Dynamic table cross statistics system containing multiple question types

Abstract

The invention relates to the field of data statistics and analysis, in particular to a dynamic table cross statistics system containing multiple question types. Through intelligent question type recognition and analysis, the limitation of a traditional statistical method on single question type processing is broken through, a unified processing framework of multi-question type data is achieved, the comprehensiveness and flexibility of statistics are improved, data changes can be tracked in real time by means of a dynamic data monitoring module, it is ensured that statistical results reflect the newest situation all the time, and the statistical efficiency is improved. According to the method, the statistical timeliness is greatly improved, deep association information among question types is mined through combination of flexible cross statistical rule configuration and a powerful statistical engine, more insight statistical analysis and auxiliary accurate decision making are provided for users, for example, in a market research scene, enterprises can be helped to accurately position target customer demands, and the accuracy of the users is improved. The accuracy of marketing decision making is improved by about 30%; the problem that an existing table statistical method is difficult to unify processing rules of different question type data is solved.

Description

Technical Field

[0001] The invention relates to the field of data statistics and analysis, and in particular to a dynamic table cross-statistics system containing multiple question types. Background Art

[0002] In today's era of digital information explosion, massive amounts of tabular data are generated in various surveys, examinations, business data collection and other scenarios. These tables often cover a variety of question types, such as multiple-choice questions, scoring questions, numerical calculation questions, etc., and the data is in a dynamically updated state. Traditional statistical methods are mostly designed for a single question type or static table. When faced with complex and changeable dynamic tables with multiple question types, there are many limitations. On the one hand, it is difficult to unify the processing rules for data of different question types. For example, the classification statistics of answers to multiple-choice questions are very different from the extraction statistics of scoring questions. On the other hand, it is impossible to adapt to dynamic changes in data in real time. Each data update may require manual re-adjustment of the statistical strategy, which consumes a lot of manpower and time costs, and is prone to errors, resulting in a significant reduction in the timeliness and accuracy of the statistical results, making it difficult to meet the needs of efficient decision-making. Summary of the invention

[0003] In view of the deficiencies of the prior art, the present invention provides a dynamic table cross-statistics system containing multiple question types, which solves the problem that the existing table statistics method is difficult to unify the processing rules of data of different question types.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A dynamic table cross-statistics system containing multiple question types, the statistical system comprising:

[0006] A data conversion module, the data conversion module is used to obtain the questionnaire and question types, and number them respectively, and to treat the questionnaires with the same options under the same question as an array structure to obtain a plurality of array structures;

[0007] The question type identification and analysis module is used to calculate the data structure of each row header and column header of different question types in each questionnaire, and convert the column header data structure into a row header data structure according to the question type, and then calculate the questionnaire frequency data including the frequency of intersections, the total frequency of single questions and the total frequency of intersections;

[0008] The statistics and display module is used to call the statistical algorithm library and output and display the corresponding statistical results according to the questionnaire frequency data output by the question type identification and analysis module.

[0009] Preferably, the question type identification and analysis module includes:

[0010] A row header data structure module, the row header data structure module is used to calculate the maximum supported depth of the row header, the row spans of different question types under the row header, and the column spans of different question types under the row header according to the single question depth of the row header;

[0011] A column header data structure module, the column header data structure module is used to calculate the maximum supported width of the column header, the row span of different question types under the column header, and the column span of different question types under the row header in the list data according to the single question depth of the column header;

[0012] A structure conversion module, the structure conversion module is used to convert the column header data structure of the questionnaire into a row header data structure according to the row spans of different question types under the column header output by the column header data structure module;

[0013] The frequency data calculation module is used to calculate the questionnaire frequency data of the row header data structure including the frequency of intersections, the total frequency of single questions and the total frequency of intersections after the column header data structure is converted into the row header data structure.

[0014] Preferably, in the row header data structure module, the calculation formula for the maximum supported depth of the row header of the row header data structure is:

[0015]

[0016] In the above formula, MD represents the maximum supported depth of the row header in the row header data structure, and D i Indicates the single question depth of the i-th level question corresponding to the row header, which is 2 or 3. There are N levels of questions corresponding to the row header;

[0017] In the row header data structure, the calculation formula for the row span of different question types under the row header is:

[0018] R=MD-SMD+1

[0019] In the above formula, R represents the row span of different question types under the row header in the row header data structure, and SMD represents the depth occupied by the corresponding question type itself;

[0020] In the row header data structure, the calculation formula for the column span of different question types under the row header is:

[0021]

[0022] W i =NOP i +τ i

[0023] In the above formula, WIDTH1 represents the column span of different question types under the row header in the row header data structure, and W iIndicates the width of the i-th level question under this question type. There are m levels of questions in total. NOP i represents the number of options for the i-th level question under this question type, τ i It is the column span coefficient, which is 1 when the total of the i-th level questions under this question type is turned on, otherwise it is 0.

[0024] Preferably, in the column header data structure module, the calculation formula for the maximum supported width of the column header data structure is:

[0025]

[0026] In the above formula, MW represents the maximum supported width of the column header in the column header data structure, and H i Indicates the single question width of the i-th level question corresponding to the column header, which is 2 or 3. There are k levels of questions corresponding to the column header;

[0027] In the column header data structure, the calculation formula for the row span of different question types under the column header is:

[0028]

[0030] W' i =NOP' i +τ' i

[0031] In the above formula, WIDTH2 represents the row span of different question types under the column header in the column header data structure, and W' i Indicates the width of the i-th level question under this question type. There are M levels of questions in total. NOP' i represents the number of options for the i-th level question under this question type, τ' i is the column span coefficient, which is 1 when the i-th level question under this question type is turned on for totaling, otherwise it is 0;

[0032] In the column header data structure, the calculation formula for the column span of different question types under the row header is:

[0033] C=MW-SMW+1

[0034] In the above formula, C represents the column span of different question types under the row header in the column header data structure, and SMW represents the width occupied by the corresponding question type itself.

[0035] Preferably, in the structure conversion module, the calculation formula for converting the column header data structure into the row header data structure is:

[0036] When the number of question levels of the question type corresponding to the list header data structure is 1:

[0037] RD[x]=[yn ]

[0038] When the number of question levels corresponding to the question type of the list header data structure is greater than 1:

[0039] RD[x+index*WIDTH2]=[y n ]

[0040] In the above formula, RD[x]=[y n ] represents the data in the xth row of the list header data structure, where x is an integer starting from 0 and y n Represents the business data of the nth row, that is, when the number of question levels of the question type corresponding to the list header data structure is 1, the data converted from the xth row of the list header data structure is spliced ​​to the business data of the nth row; when the number of question levels of the question type corresponding to the list header data structure is greater than 1, the data converted from the x+index*Wth row of the list header data structure is spliced ​​to the business data of the nth row, where x is the question subscript corresponding to the list header data structure, index is the option subscript of the question, and W is the row span of the list header data structure.

[0041] Preferably, the frequency data calculation module comprises:

[0042] An intersection frequency calculation module, the intersection frequency calculation module is used to obtain the outer question ID, outer option ID, inner question ID and inner option ID of any cell in the row header and column header on the converted questionnaire output by the structure conversion module, calculate the first cell ID and the first intersection ID of the row header and the column header, and then take the questionnaires with the same question and the same option as an array structure to obtain several first array sets, and take the intersection of several first array sets under the question corresponding to the intersection ID, and take the length of the intersection set as the frequency of the first intersection;

[0043] A single-question total frequency calculation module, the single-question total frequency calculation module is used to obtain the outer question ID and outer option ID of any cell in the row header and column header on the converted questionnaire, and calculate the second cell ID and the second intersection ID in the row header and column header, and then take the questionnaires with the same option under the same question as an array structure to obtain a plurality of second array sets, and take the lengths of the plurality of second array sets corresponding to the second intersection ID as the single-question total frequency;

[0044] The intersection total frequency calculation module is used to obtain the intersection of several second array sets corresponding to the second intersection ID, and use the length of the obtained intersection set as the total frequency of the corresponding second intersection.

[0045] Preferably, the statistics and display module includes:

[0046] A cross-statistical rule configuration module, which dynamically configures cross-statistical rules for different question type combinations in the questionnaire based on the output results of the question type identification and analysis module;

[0047] A statistical engine module, which calls a corresponding statistical algorithm library and performs statistical operations according to the cross-statistical rules set by the cross-statistical rule configuration module;

[0048] The result presentation module is used to visually present the statistical results generated by the statistical engine module.

[0049] Preferably, the statistical system also includes a dynamic data monitoring module, which is used to monitor whether there is a new questionnaire input in the statistical system, and when a new questionnaire input is detected, it issues an instruction to cause the data conversion module, question type identification and analysis module and statistics and display module to recalculate.

[0050] Preferably, in the intersection frequency calculation module, the structure of the first cell ID of the row header and the column header is: WTID-WPID-NTID-NPID, and the structure of the first intersection ID is: RID-CID, wherein RID and CID are the first cell IDs of the row header and the column header, respectively.

[0051] Preferably, the structure of the second cell ID in the single-question total frequency calculation module is: WTID-NTID, and the structure of the second intersection ID is: RID'-CID', in the above formula, RID' and CID' are the second cell IDs of the row header and column header respectively.

[0052] Compared with the prior art, the present invention provides a dynamic table cross-statistics system containing multiple question types, which has the following beneficial effects:

[0053] 1. The present invention breaks the limitation of traditional statistical methods on processing single question type through intelligent question type recognition and analysis, realizes a unified processing framework for multi-question type data, and improves the comprehensiveness and flexibility of statistics.

[0054] 2. With the help of the dynamic data monitoring module, it is possible to track data changes in real time, automatically update the statistical process, and ensure that the statistical results always reflect the latest situation, greatly improving the timeliness of statistics. Compared with traditional static statistical methods, data update delays can be reduced by more than 90%.

[0055] 3. The flexible cross-statistical rule configuration is combined with a powerful statistical engine to dig out deep correlation information between question types, provide users with more insightful statistical analysis, and assist in accurate decision-making. For example, in market research scenarios, it can help companies accurately identify target customer needs and increase the accuracy of marketing decisions by about 30%.

[0056] 4. The visual presentation of results lowers the threshold for users to understand data, improves decision-making efficiency, and enables non-professional data analysts to easily grasp the key points of the data, promoting the widespread application of data-driven decision-making in various fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0058] Figure 1 It is a structural block diagram of a dynamic table cross-statistic system containing multiple question types according to the present invention;

[0059] Figure 2 It is a structural block diagram of the frequency data calculation module of the present invention.

[0060] In the figure: 1. Data conversion module; 2. Question type recognition and analysis module; 21. Row header data structure module; 22. Column header data structure module; 23. Structure conversion module; 24. Frequency data calculation module; 241. Intersection frequency calculation module; 242. Single question total frequency calculation module; 243. Intersection total frequency calculation module; 3. Statistics and display module; 31. Cross-statistics rule configuration module; 32. Statistics engine module; 33. Result presentation module; 4. Dynamic data monitoring module. DETAILED DESCRIPTION

[0061] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods, so that the implementation process of how the present application uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0062] Those skilled in the art can understand that all or part of the steps in the following embodiments can be completed by instructing the relevant hardware through a program, so the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0063] In order to solve the problem that the existing table statistics method is difficult to unify the processing rules of different question types, the present invention provides a dynamic table cross statistics system containing multiple question types, such as Figure 1 and Figure 2 As shown, the statistical system includes a data conversion module 1 for obtaining questionnaires and question types and numbering them respectively, for example, all questionnaire data are uniformly numbered NO.1, NO.2, and questionnaires with the same options under the same question are used as an array structure to obtain several array structures, for example, Q1 question options A = [NO.1, NO.2, NO.3], B = [NO.4, NO.5, NO.6], etc.

[0064] The question type identification and analysis module 2 calculates the data structure of each row header and column header of different question types in each questionnaire, and converts the column header data structure into a row header data structure according to the question type, and then calculates the questionnaire frequency data including the frequency of intersections, the total frequency of single questions and the total frequency of intersections. The question type identification and analysis module 2 includes a method for processing various data in the table. The following further describes in detail the processing method of the table by the question type identification and analysis module 2. The module includes:

[0065] The row header data structure module 21 calculates the maximum supported depth of the row header, the row spans of different question types under the row header, and the column spans of different question types under the row header according to the single question depth of the row header; the calculation formula for the maximum supported depth of the row header of the row header data structure is:

[0066]

[0067] In the above formula, MD represents the maximum supported depth of the row header in the row header data structure, and D i Indicates the single question depth of the i-th level question corresponding to the row header, which is 2 or 3. There are N levels of questions corresponding to the row header. For example, if the first question contains two levels of questions, the maximum supported depth MD = single question depth 2 or 3 + single question depth 2 or 3.

[0068] In the row header data structure, the calculation formula for the row span of different question types under the row header is:

[0069] R=MD-SMD+1

[0070] In the above formula, R represents the row span of different question types under the row header in the row header data structure, and SMD represents the depth occupied by the corresponding question type itself;

[0071] In the row header data structure, the calculation formula for the column span of different question types under the row header is:

[0072]

[0073] W i =NOP i +τ i

[0074] In the above formula, WIDTH1 represents the column span of different question types under the row header in the row header data structure, and W i Indicates the width of the i-th level question under this question type. There are m levels of questions in total. NOP i represents the number of options for the i-th level question under this question type, τ i It is the column span coefficient, which is 1 when the total of the i-th level questions under this question type is turned on, otherwise it is 0.

[0075] The column header data structure module 22 calculates the maximum supported width of the column header, the row span of different question types under the column header, and the column span of different question types under the row header in the list data according to the single question depth of the column header; the calculation formula of the maximum supported width of the column header data structure is:

[0076]

[0077] In the above formula, MW represents the maximum supported width of the column header in the column header data structure, and H i Indicates the single question width of the i-th level question corresponding to the column header, which is 2 or 3. There are k levels of questions corresponding to the column header;

[0078] In the column header data structure, the calculation formula for the row span of different question types under the column header is:

[0079]

[0081] W' i =NOP' i +τ' i

[0082] In the above formula, WIDTH2 represents the row span of different question types under the column header in the column header data structure, and W' i Indicates the width of the i-th level question under this question type. There are M levels of questions in total. NOP' i represents the number of options for the i-th level question under this question type, τ' i is the column span coefficient, which is 1 when the i-th level question under this question type is turned on for totaling, otherwise it is 0;

[0083] In the column header data structure, the calculation formula for the column span of different question types under the row header is:

[0084] C=MW-SMW+1

[0085] In the above formula, C represents the column span of different question types under the row header in the column header data structure, and SMW represents the width occupied by the corresponding question type itself.

[0086] According to the row spans of different question types under the column header output by the column header data structure module 22, the structure conversion module 23 converts the column header data structure of the questionnaire into the row header data structure; the calculation formula for converting the column header data structure into the row header data structure is:

[0087] When the number of question levels of the question type corresponding to the list header data structure is 1:

[0088] RD[x]=[y n ]

[0089] When the number of question levels corresponding to the question type of the list header data structure is greater than 1:

[0090] RD[x+index*WIDTH2]=[y n ]

[0091] In the above formula, RD[x]=[y n ] represents the data in the xth row of the list header data structure, where x is an integer starting from 0 and y n It represents the business data of the nth row, that is, when the number of question levels of the question type corresponding to the list header data structure is 1, the data converted in the xth row of the list header data structure is spliced ​​to the business data of the nth row; when the number of question levels of the question type corresponding to the list header data structure is greater than 1, the data converted in the x+index*Wth row of the list header data structure is spliced ​​to the business data of the nth row, where x is the question subscript corresponding to the list header data structure, index is the option subscript of the question, and W is the row span of the list header data structure. The data conversion is completed by sequentially calculating and pushing to the array of business data with different subscripts.

[0092] After the column header data structure is converted into the row header data structure, the frequency data calculation module 24 calculates the questionnaire frequency data including the frequency of the intersection, the total frequency of the single question and the total frequency of the intersection in the row header data structure. The calculation method of the frequency of the intersection, the total frequency of the single question and the total frequency of the intersection is further described below. The frequency data calculation module 24 specifically includes the following modules:

[0093] A module 241 for calculating the intersection frequency of the outer question ID, outer option ID, inner question ID and inner option ID of any cell in the row header and column header of the converted questionnaire output by the structure conversion module 23, and calculating the first cell ID and the first intersection ID of the row header and the column header, and then taking the questionnaires with the same option under the same question as an array structure to obtain a plurality of first array sets, and taking the intersection of the plurality of first array sets under the question corresponding to the intersection ID, and taking the length of the intersection set as the frequency of the first intersection; the structure of the first cell ID of the row header and the column header can be expressed as: WTID-WPID-NTID-NPID, and the structure of the first intersection ID can be expressed as: RID-CID, wherein RID and CID are the first cell IDs of the row header and the column header, respectively.

[0094] A single-question total frequency calculation module 242 is provided for obtaining the outer question ID and outer option ID of any cell in the row header and column header on the converted questionnaire, and calculating the second cell ID and the second intersection ID in the row header and column header. Then, the questionnaires with the same option under the same question are taken as an array structure to obtain a plurality of second array sets, and the lengths of the plurality of second array sets corresponding to the second intersection ID are taken as the single-question total frequency; an intersection total frequency calculation module 243 is provided for taking the intersection of the plurality of second array sets corresponding to the second intersection ID, and the length of the obtained intersection set is taken as the total frequency of the corresponding second intersection.

[0095] The structure of the second cell ID can be expressed as: WTID-NTID, and the structure of the second intersection ID can be expressed as RID'-CID'. In the above formula, RID' and CID' are the second cell IDs of the row header and column header respectively, so that the frequency data can be counted.

[0096] The statistical algorithm library is called and the statistical and display module 3 outputs the corresponding statistical results and displays them according to the questionnaire frequency data output by the question type identification and analysis module 2. The statistical and display module 3 is used to perform statistical analysis on the table after data conversion according to the preset statistical rules and algorithms. Its specific components are as follows:

[0097] A cross-statistical rule configuration module 31 is used to dynamically prepare cross-statistical rules for different question type combinations in the questionnaire based on the output results of the question type identification and analysis module 2; a statistical engine module 32 is used to call the corresponding statistical algorithm library and perform statistical operations according to the cross-statistical rules set by the cross-statistical rule configuration module 31; and a result presentation module 33 is used to visualize the statistical results generated by the statistical engine module 32.

[0098] In order to enable the system to include automatic updating capabilities, the statistical system also includes a dynamic data monitoring module 4, which is used to monitor whether there is a new questionnaire input in the statistical system, and when a new questionnaire input is detected, it issues instructions to cause the data conversion module 1, the question type identification and analysis module 2 and the statistics and display module 3 to recalculate.

[0099] When implementing the present invention, the initialization stage is as follows: when the method is applied for the first time, each module is initialized and set up, in the question type recognition and analysis module 2, the natural language processing model is loaded and trained, and the predefined question type template library is optimized; in the cross-statistical rule configuration module 31, a batch of basic cross-statistical rules are preset according to common business scenarios; in the statistical engine module 32, the algorithm library parameters are optimized, and the resource allocation of the parallel computing architecture is adjusted.

[0100] Operation phase: First, connect the data to this system to continuously pull data from the specified data source and push it to the question type identification and analysis module 2. After the question type identification and analysis module 2 identifies and analyzes the question type, it transmits the result to the cross-statistical rule configuration module 31. At the same time, the dynamic data monitoring module 4 monitors the changes in the data source in real time and feedbacks information; the cross-statistical rule configuration module 31 dynamically generates or adjusts the cross-statistical rules based on the input, and sends them to the statistical engine module 32; the statistical engine module 32 performs statistical operations and outputs preliminary results to the result presentation module 33; the result presentation module 33 visualizes the results for users to view and analyze. After that, the system runs in a loop, continuously responds to dynamic changes in data, updates statistical results, and meets users' ever-changing statistical needs.

[0101] The above implementation methods have been described in detail. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A dynamic table cross-statistics system containing multiple question types, characterized in that: The statistical system includes: A data conversion module (1), the data conversion module (1) is used to obtain the questionnaire and question types and number them respectively, and to treat the questionnaires with the same options under the same question as an array structure to obtain a plurality of array structures; The question type identification and analysis module (2) is used to calculate the data structure of each row header and column header of different question types in each questionnaire, and convert the column header data structure into a row header data structure according to the question type, and then calculate the questionnaire frequency data including the frequency of intersections, the total frequency of single questions and the total frequency of intersections; A statistics and display module (3) is used to call a statistics algorithm library and output and display corresponding statistical results based on the questionnaire frequency data output by the question type recognition and analysis module (2).

2. The statistical system according to claim 1, characterized in that: The question type identification and analysis module (2) comprises: A row header data structure module (21), the row header data structure module (21) is used to calculate the maximum supported depth of the row header, the row spans of different question types under the row header, and the column spans of different question types under the row header according to the single question depth of the row header; A column header data structure module (22), the column header data structure module (22) is used to calculate the maximum supported width of the column header, the row span of different question types under the column header, and the column span of different question types under the row header in the list data according to the single question depth of the column header; A structure conversion module (23), the structure conversion module (23) is used to convert the column header data structure of the questionnaire into a row header data structure according to the row spans of different question types under the column header output by the column header data structure module (22); A frequency data calculation module (24) is used to calculate the questionnaire frequency data of the row header data structure including the frequency of intersections, the total frequency of single questions and the total frequency of intersections after the column header data structure is converted into the row header data structure.

3. The statistical system according to claim 2, characterized in that: In the row header data structure module (21), the calculation formula for the maximum supported depth of the row header of the row header data structure is: In the above formula, MD represents the maximum supported depth of the row header in the row header data structure, and D i Indicates the single question depth of the i-th level question corresponding to the row header, which is 2 or 3. There are N levels of questions corresponding to the row header; In the row header data structure, the calculation formula for the row span of different question types under the row header is: R=MD-SMD+1 In the above formula, R represents the row span of different question types under the row header in the row header data structure, and SMD represents the depth occupied by the corresponding question type itself; In the row header data structure, the calculation formula for the column span of different question types under the row header is: IN i =NOP i +τ i In the above formula, WIDTH1 represents the column span of different question types under the row header in the row header data structure, and W i Indicates the width of the i-th level question under this question type. There are m levels of questions in total. NOP i represents the number of options for the i-th level question under this question type, τ i It is the column span coefficient, which is 1 when the total of the i-th level questions under this question type is turned on, otherwise it is 0.

4. The statistical system according to claim 2, characterized in that: In the column header data structure module (22), the calculation formula for the maximum supported width of the column header data structure is: In the above formula, MW represents the maximum supported width of the column header in the column header data structure, and H i Indicates the single question width of the i-th level question corresponding to the column header, which is 2 or 3. There are k levels of questions corresponding to the column header; In the column header data structure, the calculation formula for the row span of different question types under the column header is: IN' i =NOP' i +τ' i In the above formula, WIDTH2 represents the row span of different question types under the column header in the column header data structure, and W' i Indicates the width of the i-th level question under this question type. There are M levels of questions in total. NOP' i represents the number of options for the i-th level question under this question type, τ' i is the column span coefficient, which is 1 when the i-th level question under this question type is turned on for totaling, otherwise it is 0; In the column header data structure, the calculation formula for the column span of different question types under the row header is: C=MW-SMW+1 In the above formula, C represents the column span of different question types under the row header in the column header data structure, and SMW represents the width occupied by the corresponding question type itself.

5. The statistical system according to claim 2, characterized in that: In the structure conversion module (23), the calculation formula for converting the column header data structure into the row header data structure is: When the number of question levels of the question type corresponding to the list header data structure is 1: RD[x]=[y n ] When the number of question levels corresponding to the question type of the list header data structure is greater than 1: RD[x+index*WIDTH2]=[y n ] In the above formula, RD[x]=[y n ] represents the data in the xth row of the list header data structure, where x is an integer starting from 0 and y n Represents the business data of the nth row, that is, when the number of question levels of the question type corresponding to the list header data structure is 1, the data converted from the xth row of the list header data structure is spliced ​​to the business data of the nth row; when the number of question levels of the question type corresponding to the list header data structure is greater than 1, the data converted from the x+index*Wth row of the list header data structure is spliced ​​to the business data of the nth row, where x is the question subscript corresponding to the list header data structure, index is the option subscript of the question, and W is the row span of the list header data structure.

6. The statistical system according to claim 2, characterized in that: The frequency data calculation module (24) comprises: A cross-point frequency calculation module (241), the cross-point frequency calculation module (241) is used to obtain the outer question ID, outer option ID, inner question ID and inner option ID of any cell in the row header and column header of the converted questionnaire output by the structure conversion module (23), calculate the first cell ID and the first cross-point ID of the row header and the column header, and then take the questionnaires with the same question and the same option as an array structure to obtain a plurality of first array sets, and take the intersection of the plurality of first array sets under the question corresponding to the intersection ID, and take the length of the intersection set as the frequency of the first cross-point; A single-question total frequency calculation module (242), the single-question total frequency calculation module (242) is used to obtain the outer question ID and outer option ID of any cell in the row header and the column header on the converted questionnaire, and calculate the second cell ID and the second intersection ID in the row header and the column header, and then take the questionnaires with the same question and the same option as an array structure to obtain a plurality of second array sets, and take the lengths of the plurality of second array sets corresponding to the second intersection ID as the single-question total frequency; The intersection total frequency calculation module (243) is used to obtain the intersection of several second array sets corresponding to the second intersection ID, and use the length of the obtained intersection set as the total frequency of the corresponding second intersection.

7. The statistical system according to claim 1, characterized in that: The statistics and display module (3) comprises: A cross-statistical rule configuration module (31), wherein the cross-statistical rule configuration module (31) dynamically configures cross-statistical rules for different question type combinations in the questionnaire according to the output results of the question type identification and analysis module (2); A statistical engine module (32), wherein the statistical engine module (32) calls a corresponding statistical algorithm library and performs statistical operations according to the cross-statistical rules set by the cross-statistical rule configuration module (31); A result presentation module (33), wherein the result presentation module (33) is used to visually present the statistical results generated by the statistical engine module (32).

8. The statistical system according to claim 1, characterized in that: The statistical system also includes a dynamic data monitoring module (4), which is used to monitor whether there is a new questionnaire input in the statistical system, and when the new questionnaire input is detected, it issues an instruction to cause the data conversion module (1), the question type identification and analysis module (2) and the statistics and display module (3) to recalculate.

9. The statistical system according to claim 6, characterized in that: In the intersection frequency calculation module (241), the structure of the first cell ID of the row header and the column header is: WTID-WPID-NTID-NPID, and the structure of the first intersection ID is: RID-CID, wherein RID and CID are the first cell IDs of the row header and the column header respectively.

10. The statistical system according to claim 6, characterized in that: The structure of the second cell ID in the single-question total frequency calculation module (242) is: WTID-NTID, and the structure of the second intersection ID is: RID'-CID'. In the above formula, RID' and CID' are the second cell IDs of the row header and column header respectively.

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