary questionnaire. Finally, the new questionnaire result recovered is used as supplementary data and is recorded into the system by the same method; and (4) supplementing and collecting the data with unqualified quantity, namely deducing the patience degree of the examinee according to the obtained data, and supplementing the data after adjusting the quantity of the test questions of each questionnaire, so that the obtained data is sufficient in quantity and high in effectiveness.
Further, as shown in fig. 2, in the questionnaire generating step, the questionnaire generating algorithm includes the following steps:
step 1, numbering test questions in a question bank according to the relevance of the test questions and a bottom-layer index;
step 2, generating a test question numbering matrix, taking a test question numbering set associated with each index as a column in the test question numbering matrix, and if the number of rows of the matrix is not equal, filling the missing part of the column with less quantity with the test question numbering of the column to obtain a test question numbering matrix with the total number of the indexes and the equal rows;
step 3, firstly, randomly arranging the serial numbers of each row in the row to obtain a new test question serial number matrix, and then sequentially putting the serial numbers of each row into a new set to obtain a test question serial number sequence for generating a questionnaire;
step 4, generating questionnaires according to the test question numbering sequence, extracting test questions according to the numbering sequence in the step 3, namely taking X test questions as a new questionnaire, circulating until the total number M of the set test questions is obtained, and if the number of the last test question is not less than X, selecting the numbers from the sequence again in sequence for completion, so that the generated questionnaires can cover all indexes; and when each questionnaire is generated, the number of each questionnaire is required to be recorded, and the test question number of each test paper is added with a timestamp, so that subsequent questionnaire recovery and survey result entry are facilitated.
According to the using state, the process of numbering the test questions in the question bank according to the relevance with the bottom layer indexes can be started in the question bank generating step, the test questions are numbered for the bottom layer indexes firstly, then the test questions relevant to each bottom layer index are numbered, and the test questions are numbered in the ways of prefix and suffix and the like.
In the step 1, indexes are numbered and marked as Z j And j ∈ N + (ii) a Each index Z j All have corresponding question banks, and the question bank corresponding to the index is the test question number, such as index Z 1 The associated test question number set is { Z (1，1) ,Z (1,2) ,Z (1,3) ,...,Z (1，n) }。
And the questionnaire recycling step is also included, after the questionnaire is recycled, the questionnaire number and the questionnaire result are automatically obtained by utilizing the scanning technology, the information is sent to the system, and the system automatically scores the questionnaire and brings the questionnaire into statistics.
Example 3
As a preferred embodiment of the present invention, this embodiment discloses an automatic questionnaire generating method, which includes the following steps:
step 1, calculating the total number of questionnaires according to the budget of questionnaire survey, and then determining the number of questionnaire types according to the total number of questionnaires; the questionnaire questions of the same type are the same, and the questionnaire questions of different types are different, so that the composition of the questionnaire quantity is determined.
The budget in the questionnaire is limited, and the number of questionnaires needs to be determined according to the budget. Let the relationship between the questionnaire budget and the total number of questionnaires (denoted by S) be a positive correlation. When S is determined, the number of questionnaire types (denoted by L) can be specified according to the need. Wherein, the questionnaire questions of different types are different, and the questionnaire questions of the same type are the same, and the quantity of the questionnaire under the same type is marked as C i . The total number of questionnaires being the sum of the number of questionnaires for all types, i.e.
The number of types of questionnaires L is increased, and the number of questionnaires C in the same type i It will be reduced. The above formula can determine the relationship between the number of types of questionnaires and the number of questionnaires under each type
Step 2, the total amount of the questionnaire test questions at least needs to cover the whole index system, and under the premise, the user can also specify the total amount of the test questions; therefore, after determining the number of types of questionnaires, the number of questions per questionnaire needs to be calculated according to the total number of questionnaire questions.
After determining the number of types of questions, the user can specify the total number of test questions (marked as M), the total number of test questions at least covers the whole index system (the total number of indexes is marked as Z), and at most covers the whole question bank (the total number of test questions in the question bank is marked as T). The number of questions per questionnaire (denoted as X) is then calculated based on the total number of questions M specified by the user. The product of the number N of the questions in each questionnaire and the number L of the types of the questionnaires is the total number M of the questions. And the number X of the test questions of each questionnaire needs to satisfy the formula
From this, the number of test questions X per questionnaire can be determined.
Step 3, generating the questionnaire according to the determined type number of the questionnaire and the number of the test questions of each questionnaire; calling a questionnaire generation algorithm, wherein the algorithm firstly numbers all indexes and numbers test questions in an index-associated question library; processing the numbered test questions to finally obtain a feasible test question numbering sequence; and finally, sequentially extracting the test questions from the test question numbering sequence to form different types of questionnaires. The questionnaire numbers are recorded so that the system automatically processes the survey results.
The questionnaire generation algorithm comprises the following specific steps:
1. the indexes and test questions are numbered. The algorithm numbers all indices and labels as Z j (j∈N + ). For each index Z j There is a corresponding question bank. Numbering the test questions according to an index question bank, e.g. index Z j The associated test question number set is { Z } 11 ，Z 12 ，Z 13 ，…，Z 1n }。
2. And generating a test question number matrix. And taking the test question number set associated with each index as a column in the test question number matrix, if the number of rows of the matrix is not equal, filling the missing part of the column with less number with the test question number of the column, and finally obtaining the test question number matrix with the total number of the indexes and the equal rows.
3. And obtaining a new test question numbering sequence. The algorithm firstly carries out random arrangement on the serial numbers of each row in the row to obtain a new test question serial number matrix. The numbers of each row are then sequentially placed into a new set. A sequence of test question numbers is obtained which can be used to generate a questionnaire.
4. And generating a questionnaire according to the test question numbering sequence. The algorithm extracts the test questions according to the sequence of the number sequences, namely every N test questions are used as a new questionnaire, and the process is circulated until the total number M of the test questions specified by the user is obtained. And if the number of the last questionnaire test questions is less than X, sequentially selecting numbers from the sequence again for filling. The questionnaire thus generated can cover all the indicators. Each questionnaire is generated and simultaneously the number of each questionnaire is required to be numbered, the test question number of each test paper is required to be recorded, and a time stamp is added. And subsequent questionnaire recovery and survey result input are facilitated.
Further, in order to evaluate the quality of the questionnaire and continuously perfect the question bank and the algorithm, the method also comprises the following steps:
and 4, recycling the questionnaire, and automatically acquiring the number of the questionnaire in a scanning mode. Automatically calling out the relevant information of the questionnaire from the database according to the number of the questionnaire, and then recording the answers of the testees according to the test question numbers. The system will automatically score and record data based on the subject answers.
Step 5, the condition of invalid questionnaire can reflect the patience degree of the tested population to a certain extent. If the number of the answers of the testee in a certain questionnaire is less than 70% of the number of the test questions, the result of the questionnaire is considered invalid, and the system automatically records the number of the invalid questionnaire and the number of the answers. After the statistics is completed, if the data volume of a certain type of questionnaire is insufficient, adjusting the number X of the questionnaire questions of each questionnaire according to the condition of invalid questionnaires to generate a new supplementary questionnaire. The new questionnaire results that are finally retrieved are entered into the system in the same way as supplementary data.
Claims (5)
1. An automatic questionnaire generation method is characterized in that: the method comprises the steps of question bank generation, volume type construction, questionnaire question number determination and questionnaire generation;
in the step of generating the question bank, questionnaire survey work usually needs a systematic index system as guidance, the sum of indexes at the bottommost layer in the index system is the total number of the indexes, each bottom-layer index is associated with one or more test questions, and the test questions jointly form the questionnaire question bank;
the volume type constructing step, namely determining the total quantity S of the questionnaires according to the budget of a certain questionnaire survey, wherein the total quantity S of the questionnaires is positively correlated with the budget of the questionnaire survey; setting the quantity L of questionnaire types according to questionnaire requirements;
the step of determining the number of the questionnaires, namely determining the number L of the questionnaire types and setting the total number M of the questionnaires, wherein the total number of the questionnaires is at least not less than the total number of the indexes and at most equal to the total number of the questionnaires in the whole question bank; calculating the number X = M/L of the test questions of each questionnaire according to the total number M of the test questions of the questionnaire and the number L of the types of the questionnaire; the product of the number of the test questions of each questionnaire and the type number of the questionnaires is the total number of the test questions;
the questionnaire generating step is to call a questionnaire generating algorithm to generate the questionnaire according to the questionnaire type and the number m of the test questions of each questionnaire determined in the questionnaire type forming step and the questionnaire question number determining step, wherein the questionnaire generating algorithm is to process numbered test questions in the question bank to obtain a test question numbering sequence and extract the test questions from the question bank according to the test question numbering sequence to form the questionnaire;
the questionnaire generation algorithm comprises the following steps:
step 1, numbering test questions in a question bank according to the relevance of the test questions and a bottom-layer index;
step 2, generating a test question number matrix, taking a test question number set associated with each index as a column in the test question number matrix, if the number of rows of the matrix is not equal, filling the part lacking in the less columns with the test question numbers of the column to obtain a test question number matrix with the total number of the indexes and the equal rows;
step 3, firstly, randomly arranging the serial numbers of each row in the row to obtain a new test question serial number matrix, and then sequentially putting the serial numbers of each row into a new set to obtain a test question serial number sequence for generating a questionnaire;
step 4, generating a questionnaire according to the test question numbering sequence, extracting test questions according to the numbering sequence in the step 3, namely taking each X test questions as a new questionnaire, circulating the steps until the set total number M of the test questions is obtained, and if the number of the last questionnaire test questions is less than X, sequentially selecting numbers from the sequence again to complement, so that the generated questionnaire can cover all indexes; and when each questionnaire is generated, the number of each questionnaire is required to be recorded, and the test question number of each test paper is added with a timestamp, so that subsequent questionnaire recovery and survey result entry are facilitated.
2. The method of claim 1, wherein the questionnaire comprises: in the step of forming the quantity of the questionnaires, the total quantity S of the questionnaires and the quantity L of the types of the questionnaires; after the total number S of the questionnaires is determined, the type number L of the questionnaires is specified according to the requirement, and the number of the questionnaires in the same type is recorded as C i The total number of questionnaires S is the sum of the number of questionnaires under all questionnaire types, i.e., wherein
(ii) a The quantity of questionnaires C in the same type is increased when the quantity of questionnaire types L is increased i Reduction; the above formula can determine the relationship between the number of types of questionnaires and the number of questionnaires under each type.
3. The method of claim 1, wherein the questionnaire comprises: in the step of determining the number of the questionnaires, setting the total number M of the questionnaires, the total number Z of the indexes, the total number T of the questions in the whole question bank and the number X of the questions in each questionnaire; and wherein, in the above-mentioned method,
is an integer, from which the number of test questions X per questionnaire can be determined.
4. The method of claim 1, wherein the questionnaire comprises: in the step 1, indexes are numbered and marked as Z j And is and
(ii) a Each index Z j All have corresponding question banks, and the question bank corresponding to the index is the test question number, such as index Z 1 The associated test question number sets are.
5. The method of claim 1, wherein the questionnaire comprises: and the questionnaire recycling step is also included, after the questionnaire is recycled, the questionnaire number and the questionnaire result are automatically obtained by utilizing the scanning technology, the information is sent to the system, and the system automatically scores the questionnaire and brings the questionnaire into statistics.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101017540A (en) * | 2007-01-24 | 2007-08-15 | 华为技术有限公司 | Intelligent questionnaire system, questionnaire development method and device thereof |
| CN101315680A (en) * | 2007-05-31 | 2008-12-03 | 中国科学院自动化研究所 | Group qualitative analysis tool based on automatic investigation questionnaire and implementing method thereof |
| CN105117867A (en) * | 2015-10-09 | 2015-12-02 | 张娟 | Design and implementation of enterprise questionnaire system |
| CN105825270A (en) * | 2016-03-03 | 2016-08-03 | 云南电网有限责任公司教育培训评价中心 | Automatic test paper generation method for test questions in question bank through genetic algorithm |
| CN106803123A (en) * | 2016-12-20 | 2017-06-06 | 广州中软信息技术有限公司 | A kind of automatic volume group method for online exam |
| CN107194743A (en) * | 2017-06-19 | 2017-09-22 | 腾讯科技（深圳）有限公司 | A kind of network surveying questionnaire generation method and device |
| CN108428152A (en) * | 2018-03-12 | 2018-08-21 | 平安科技（深圳）有限公司 | questionnaire generation method, server and computer readable storage medium |
| CN109050103A (en) * | 2018-11-06 | 2018-12-21 | 电子科技大学中山学院 | Questionnaire statistics record board based on big data analysis |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003244920A1 (en) * | 2002-06-13 | 2003-12-31 | L'oreal S.A. | Methods and systems for generating diagnostic algorithms based on questionnaires |
| CN104008453A (en) * | 2014-05-29 | 2014-08-27 | 启秀科技（北京）有限公司 | Vocational ability evaluation simulation system |
| US20170178163A1 (en) * | 2015-12-17 | 2017-06-22 | B3Intelligence Ltd. | Method and system for generating a split questionnaire |
| CN110245213B (en) * | 2019-05-08 | 2023-10-20 | 平安科技（深圳）有限公司 | Questionnaire generation method, device, equipment and storage medium |
-
2019
- 2019-05-16 CN CN201910404782.8A patent/CN110147953B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101017540A (en) * | 2007-01-24 | 2007-08-15 | 华为技术有限公司 | Intelligent questionnaire system, questionnaire development method and device thereof |
| CN101315680A (en) * | 2007-05-31 | 2008-12-03 | 中国科学院自动化研究所 | Group qualitative analysis tool based on automatic investigation questionnaire and implementing method thereof |
| CN105117867A (en) * | 2015-10-09 | 2015-12-02 | 张娟 | Design and implementation of enterprise questionnaire system |
| CN105825270A (en) * | 2016-03-03 | 2016-08-03 | 云南电网有限责任公司教育培训评价中心 | Automatic test paper generation method for test questions in question bank through genetic algorithm |
| CN106803123A (en) * | 2016-12-20 | 2017-06-06 | 广州中软信息技术有限公司 | A kind of automatic volume group method for online exam |
| CN107194743A (en) * | 2017-06-19 | 2017-09-22 | 腾讯科技（深圳）有限公司 | A kind of network surveying questionnaire generation method and device |
| CN108428152A (en) * | 2018-03-12 | 2018-08-21 | 平安科技（深圳）有限公司 | questionnaire generation method, server and computer readable storage medium |
| CN109050103A (en) * | 2018-11-06 | 2018-12-21 | 电子科技大学中山学院 | Questionnaire statistics record board based on big data analysis |
Non-Patent Citations (2)
| Title |
|---|
| 一种高效的随机组卷算法的设计;周文君;《电脑与电信》;20160710(第07期);67-71 * |
| 基于K-means聚类的调查问卷动态赋权统计方法;李晓英;《统计与决策》;20181210;80-83 * |
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