Information analysis method and system based on artificial intelligence and big data

Abstract

The invention provides an information analysis method and system based on artificial intelligence and big data, and the method comprises the steps: inputting to-be-analyzed big data into a plurality of artificial intelligence models, and obtaining a plurality of hidden information analysis results and the information analysis cost of each hidden information analysis result; obtaining a result score of each hidden information analysis result according to a result error of each hidden information analysis result; according to the to-be-analyzed big data, the result score and the information analysis cost, obtaining a cost performance score of each artificial intelligence model; according to the information analysis cost, the result score and the cost performance score, displaying each artificial intelligence model for a user to select; and determining the hidden information analysis result of the artificial intelligence model selected by the user as a target information analysis result, and displaying the target information analysis result. The difficulty that a user selects artificial intelligence to carry out information analysis on big data can be reduced.

Description

Technical Field

[0001] The present application relates to the technical field of information analysis, and specifically to an information analysis method and system based on artificial intelligence and big data. Background Art

[0002] The combination of artificial intelligence and big data analysis can quickly realize information analysis to obtain the information analysis results required by users. However, the accuracy of artificial intelligence in analyzing big data is affected by many factors, such as the network structure of artificial intelligence, the amount of data used for training, and training parameters. Therefore, an artificial intelligence with high accuracy often requires a huge cost, which leads to the fact that most artificial intelligences on the market require a fee to use. However, since there are too many artificial intelligences on the market, there are differences in accuracy and charges, which makes it difficult for users to choose appropriate artificial intelligence to analyze big data according to actual needs. That is, the existing technology has a technical defect that it is difficult to select artificial intelligence to analyze big data. Summary of the invention

[0003] The purpose of this application is to provide an information analysis method and system based on artificial intelligence and big data, which can overcome the shortcomings and deficiencies in the prior art.

[0004] A first aspect of an embodiment of the present application provides an information analysis method based on artificial intelligence and big data, comprising:

[0005] Inputting the big data to be analyzed into several artificial intelligence models to obtain several hidden information analysis results and information analysis costs of each hidden information analysis result;

[0006] Obtaining result scores for each of the hidden information analysis results according to result errors of each of the hidden information analysis results;

[0007] Obtaining a cost-effectiveness score for each of the artificial intelligence models based on the big data to be analyzed, the result score, and the information analysis fee;

[0008] Displaying each of the artificial intelligence models according to the information analysis fee, the result score and the cost performance score for selection by the user;

[0009] The hidden information analysis result of the artificial intelligence model selected by the user is determined as the target information analysis result, and the target information analysis result is displayed.

[0010] Furthermore, the step of obtaining a result score of each hidden information analysis result according to a result error of each hidden information analysis result includes:

[0011] The result score is obtained by the following formula:

[0012]

[0013] Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

[0014] Furthermore, the step of obtaining the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee includes:

[0015] According to the result score, obtaining the cost weight of each artificial intelligence model; wherein the smaller the result score, the smaller the cost weight;

[0016] The cost-effectiveness score of each artificial intelligence model is obtained based on the information analysis fee, the fee weight and the data volume of the big data to be analyzed.

[0017] Furthermore, the step of obtaining the cost-performance score of each artificial intelligence model according to the information analysis fee, the fee weight and the data volume of the big data to be analyzed includes:

[0018] Analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model;

[0019] The cost performance rating is obtained according to the cost value and the data volume.

[0020] Furthermore, the step of displaying each of the artificial intelligence models according to the information analysis cost, the result score and the cost performance score includes:

[0021] Analyze the cost according to the information, and display each of the artificial intelligence models in order from small to large;

[0022] Or, according to the result scores, the artificial intelligence models are displayed in descending order;

[0023] Alternatively, the artificial intelligence models may be displayed in order of size based on the cost-effectiveness score.

[0024] A second aspect of the embodiments of the present application provides an information analysis system based on artificial intelligence and big data, including:

[0025] A hidden information analysis result and cost acquisition module is used to input the big data to be analyzed into several artificial intelligence models to obtain several hidden information analysis results and the information analysis cost of each hidden information analysis result;

[0026] A result score acquisition module, used for obtaining the result score of each hidden information analysis result according to the result error of each hidden information analysis result;

[0027] A cost-effectiveness score acquisition module, used to obtain the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee;

[0028] A display module, for displaying each of the artificial intelligence models according to the information analysis cost, the result score and the cost performance score, for user selection;

[0029] The target information analysis result display module is used to determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result and display the target information analysis result.

[0030] Furthermore, the result score acquisition module is used to obtain the result score through the following formula:

[0031]

[0032] Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

[0033] Furthermore, the cost performance rating acquisition module includes:

[0034] A fee weight acquisition submodule is used to acquire the fee weight of each artificial intelligence model according to the result score; wherein the smaller the result score, the smaller the fee weight;

[0035] The cost performance score acquisition submodule is used to obtain the cost performance score of each artificial intelligence model based on the information analysis cost, the cost weight and the data volume of the big data to be analyzed.

[0036] Furthermore, the cost performance rating acquisition submodule includes:

[0037] A cost value acquisition submodule, used to analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model;

[0038] The value and data volume calculation submodule is used to obtain the cost performance score according to the cost value and the data volume.

[0039] Furthermore, the target information analysis result display module is used to arrange and display each of the artificial intelligence models from small to large according to the information analysis cost; or, to arrange and display each of the artificial intelligence models from large to small according to the result score; or, to arrange and display each of the artificial intelligence models from large to small according to the cost-effectiveness score.

[0040] Compared with the related art, the present application obtains several hidden information analysis results and the information analysis cost of each hidden information analysis result by inputting the big data to be analyzed into several artificial intelligence models, and then obtains the result score of each hidden information analysis result according to the result error of each hidden information analysis result, and then obtains the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis cost, so as to display each artificial intelligence model according to the information analysis cost, the result score and the cost-effectiveness score, so as to facilitate the user to select the artificial intelligence model according to the information analysis cost, the result score and the cost-effectiveness score, and finally determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result, and display the target information analysis result, so as to facilitate the user to select from the hidden information analysis results of multiple artificial intelligence models to obtain the target information analysis result that meets his requirements, reduce the difficulty of selecting artificial intelligence to perform information analysis on big data, and improve the convenience of users to select artificial intelligence when they need to perform information analysis on big data, and because the hidden information analysis result will not be displayed to the user, the concealment of the hidden information analysis results of other artificial intelligence models that have not been selected can also be protected.

[0041] In order to provide a clearer understanding of the present application, the specific implementation of the present application will be described below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flowchart of an information analysis method based on artificial intelligence and big data according to an embodiment of the present application.

[0043] Figure 2 This is a flowchart of steps S31-S32 of an information analysis method based on artificial intelligence and big data in one embodiment of the present application.

[0044] Figure 3 This is a schematic diagram of the module connections of an information analysis system based on artificial intelligence and big data according to one embodiment of the present application.

[0045] 1. Hidden information analysis results and cost acquisition module; 2. Result score acquisition module; 3. Cost performance score acquisition module; 4. Display module; 5. Target information analysis results display module. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0047] It should be clear that the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present application.

[0048] When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. The singular forms of "a", "said" and "the" used in the present application and the appended claims are also intended to include the majority form, unless the context clearly indicates other meanings. The words "if" / "if" used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0049] In addition, in the description of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0050] See also Figure 1 , which is a flow chart of an information analysis method based on artificial intelligence and big data according to an embodiment of the present application, including:

[0051] S1: inputting the big data to be analyzed into several artificial intelligence models to obtain several hidden information analysis results and the information analysis cost of each hidden information analysis result;

[0052] S2: obtaining a result score for each of the hidden information analysis results according to the result error of each of the hidden information analysis results;

[0053] S3: Obtaining a cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee;

[0054] S4: Displaying each of the artificial intelligence models according to the information analysis fee, the result score and the cost performance score for selection by the user;

[0055] S5: Determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result, and display the target information analysis result.

[0056] Among them, several artificial intelligence models can correspond to a common platform, so that users can directly input the big data to be analyzed on the platform, and then display each artificial intelligence model according to the information analysis cost, the result score and the cost-effectiveness score, so that users can select the target information analysis results to be displayed. Specifically, several artificial intelligence models can be determined according to user needs, for example, according to the type of data input by the user and the information analysis items to be obtained.

[0057] In a feasible embodiment, the step of obtaining a result score of each hidden information analysis result according to a result error of each hidden information analysis result includes:

[0058] The result score is obtained by the following formula:

[0059]

[0060] Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

[0061] The result data of the hidden information analysis result may be a value of the hidden information analysis result, or a value obtained by converting the hidden information analysis result through a preset conversion model, wherein the preset conversion model refers to a conversion model selected or uploaded by the user.

[0062] See also Figure 2 In a feasible embodiment, the step of S3: obtaining the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis cost, comprises:

[0063] S31: Obtaining the cost weight of each artificial intelligence model according to the result score; wherein the smaller the result score, the smaller the cost weight;

[0064] Among them, the result score is used to indicate the error degree between the hidden information analysis result of the artificial intelligence model and the standard deviation of all hidden information analysis results, that is, the result score can also be understood as an error score. The smaller the result score, the higher the accuracy of the hidden information analysis result of the artificial intelligence model. The accuracy ratio of the artificial intelligence model is greater than the cost ratio, so the cost weight of the artificial intelligence model is smaller. A relationship or correspondence between the result score and the cost weight can be established in terms of the operation method, that is, after the result score is operated in a preset manner, the corresponding cost weight can be obtained, or according to the correspondence between the result score and the cost weight, the cost weight corresponding to the result score can be directly obtained.

[0065] S32: Obtain the cost-effectiveness score of each artificial intelligence model based on the information analysis fee, the fee weight and the data volume of the big data to be analyzed.

[0066] Specifically, the step of obtaining the cost-performance score of each artificial intelligence model according to the information analysis fee, the fee weight and the data volume of the big data to be analyzed in S32 includes:

[0067] S321: Analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model;

[0068] The cost value is the product of the information analysis cost and the cost weight.

[0069] S322: Obtain the cost performance rating according to the cost value and the data volume.

[0070] The cost-effectiveness score is the quotient obtained by dividing the cost value by the data volume.

[0071] In a feasible embodiment, the historical records of the hidden information analysis results of the artificial intelligence model selected by the user, as well as the user's cost-effectiveness rating made by the user on the historical records, can also be used as training samples to train a cost-effectiveness rating prediction model for the user, and then the big data to be analyzed, the result rating, and the information analysis fee are input into the cost-effectiveness rating prediction model to obtain the cost-effectiveness rating corresponding to the user. Among them, the training sample at least includes the big data to be analyzed, the result rating, the information analysis fee, and the user cost-effectiveness rating corresponding to the historical records. Among them, the data type, data volume, and data source of the big data to be analyzed can all be used as reference features of the training sample to train a cost-effectiveness rating prediction model.

[0072] In a feasible embodiment, the step of displaying each of the artificial intelligence models according to the information analysis cost, the result score and the cost performance score in S4 includes:

[0073] Analyze the cost according to the information, and display each of the artificial intelligence models in order from small to large;

[0074] Or, according to the result scores, the artificial intelligence models are displayed in descending order;

[0075] Alternatively, the artificial intelligence models may be displayed in order of size based on the cost-effectiveness score.

[0076] Compared with the related art, the present application obtains several hidden information analysis results and the information analysis cost of each hidden information analysis result by inputting the big data to be analyzed into several artificial intelligence models, and then obtains the result score of each hidden information analysis result according to the result error of each hidden information analysis result, and then obtains the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis cost, so as to display each artificial intelligence model according to the information analysis cost, the result score and the cost-effectiveness score, so as to facilitate the user to select the artificial intelligence model according to the information analysis cost, the result score and the cost-effectiveness score, and finally determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result, and display the target information analysis result, so as to facilitate the user to select from the hidden information analysis results of multiple artificial intelligence models to obtain the target information analysis result that meets his requirements, reduce the difficulty of selecting artificial intelligence to perform information analysis on big data, and improve the convenience of users to select artificial intelligence when they need to perform information analysis on big data, and because the hidden information analysis result will not be displayed to the user, the concealment of the hidden information analysis results of other artificial intelligence models that have not been selected can also be protected.

[0077] See also Figure 3 The second aspect of the embodiment of the present application provides an information analysis system based on artificial intelligence and big data, including:

[0078] Hidden information analysis result and cost acquisition module 1, used to input the big data to be analyzed into several artificial intelligence models, and obtain several hidden information analysis results and information analysis costs of each hidden information analysis result;

[0079] A result score acquisition module 2, used for obtaining a result score of each hidden information analysis result according to a result error of each hidden information analysis result;

[0080] The cost performance score acquisition module 3 is used to obtain the cost performance score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee;

[0081] Display module 4, used for displaying each artificial intelligence model according to the information analysis cost, the result score and the cost performance score for user selection;

[0082] The target information analysis result display module 5 is used to determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result, and display the target information analysis result.

[0083] In a feasible embodiment, the result score acquisition module 2 is used to obtain the result score through the following formula:

[0084]

[0085] Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

[0086] In a feasible embodiment, the cost performance rating acquisition module 3 includes:

[0087] A fee weight acquisition submodule is used to acquire the fee weight of each artificial intelligence model according to the result score; wherein the smaller the result score, the smaller the fee weight;

[0088] The cost performance score acquisition submodule is used to obtain the cost performance score of each artificial intelligence model based on the information analysis cost, the cost weight and the data volume of the big data to be analyzed.

[0089] In a feasible embodiment, the cost performance rating acquisition submodule includes:

[0090] A cost value acquisition submodule, used to analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model;

[0091] The value and data volume calculation submodule is used to obtain the cost performance score according to the cost value and the data volume.

[0092] In a feasible embodiment, the target information analysis result display module 5 is used to arrange and display each of the artificial intelligence models from small to large according to the information analysis cost; or, according to the result score, arrange and display each of the artificial intelligence models from large to small; or, according to the cost-effectiveness score, arrange and display each of the artificial intelligence models from large to small.

[0093] It should be noted that the information analysis system based on artificial intelligence and big data provided in the second embodiment of the present application only uses the division of the above-mentioned functional modules as an example when executing the information analysis method based on artificial intelligence and big data. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the information analysis system based on artificial intelligence and big data provided in the second embodiment of the present application and the information analysis method based on artificial intelligence and big data in the first embodiment of the present application belong to the same concept. The implementation process is detailed in the method embodiment, which will not be repeated here.

[0094] The system embodiments described above are merely illustrative, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application. Ordinary technicians in this field can understand and implement it without creative work.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the function selected in the process. Figure 1A process or multiple processes and / or boxes Figure 1 function selected in a box or multiple boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 steps for the function selected in a box or multiple boxes.

[0098] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0099] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0100] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0101] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0102] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. An information analysis method based on artificial intelligence and big data, characterized in that: include: Inputting the big data to be analyzed into several artificial intelligence models to obtain several hidden information analysis results and information analysis costs of each hidden information analysis result; Obtaining result scores for each of the hidden information analysis results according to result errors of each of the hidden information analysis results; Obtaining a cost-effectiveness score for each of the artificial intelligence models based on the big data to be analyzed, the result score, and the information analysis fee; Displaying each of the artificial intelligence models according to the information analysis fee, the result score and the cost performance score for selection by the user; The hidden information analysis result of the artificial intelligence model selected by the user is determined as the target information analysis result, and the target information analysis result is displayed.

2. The information analysis method based on artificial intelligence and big data according to claim 1, characterized in that: The step of obtaining a result score of each hidden information analysis result according to a result error of each hidden information analysis result comprises: The result score is obtained by the following formula: Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

3. The information analysis method based on artificial intelligence and big data according to claim 1, characterized in that: The step of obtaining the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee includes: According to the result score, obtaining the cost weight of each artificial intelligence model; wherein the smaller the result score, the smaller the cost weight; The cost-effectiveness score of each artificial intelligence model is obtained based on the information analysis fee, the fee weight and the data volume of the big data to be analyzed.

4. The information analysis method based on artificial intelligence and big data according to claim 3 is characterized in that: The step of obtaining the cost-performance score of each artificial intelligence model according to the information analysis fee, the fee weight and the data volume of the big data to be analyzed includes: Analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model; The cost performance rating is obtained according to the cost value and the data volume.

5. The information analysis method based on artificial intelligence and big data according to claim 1, characterized in that: The step of displaying each of the artificial intelligence models according to the information analysis cost, the result score and the cost performance score comprises: Analyze the cost according to the information, and display each of the artificial intelligence models in order from small to large; Or, according to the result scores, the artificial intelligence models are displayed in descending order; Alternatively, the artificial intelligence models may be displayed in order of size based on the cost-effectiveness score.

6. An information analysis system based on artificial intelligence and big data, characterized in that: include: A hidden information analysis result and cost acquisition module is used to input the big data to be analyzed into several artificial intelligence models to obtain several hidden information analysis results and the information analysis cost of each hidden information analysis result; A result score acquisition module, used for obtaining the result score of each hidden information analysis result according to the result error of each hidden information analysis result; A cost-effectiveness score acquisition module, used to obtain the cost-effectiveness score of each artificial intelligence model according to the big data to be analyzed, the result score and the information analysis fee; A display module, for displaying each of the artificial intelligence models according to the information analysis cost, the result score and the cost performance score, for user selection; The target information analysis result display module is used to determine the hidden information analysis result of the artificial intelligence model selected by the user as the target information analysis result and display the target information analysis result.

7. The information analysis system based on artificial intelligence and big data according to claim 1, characterized in that: The result score acquisition module is used to obtain the result score through the following formula: Among them, S is the result score, k is the total number of hidden information analysis results, X i is the result data of the i-th hidden information analysis result, The average result data for the hidden information analysis results.

8. The information analysis system based on artificial intelligence and big data according to claim 1, characterized in that: The cost performance rating acquisition module includes: A fee weight acquisition submodule is used to acquire the fee weight of each artificial intelligence model according to the result score; wherein the smaller the result score, the smaller the fee weight; The cost performance score acquisition submodule is used to obtain the cost performance score of each artificial intelligence model based on the information analysis cost, the cost weight and the data volume of the big data to be analyzed.

9. The information analysis system based on artificial intelligence and big data according to claim 3, characterized in that: The cost performance rating acquisition submodule includes: A cost value acquisition submodule, used to analyze the cost and the cost weight according to the information to obtain the cost value of each artificial intelligence model; The value and data volume calculation submodule is used to obtain the cost performance score according to the cost value and the data volume.

10. The information analysis system based on artificial intelligence and big data according to claim 1, characterized in that: The target information analysis result display module is used to display each artificial intelligence model in an ascending order according to the information analysis cost; or, to display each artificial intelligence model in an ascending order according to the result score; or, to display each artificial intelligence model in an ascending order according to the cost-performance ratio score.

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