CN115862790A - Questionnaire question weight generation method, device, equipment and storage medium - Google Patents
Questionnaire question weight generation method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to a data analysis technology, and discloses a questionnaire question weight generating method for medical care questionnaire survey, which comprises the following steps: determining each question in the target questionnaire template as a target question, and determining a test questionnaire containing the target question as a target test questionnaire of the target question; obtaining an answer to the target question in each target test questionnaire of the target questions; grading and converting the answers to obtain the grade of the answers; performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight; and carrying out normalization calculation on the initial weight of the target question, and generating the weight of each question in the target questionnaire template according to the calculation result. The invention also relates to a blockchain technique, and the answer scores can be stored in blockchain nodes. The invention also provides a questionnaire question weight generating device, equipment and medium. The invention can improve the accuracy of the weight generation of the questionnaire questions.
Description
Technical Field
The present invention relates to data analysis technologies, and in particular, to a method and an apparatus for generating weight of questionnaire questions, an electronic device, and a storage medium.
Background
In the field of medical care business development, in order to better understand user needs, questionnaires are often required to be issued to users to perform previous user need investigation.
Generally, a questionnaire survey needs to configure the weight of each question in a questionnaire template before issuing a questionnaire, however, the current questionnaire question weight generation method often configures all questions with the same weight, and cannot distinguish the importance degree of different questionnaire questions, so that the accuracy rate of generating the questionnaire question weight is low.
Disclosure of Invention
The invention provides a questionnaire question weight generation method and device, electronic equipment and a storage medium, and mainly aims to improve the accuracy of questionnaire question weight generation.
Acquiring a test questionnaire set and a target questionnaire template, wherein all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template;
taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question;
obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question;
analyzing a target answer of a target question to which the grading rule belongs by using the grading rule to obtain an answer grade of the target question;
performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question;
carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem;
and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain a target questionnaire.
Optionally, the performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question includes:
calculating the average value and the standard deviation of all answer scores of the target question;
and calculating by using the average value and the standard deviation to obtain the initial weight.
Optionally, the performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question includes:
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
judging whether the number of the answer scores is larger than a preset number threshold value or not;
when the number of the answer scores is larger than the preset number threshold, calculating the average value and the standard deviation of all the answer scores of the target question;
calculating by using the average value and the standard deviation to obtain the initial weight;
and when the number of the answer scores is not greater than the preset number threshold, calculating by using the number of the questions in the target questionnaire template and a preset weight threshold to obtain the initial weight.
Optionally, the performing normalization calculation on the initial weight of the target problem to obtain a standard weight of the target problem includes:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of each target problem.
Optionally, the performing normalization calculation on the initial weight of the target problem to obtain a standard weight of the target problem includes:
performing index conversion on the initial weight of the target problem to obtain the index weight of the target problem;
calculating by using the index weights of all the target problems to obtain an index weight sum;
and calculating the ratio of the exponential weight of each target problem to the exponential weight sum to obtain the standard weight of each target problem.
Optionally, the analyzing, by using the scoring rule, a target answer of a target question to which the scoring rule belongs to obtain an answer score of the target question, including:
inquiring the standard answer which is the same as the target answer in the scoring rule to obtain a target standard answer;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
In order to solve the above problem, the present invention also provides a questionnaire question weight generating device, the device including:
the system comprises a scoring conversion module, a scoring conversion module and a scoring conversion module, wherein the scoring conversion module is used for acquiring a test questionnaire set and a target questionnaire template, and all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template; taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question; obtaining a scoring rule of each target question and an answer of the target question in each target test questionnaire corresponding to the target question; analyzing the target answer of the target question to which the grading rule belongs by using the grading rule to obtain the answer grade of the target question;
the dispersion analysis module is used for carrying out score dispersion analysis on all answer scores of the target question to obtain the initial weight of the target question;
the weight configuration module is used for carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem; and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
Optionally, the performing normalization calculation on the initial weight of the target problem to obtain a standard weight of the target problem includes:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of each target problem.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one computer program; and
and a processor executing the computer program stored in the memory to implement the questionnaire question weight generating method described above.
In order to solve the above problem, the present invention also provides a computer-readable storage medium having at least one computer program stored therein, the at least one computer program being executed by a processor in an electronic device to implement the questionnaire question weight generating method described above.
The embodiment of the invention analyzes the target answer of the target question to which the grading rule belongs by utilizing the grading rule to obtain the answer grade of the target question; performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question; carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem; and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire. The importance degrees of different target questions are evaluated based on the discrete degree of the answer scores of the target questions, so that corresponding question weights are calculated, and the question weight configuration is more accurate compared with the problem weight configuration with the same weight for different target questions, so that the questionnaire question weight generation method, the device, the electronic equipment and the readable storage medium provided by the embodiment of the invention reduce the accuracy rate of questionnaire question weight generation.
Drawings
Fig. 1 is a schematic flowchart of a method for generating weight of questionnaire questions according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a questionnaire question weight generating device according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an internal structure of an electronic device for implementing a method for generating weight of questionnaire questions according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the invention provides a questionnaire question weight generating method. The execution subject of the questionnaire question weight generation method includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the questionnaire question weight generating method may be executed by software or hardware installed in the terminal device or the server device, and the software may be a block chain platform. The server includes but is not limited to: the cloud server can be an independent server, or can be a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Referring to a flow diagram of a questionnaire question weight generation method provided in an embodiment of the present invention shown in fig. 1, in the embodiment of the present invention, the questionnaire question weight generation method includes the following steps:
s1, obtaining a test questionnaire set and a target questionnaire template, wherein all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template;
in the embodiment of the present invention, the target questionnaire template is a questionnaire for a questionnaire survey for medical care service (for example, a corresponding care regimen is recommended according to medical conditions of different users) that needs to be subjected to questionnaire question weight generation, the test questionnaire is a recovered questionnaire used for testing questions in the target questionnaire template, the test questionnaire includes one or more questions, and all the questions in the test questionnaire are included in the target questionnaire template.
S2, taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question;
in the embodiment of the present invention, in order to evaluate the weight of each question in the volume template, each question in the target questionnaire template is taken as a target question, and further, in the embodiment of the present invention, a weight analysis of the question is performed based on an answer to the target question, and the answer to the target question can only be found in a test questionnaire containing the target question, so that the test questionnaire containing the target question is set as the target test questionnaire for the target question.
S3, obtaining a grading rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question;
in the embodiment of the present invention, the scoring rule is a mapping rule that different answers in the target question correspond to different scores, and the target answer of the target question is a question answer filled in a target test questionnaire for the target question by a user aiming at the question.
S4, analyzing a target answer of a target question to which the grading rule belongs by using the grading rule to obtain an answer grade of the target question;
in the embodiment of the present invention, the answers to the target questions may be different types of target answers, and in order to better quantify the target answers to the target questions, the scoring rules are used to score and convert the target answers to the target questions, so that different target answers are mapped to corresponding scores to obtain the answer scores of the target questions.
Specifically, in the embodiment of the present invention, the scoring rule includes one or more standard answers and a mapping score associated with each standard answer.
In detail, the S4 in the embodiment of the present invention includes:
inquiring the standard answer which is the same as the target answer in the scoring rule to obtain a target standard answer;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
In another embodiment of the present invention, in order to prevent the answer from not completely matching with the standard answer, which results in a non-scoring condition, the S4 includes:
converting the target answer into a target answer vector;
obtaining a standard answer vector of each type of standard answer in the scoring rule;
calculating the vector similarity of the target answer vector and the standard answer vector;
screening all standard answers in the scoring rule based on the vector similarity to obtain target standard answers;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
In the embodiment of the present invention, the target answer may be converted into an answer vector by using a deep learning model (e.g., a bert model), a one-hot algorithm, and the like, the standard answer vector is obtained by converting the standard answer, and a conversion method is similar to a method of converting the answer into the answer vector, and is not described herein again.
In another embodiment of the present invention, the answer scores may be stored in the blockchain nodes, and the data access efficiency is improved by using the characteristic of high throughput of the blockchain nodes.
S5, performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question;
since the questions in the questionnaire are set for collecting the viewpoint information of different users, if the dispersion degree of all answer scores of the target question is higher, the difference of the viewpoints of different users representing the question is larger, the more diverse and richer the viewpoint information of the users collected by the question is, the more important the question is, and the weight of the question should be correspondingly larger, so in the embodiment of the present invention, the score dispersion analysis is performed based on all answer scores of the target question to obtain the initial weight of the target question.
In the embodiment of the present invention, the step S5 includes:
calculating the average value and the standard deviation of all answer scores of the target question;
and calculating by using the average value and the standard deviation to obtain the initial weight.
Specifically, in the embodiment of the present invention, the initial weight of the target problem is calculated by using the following formula:
wherein, cov j Is the initial weight, δ, of the target problem j j Standard deviation, x, of all answer scores representing the target question j j Represents the average of all answer scores of the target question j, and j represents the rank of the target question.
In another embodiment of the present invention, in order to ensure that the initial weight has referential property, and therefore, when the number of answer scores of the target question needs to reach a certain number threshold, the score dispersion analysis makes sense, the S5 includes:
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
judging whether the number of the answer scores is larger than a preset number threshold value or not;
when the number of the answer scores is larger than the preset number threshold, calculating the average value and the standard deviation of all the answer scores of the target question;
calculating by using the average value and the standard deviation to obtain the initial weight;
and when the number of the answer scores is not greater than the preset number threshold, calculating by using the number of the questions in the target questionnaire template and a preset weight threshold to obtain the initial weight.
Specifically, in the embodiment of the present invention, the weight threshold is a preset total weight of the target questionnaire template, the number of answer scores of the target questions does not reach a number threshold, and an average weight of each question in the target questionnaire template may be calculated by using the number of questions in the target questionnaire template and a preset weight threshold as the initial weight.
Further, in the embodiment of the present invention, the calculating by using the number of questions in the target questionnaire template and a preset weight threshold to obtain the initial weight includes:
and performing division operation by using the weight threshold and the number of the questions in the target questionnaire template to obtain the initial weight.
Optionally, in the embodiment of the present invention, the weight threshold may be 1, for example: if the number of questions in the target questionnaire template is 5 and the weight threshold is 1, the initial weight is 1/5=0.2.
S6, carrying out normalization calculation on the initial weight of the target problem to obtain a standard weight of the target problem;
the S6 in the embodiment of the present invention includes:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of each target problem.
Specifically, in the embodiment of the present invention, the following formula is used to calculate the standard weight W of the target problem j j ：
Wherein, cov j Initial weight of target problem j, cov k For the initial weight of the target question k, j, k represent the sequence number of the target question, and m represents the total number of the target questions.
In another embodiment of the present invention, to amplify the difference of the similar initial weights, the S6 includes:
performing index conversion on the initial weight of the target problem to obtain the index weight of the target problem;
calculating by using all the exponential weights of the target problem to obtain the exponential weight sum of the target problem;
and calculating a ratio by using the exponential weight of the target problem and the exponential weight sum to obtain the problem weight of the target problem.
For example: if the initial weight of the target problem is 0.1, performing exponential conversion on the initial weight to obtain an exponential weight e 0.1 。
And S7, generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
In the embodiment of the invention, the weight of the corresponding target question in the target questionnaire template is generated according to the standard weight of each target question until the weight generation of all the target questions in the target questionnaire template is completed, so that the target questionnaire is obtained.
For example: the standard weight of the target question a is 0.1, and then the generated weight of the target question in the target questionnaire template is also 0.1.
In the embodiment of the invention, the standard weight is used for carrying out weight configuration on each corresponding question in the target questionnaire template, and after the target questionnaire is obtained, the target questionnaire can be sent to the corresponding user for questionnaire survey, so that the physical condition of the user can be more accurately known, and more appropriate recuperation and old age care services can be conveniently matched for the corresponding user in the follow-up process.
As shown in fig. 2, the present invention is a functional block diagram of the questionnaire question weight generation device.
The questionnaire question weight generating apparatus 100 according to the present invention can be installed in an electronic device. According to the implemented functions, the questionnaire question weight generating device may include a score conversion module 101, a discrete analysis module 102, and a weight configuration module 103, which may also be referred to as a unit, and refer to a series of computer program segments that can be executed by a processor of an electronic device and can perform fixed functions, and are stored in a memory of the electronic device.
The scoring conversion module 101 is configured to obtain a test questionnaire set and a target questionnaire template, where all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template; taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question; obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question; analyzing the target answer of the target question to which the grading rule belongs by using the grading rule to obtain the answer grade of the target question;
in the embodiment of the present invention, the target questionnaire template is a questionnaire for a questionnaire survey for medical care service (for example, a corresponding care regimen is recommended according to medical conditions of different users) that needs to be subjected to questionnaire question weight generation, the test questionnaire is a recovered questionnaire used for testing questions in the target questionnaire template, the test questionnaire includes one or more questions, and all the questions in the test questionnaire are included in the target questionnaire template.
In the embodiment of the present invention, in order to evaluate the weight of each question in the volume template, the score conversion module 101 uses each question in the target questionnaire template as a target question, and further, in the embodiment of the present invention, the weight analysis of the question is performed based on the answer to the target question, and the answer to the target question can only be found in the test questionnaire containing the target question, so the score conversion module 101 sets the test questionnaire containing the target question as the target test questionnaire for the target question.
In the embodiment of the present invention, the scoring rule is a mapping rule that different answers in the target question correspond to different scores, and the target answer of the target question is a question answer filled in a target test questionnaire for the target question by a user aiming at the question.
In the embodiment of the present invention, the answers to the target questions may be different types of target answers, and in order to better quantify the target answers to the target questions, the scoring rules are used to score and convert the target answers to the target questions, so that different target answers are mapped to corresponding scores to obtain the answer scores of the target questions.
Specifically, in the embodiment of the present invention, the scoring rule includes one or more standard answers and a mapping score associated with each standard answer.
In detail, in the embodiment of the present invention, the score conversion module 101 calculates the answer score by using the following means, including:
inquiring the standard answer which is the same as the target answer in the scoring rule to obtain a target standard answer;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
In another embodiment of the present invention, in order to prevent the answer from not completely matching with the standard answer, which results in a situation of being unable to score, the score conversion module 101 calculates the score of the answer by using the following means, including:
converting the target answer into a target answer vector;
obtaining a standard answer vector of each type of standard answer in the scoring rule;
calculating the vector similarity of the target answer vector and the standard answer vector;
screening all standard answers in the scoring rule based on the vector similarity to obtain target standard answers;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
In the embodiment of the present invention, the score conversion module 101 may convert the target answer into an answer vector by using a deep learning model (such as a bert model), a one-hot algorithm, and the like, and the standard answer vector is also obtained by converting the standard answer.
In another embodiment of the present invention, the answer scores may be stored in the blockchain nodes, and the data access efficiency is improved by using the characteristic of high throughput of the blockchain nodes.
The discrete analysis module 102 is configured to perform score discrete analysis based on all answer scores of the target question to obtain an initial weight of the target question;
since the questions in the questionnaire are set for collecting the viewpoint information of different users, if the dispersion degree of all answer scores of the target question is higher, the difference of the viewpoints of different users representing the question is larger, the more diverse and richer the viewpoint information of the users collected by the question is, the more important the question is, and the weight of the question should be correspondingly larger, so in the embodiment of the present invention, the score dispersion analysis is performed based on all answer scores of the target question to obtain the initial weight of the target question.
In the embodiment of the present invention, the discrete analysis module 102 calculates the initial weight by using the following means, including:
calculating the average value and the standard deviation of all answer scores of the target question;
and calculating by using the average value and the standard deviation to obtain the initial weight.
Specifically, in the embodiment of the present invention, the discrete analysis module 102 calculates the initial weight of the target problem by using the following formula:
wherein, cov j Is the initial weight, δ, of the target problem j j Standard deviation, x, of all answer scores representing the target question j j Represents the average of all answer scores for the target question j, j representing the rank of the target question.
In another embodiment of the present invention, in order to ensure that the initial weight has referential property, and therefore, when the number of the answer scores of the target question needs to reach a certain number threshold, the score dispersion analysis is meaningful, the dispersion analysis module 102 calculates the initial weight by using the following means, including:
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
judging whether the number of the answer scores is larger than a preset number threshold value or not;
when the number of the answer scores is larger than a preset number threshold value, calculating the average value and the standard deviation of all the answer scores of the target question;
calculating by using the average value and the standard deviation to obtain the initial weight;
and when the number of the answer scores is not more than a preset number threshold, calculating by using the number of the questions in the target questionnaire template and a preset weight threshold to obtain the initial weight.
Specifically, in the embodiment of the present invention, the weight threshold is a total weight preset in the target questionnaire template, the number of answer scores of the target questions does not reach a number threshold, and an average weight of each question in the target questionnaire template may be calculated by using the number of questions in the target questionnaire template and a preset weight threshold as the initial weight.
Further, in the embodiment of the present invention, the calculating, by the discrete analysis module 102, the initial weight by using the number of questions in the target questionnaire template and a preset weight threshold includes:
and performing division operation by using the weight threshold and the number of the questions in the target questionnaire template to obtain the initial weight.
Optionally, in the embodiment of the present invention, the weight threshold may be 1, for example: if the number of questions in the target questionnaire template is 5 and the weight threshold is 1, the initial weight is 1/5=0.2.
The weight configuration module 103 is configured to perform normalization calculation on the initial weight of the target problem to obtain a standard weight of the target problem; and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
In the embodiment of the present invention, the weight configuration module 103 calculates the standard weight by using the following means, including:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of each target problem.
Specifically, in the embodiment of the present invention, the weight configuring module 103 calculates the standard weight W of the target problem j by using the following formula j ：
Wherein, cov j To the initial weight of the target problem j, cov k For the initial weight of the target question k, j, k represent the sequence number of the target question, and m represents the total number of the target questions.
In another embodiment of the present invention, in order to amplify the difference between similar initial weights, the weight configuration module 103 calculates a standard weight by using the following means, including:
performing index conversion on the initial weight of the target problem to obtain the index weight of the target problem;
calculating by using all the exponential weights of the target problem to obtain the exponential weight sum of the target problem;
and calculating a ratio by using the exponential weight of the target problem and the exponential weight sum to obtain the problem weight of each target problem.
For example: if the initial weight of the target problem is 0.1, performing exponential conversion on the initial weight to obtain an exponential weight e 0.1 。
According to the embodiment of the invention, the weight of the corresponding target question in the target questionnaire template is generated according to the standard weight of each target question until the weight generation of all questions in the target questionnaire template is completed, so that the target questionnaire is obtained.
In the embodiment of the present invention, the weight configuration module 103 performs weight configuration on each corresponding question in the target questionnaire template by using the standard weight, and after obtaining the target questionnaire, the target questionnaire can be sent to the corresponding user for questionnaire survey, so that the user can be more accurately cognized with respect to the physical condition, and it is convenient to subsequently match a more appropriate recuperation and old care service for the corresponding user.
Fig. 3 is a schematic structural diagram of an electronic device implementing the method for generating weight of questionnaire questions according to the present invention.
The electronic device may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as a questionnaire question weight generating program, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only to store application software installed in the electronic device and various types of data, such as codes of a questionnaire question weight generating program, but also to temporarily store data that has been output or is to be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (such as a questionnaire question weight generating program) stored in the memory 11 and calling data stored in the memory 11.
The communication bus 12 may be a PerIPheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The communication bus 12 is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
Fig. 3 shows only an electronic device with components, and those skilled in the art will appreciate that the structure shown in fig. 3 is not limiting to the electronic device, and may include fewer or more components than shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power source may also include any component of one or more dc or ac power sources, recharging devices, power failure classification circuits, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Optionally, the communication interface 13 may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices.
Optionally, the communication interface 13 may further include a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally, a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
It is to be understood that the embodiments described are illustrative only and are not to be construed as limiting the scope of the claims.
The questionnaire question weight generating program stored in the memory 11 in the electronic device is a combination of a plurality of computer programs, and when running in the processor 10, can realize:
acquiring a test questionnaire set and a target questionnaire template, wherein all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template;
taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question;
obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question;
analyzing the target answer of the target question to which the grading rule belongs by using the grading rule to obtain the answer grade of the target question;
performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question;
carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem;
and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the electronic device integrated module/unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a computer readable storage medium. The computer readable medium may be non-volatile or volatile. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM).
Embodiments of the present invention may also provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program may implement:
acquiring a test questionnaire set and a target questionnaire template, wherein all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template;
taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question;
obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question;
analyzing the target answer of the target question to which the grading rule belongs by using the grading rule to obtain the answer grade of the target question;
performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question;
carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem;
and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
Further, the computer usable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the same, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A questionnaire question weight generating method, characterized in that the method comprises:
acquiring a test questionnaire set and a target questionnaire template, wherein all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template;
taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question;
obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question;
analyzing a target answer of a target question to which the grading rule belongs by using the grading rule to obtain an answer grade of the target question;
performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question;
carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem;
and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
2. The method of claim 1, wherein the performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question comprises:
calculating the average value and the standard deviation of all answer scores of the target question;
and calculating by using the average value and the standard deviation to obtain the initial weight.
3. The method of claim 1, wherein the performing score dispersion analysis based on all answer scores of the target question to obtain an initial weight of the target question comprises:
acquiring the number of all answer scores of the target question to obtain the number of the answer scores of the target question;
judging whether the number of the answer scores is larger than a preset number threshold value or not;
when the number of the answer scores is larger than the preset number threshold, calculating the average value and the standard deviation of all the answer scores of the target question;
calculating by using the average value and the standard deviation to obtain the initial weight;
and when the number of the answer scores is not more than the preset number threshold, calculating by using the number of the questions in the target questionnaire template and a preset weight threshold to obtain the initial weight.
4. The method for generating weight of questionnaire questions as set forth in claim 1, wherein the normalizing the initial weight of the target question to obtain the standard weight of the target question comprises:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of each target problem.
5. The method of claim 1, wherein the normalizing the initial weight of the target question to obtain the standard weight of the target question comprises:
performing index conversion on the initial weight of the target problem to obtain the index weight of the target problem;
calculating by using the index weights of all the target problems to obtain an index weight sum;
and calculating a ratio of the exponential weight of each target problem to the sum of the exponential weights to obtain a standard weight of each target problem.
6. The method for generating weight of questionnaire questions as claimed in any one of claims 1 to 5, wherein said analyzing the target answer of the target question to which the scoring rule belongs by using the scoring rule to obtain the answer score of the target question comprises:
inquiring the standard answer which is the same as the target answer in the scoring rule to obtain a target standard answer;
and determining the mapping scores associated with the target standard answers in the scoring rules as the answer scores.
7. A questionnaire question weight generation device, comprising:
the system comprises a scoring conversion module, a scoring conversion module and a scoring conversion module, wherein the scoring conversion module is used for acquiring a test questionnaire set and a target questionnaire template, and all questions of each test questionnaire in the test questionnaire set are contained in the target questionnaire template; taking each question in the target questionnaire template as a target question, and taking a test questionnaire containing the target question as a target test questionnaire corresponding to the target question; obtaining a scoring rule of each target question and a target answer of the target question in each target test questionnaire corresponding to the target question; analyzing the target answer of the target question to which the grading rule belongs by using the grading rule to obtain the answer grade of the target question;
the dispersion analysis module is used for carrying out score dispersion analysis on all answer scores of the target question to obtain the initial weight of the target question;
the weight configuration module is used for carrying out normalization calculation on the initial weight of the target problem to obtain the standard weight of the target problem; and generating the weight of each target question in the target questionnaire template by using all the standard weights to obtain the target questionnaire.
8. The apparatus for generating weight of questionnaire questions of claim 7, wherein the normalizing the initial weight of the target question to obtain the standard weight of the target question comprises:
calculating by using the initial weights of all the target problems to obtain an initial weight sum;
and calculating the ratio of the initial weight of each target problem to the sum of the initial weights to obtain the standard weight of the target problem.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the questionnaire question weight generating method of any of claims 1-6.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the questionnaire question weight generating method according to any one of claims 1 to 6.
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