Comprehensive analysis system and method based on financial data

Abstract

The invention relates to the technical field of data analysis, in particular to a comprehensive analysis system and method based on financial data, and the system comprises a collection module which is used for setting collection logic and collecting financial data based on the collection logic; the creating module is used for creating financial data analysis dimension labels; the analysis module is used for calling the financial data acquired by the acquisition module, traversing the called financial data and analyzing the reading recommendation degree of each piece of financial data in the called financial data; according to the method and the system, the analysis dimension of the collected financial data is subjected to tagging processing, so that the user applying the system can provide financial data with relatively high reference value for the user applying the system based on tag selection, and reading recommendation degree analysis and queue processing on the financial data in the system; therefore, a user using the system can know financial stock market information more quickly, and more financial decisions with higher accuracy can be made.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a comprehensive analysis system and method based on financial data. Background Art

[0002] Financial data is the core information in the financial field, covering money supply such as M1, M2, interest rates, exchange rates, stock market indices, bond market data, commodity price indices and company financial reports. It reflects the operation of the financial market, is an important basis for market participants to make decisions, and is of great significance to economic development and resource allocation.

[0003] As for the financial stock market, due to the large number of stock types and issuers, the amount of stock market information is huge, and users cannot quickly and effectively find and read the required data.

[0004] To this end, we proposed a comprehensive analysis system and method based on financial data. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a comprehensive analysis system and method based on financial data, which solves the technical problems raised by the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] In a first aspect, a comprehensive analysis system based on financial data includes:

[0008] The collection module is used to set the collection logic and collect financial data based on the collection logic; the creation module is used to create the financial data analysis dimension label; the analysis module is used to retrieve the financial data collected by the collection module, traverse the retrieved financial data, and analyze the reading recommendation degree of each financial data in the retrieved financial data; the queue module is used to receive the reading recommendation degree of the financial data analyzed in the analysis module, and arrange the retrieved financial data based on the reading recommendation degree of the financial data; the retrieval module is used to obtain the arrangement result of the financial data in the queue module, retrieve the arranged financial data, and provide feedback to the system end user; the reset module is used to reset the system and run it again;

[0009] Among them, the retrieval module is connected to the mobile computer device held by the system end user through a wireless network, takes the mobile computer device held by the system end user as the feedback target, transmits the retrieved financial data to the mobile computer, and the system end user reads the retrieved financial data on the mobile computer.

[0010] Furthermore, the acquisition module is provided with submodules at the lower level, including:

[0011] A setting unit, used to set a corresponding time threshold for the collection module to collect financial data, and to feed back the set time threshold to the collection module;

[0012] A storage unit, used to receive the financial data collected by the collection module and store and process the financial data;

[0013] Among them, the collection module set in the setting unit runs the corresponding time threshold for collecting financial data, that is, the collection logic set in the collection module. The setting unit is manually controlled by the system end user, and executes the setting of the corresponding time threshold for the collection module to run the collection of financial data. The collection module is connected to the financial data output APP specified by the system end user through a wireless network, and data is interacted with the financial data output APP based on the wireless network. The financial data output APP is any stock-related application included in the application store installed on the current mobile phone or computer.

[0014] Furthermore, the financial data analysis dimension labels created in the creation module are derived from the financial data;

[0015] The financial data analysis dimension label is text information extracted from the financial data. When the financial data analysis dimension label is created, the text information is extracted from each group of financial data, and the same text information in the text information corresponding to each group of financial data is further identified. The identified same text information from two or more groups of financial data is used as the financial data analysis dimension label and stored in the creation module;

[0016] Among them, the financial data analysis dimension labels stored in the creation module are deleted or retained by the system-side users. The financial data analysis dimension labels stored in the creation module are words of no less than two characters and are all different. There are no less than three groups of financial data analysis dimension labels stored in the creation module.

[0017] Furthermore, the analysis module is internally provided with submodules, including:

[0018] A retrieving unit, used to retrieve the financial data stored in the storage unit;

[0019] In the operation phase of the retrieval unit, the system end user applies the retrieval unit to select one or more financial data analysis dimension tags in the creation module, and retrieves the financial data containing the selected financial data analysis dimension tags in the storage unit based on the selected financial data analysis dimension tags.

[0020] Furthermore, during the financial data collection phase, the collection module binds a distinguishing mark to the collected financial data, wherein the distinguishing mark is a digital serial number. After retrieving the financial data, the analysis module performs distinguishing processing on the retrieved financial data based on the distinguishing mark bound to the financial data. After completing the distinguishing processing on the financial data, the analysis operation of reading the recommendation degree of the financial data is further performed.

[0021] In the analysis phase of the financial data reading recommendation, the analysis module no longer performs the retrieval and traversal operations of the financial data.

[0022] Furthermore, the financial data is a K-line chart, and the analysis logic of the reading recommendation degree of the financial data in the analysis module is expressed as follows:

[0023]

[0024] Where: P(a) is the reading recommendation of financial data a; n is the set of intervals in the K-line chart corresponding to financial data a; dE is the absolute value of the difference between the entity lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(E i ,E i+1 ) is the maximum entity length value between interval i and interval i+1; dU is the absolute value of the difference between the upper shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(U i ,U i+1 ) is the maximum upper shadow length between interval i and interval i+1; dL is the absolute value of the difference between the lower shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(L i ,L i+1 ) is the maximum length of the lower and upper shadows in interval i and interval i+1; q(max) i ,q(max) i+1 The maximum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; qmin i 、q(min) i+1 It is the minimum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; ω is the weight;

[0025] Here, the reading recommendation degree of each financial data is obtained based on the above formula.

[0026] Furthermore, the higher or lower the reading recommendation degree of financial data, the more reference value the financial data has, and vice versa. When the queue module arranges the retrieved financial data, it arranges the financial data in descending order based on the reading recommendation degree, so that the financial data with a high reading recommendation degree is arranged in front and the financial data with a low reading recommendation degree is arranged in the back.

[0027] Furthermore, the amount of financial data retrieved by the retrieval module is customized by the system end user, the source of the retrieved financial data is the front-most and the back-most financial data in the financial data queue, and the ratio of the front-most financial data to the back-most financial data in the retrieved financial data is 1:1. The reset module is internally provided with submodules, including:

[0028] A monitoring unit, used to monitor the running status of the calling module;

[0029] The monitoring unit runs in real time in the system, and after monitoring that the calling module runs and ends, it triggers the reset module to run.

[0030] Furthermore, the acquisition module is interactively connected to a setting unit and a storage unit at the lower level through a wireless network, the acquisition module is interactively connected to a creation module and an analysis module through a wireless network, the analysis module is interactively connected to a retrieval unit through a wireless network, the retrieval unit is interactively connected to the storage unit through a wireless network, the analysis module is interactively connected to a queue module, a retrieval module and a reset module through a wireless network, and the reset module is interactively connected to a monitoring unit through a wireless network.

[0031] In a second aspect, a comprehensive analysis method based on financial data comprises the following steps:

[0032] Step 1: Set the financial data collection logic and apply the financial data collection logic to collect financial data;

[0033] Step 2: Store the collected financial data, traverse the stored financial data, extract text information from the stored financial data, set the judgment logic of the financial data analysis dimension label, and select text from the extracted text information as the financial data analysis dimension label based on the judgment logic;

[0034] Step 3: According to the financial data stored in the dimension tag of financial data analysis, traverse the retrieved financial data and analyze the reading recommendation degree of each financial data;

[0035] Step 4: Generate a descending queue based on the recommendation degree of financial data reading, retrieve financial data from the queue and feed it back to the user end;

[0036] Step 5: Refresh execution of the step.

[0037] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0038] The present invention provides a comprehensive analysis system and method based on financial data. Based on the operation of the system, by labeling the analysis dimensions of the collected financial data, users who apply the system can provide users who apply the system with financial data with high reference value based on label selection, and the reading recommendation degree analysis and queue processing of the financial data in the system, so as to help users who apply the system understand financial stock market information more quickly and make more financial decisions with higher accuracy. At the same time, a comprehensive analysis method based on financial data is used to provide further operation data support for the above system, ensuring that the technical solution composed of the above system and method can be better applied to financial data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 It is a structural diagram of a comprehensive analysis system based on financial data;

[0041] Figure 2 The figure is a flowchart of a comprehensive analysis method based on financial data. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] The present invention will be further described below in conjunction with the embodiments.

[0044] Embodiment 1:

[0045] A comprehensive analysis system based on financial data in this embodiment, such as Figure 1 As shown, including:

[0046] The collection module is used to set the collection logic and collect financial data based on the collection logic;

[0047] The acquisition module is equipped with submodules, including:

[0048] A setting unit, used to set a corresponding time threshold for the collection module to collect financial data, and to feed back the set time threshold to the collection module;

[0049] A storage unit, used to receive the financial data collected by the collection module and store and process the financial data;

[0050] The collection module set in the setting unit runs the corresponding time threshold for collecting financial data, that is, the collection logic set in the collection module. The setting unit is manually controlled by the system end user to execute the setting of the corresponding time threshold for the collection module to run and collect financial data. The collection module is connected to the financial data output APP specified by the system end user through the wireless network, and data is exchanged with the financial data output APP based on the wireless network. The financial data output APP is any stock-related application included in the application store installed on the current mobile phone or computer;

[0051] Create a module for creating dimension labels for financial data analysis;

[0052] An analysis module is used to retrieve the financial data collected by the collection module, traverse the retrieved financial data, and analyze the reading recommendation degree of each financial data in the retrieved financial data;

[0053] The analysis module is internally provided with submodules, including:

[0054] A retrieving unit, used to retrieve the financial data stored in the storage unit;

[0055] In the operation phase of the retrieval unit, the system end user applies the retrieval unit to select one or more financial data analysis dimension tags in the creation module, and retrieves the financial data containing the selected financial data analysis dimension tags from the storage unit based on the selected financial data analysis dimension tags;

[0056] A queue module, used to receive the financial data reading recommendation degree analyzed by the analysis module, and arrange the retrieved financial data based on the financial data reading recommendation degree;

[0057] The retrieval module is used to obtain the arrangement results of the financial data in the queue module, retrieve the arranged financial data, and provide feedback to the system end user;

[0058] Reset module, used to reset the system and run it again;

[0059] The retrieval module is connected to the mobile computer device held by the system end user through a wireless network, takes the mobile computer device held by the system end user as a feedback target, transmits the retrieved financial data to the mobile computer, and the system end user reads the retrieved financial data on the mobile computer;

[0060] Financial data is a K-line chart. The analysis logic of the reading recommendation of financial data in the analysis module is expressed as follows:

[0061]

[0062] Where: P(a) is the reading recommendation of financial data a; n is the set of intervals in the K-line chart corresponding to financial data a; dE is the absolute value of the difference between the entity lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(E i ,E i+1 ) is the maximum entity length value between interval i and interval i+1; dU is the absolute value of the difference between the upper shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(U i ,U i+1 ) is the maximum upper shadow length between interval i and interval i+1; dL is the absolute value of the difference between the lower shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(L i ,L i+1 ) is the maximum length of the lower and upper shadows in interval i and interval i+1; q(max) i ,q(max) i+1 The maximum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; qmin i 、q(min) i+1 It is the minimum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; ω is the weight;

[0063] Among them, based on the above formula, the reading recommendation degree of each financial data is obtained, and the weight ω=1 / 3;

[0064] The number of financial data retrieved by the retrieval module is customized by the system end user. The source of the retrieved financial data is the frontmost and the last financial data in the financial data queue, and the ratio of the front financial data to the back financial data in the retrieved financial data is 1:1. The reset module is internally provided with submodules, including:

[0065] A monitoring unit, used to monitor the running status of the calling module;

[0066] The monitoring unit runs in real time in the system, and after monitoring that the calling module runs and ends, it triggers the reset module to run;

[0067] The acquisition module is interactively connected to a setting unit and a storage unit at its lower level through a wireless network, the acquisition module is interactively connected to a creation module and an analysis module through a wireless network, the analysis module is interactively connected to a retrieval unit through a wireless network, the retrieval unit is interactively connected to the storage unit through a wireless network, the analysis module is interactively connected to a queue module, a retrieval module and a reset module through a wireless network, and the reset module is interactively connected to a monitoring unit through a wireless network.

[0068] In this embodiment, the setting unit runs to set the corresponding time threshold of the collection module to run the collection of financial data, and feeds back the set time threshold to the collection module. The collection module collects financial data based on the collection logic. The storage unit receives the financial data collected by the collection module in real time, and stores and processes the financial data. The creation module further creates a financial data analysis dimension label. The analysis module post-operates to retrieve the financial data collected by the collection module, traverses the retrieved financial data, and analyzes the reading recommendation degree of each financial data in the retrieved financial data. The retrieval unit synchronously retrieves the financial data stored in the storage unit, and then the queue module receives the financial data reading recommendation degree analyzed in the analysis module, and arranges the retrieved financial data based on the financial data reading recommendation degree. The retrieval module further obtains the arrangement result of the financial data in the queue module, retrieves the arranged financial data, and feeds back to the system end user. Finally, the reset module resets the system and runs again.

[0069] Through the operation of the system in the above embodiment, financial data analysis technology is brought to the financial stock market, allowing users to quickly find the required financial data in massive financial data according to their own needs.

[0070] Embodiment 2:

[0071] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The comprehensive analysis system based on financial data in Example 1 is further described in detail:

[0072] The financial data analysis dimension labels created in the creation module are derived from the financial data;

[0073] The financial data analysis dimension label is text information extracted from the financial data. When creating the financial data analysis dimension label, the text information is extracted from each group of financial data, and the same text information in the text information corresponding to each group of financial data is further identified. The identified same text information from two or more groups of financial data is used as the financial data analysis dimension label and stored in the creation module;

[0074] Among them, the financial data analysis dimension labels stored in the creation module are deleted or retained by the system-side users. The financial data analysis dimension labels stored in the creation module are words of no less than two characters and are all different. There are no less than three groups of financial data analysis dimension labels stored in the creation module.

[0075] During the financial data collection phase of the collection module, the collected financial data are all bound with a distinguishing mark, which is a digital serial number. After retrieving the financial data, the analysis module distinguishes the retrieved financial data based on the distinguishing mark bound to the financial data. After the distinction processing of the financial data is completed, the analysis operation of the financial data reading recommendation degree is further performed;

[0076] In the analysis phase of the financial data reading recommendation, the analysis module no longer performs the retrieval and traversal operations of the financial data.

[0077] The higher or lower the reading recommendation degree of financial data, the more reference value the financial data has. Conversely, the lower the reference value of the financial data, the queue module arranges the retrieved financial data in descending order based on the reading recommendation degree of the financial data, so that the financial data with a high reading recommendation degree is arranged in front, and the financial data with a low reading recommendation degree is arranged in the back.

[0078] In this embodiment, through the above settings, further operation data support and operation logic limitation are provided for the system in Example 1, ensuring the stable operation of the system in Example 1 and serving the user's financial data query operation.

[0079] Embodiment 3:

[0080] In terms of specific implementation, based on Example 1, this example refers to Figure 2 The comprehensive analysis system based on financial data in Example 1 is further described in detail:

[0081] A comprehensive analysis method based on financial data, comprising the following steps:

[0082] Step 1: Set the financial data collection logic and apply the financial data collection logic to collect financial data;

[0083] Step 2: Store the collected financial data, traverse the stored financial data, extract text information from the stored financial data, set the judgment logic of the financial data analysis dimension label, and select text from the extracted text information as the financial data analysis dimension label based on the judgment logic;

[0084] Step 3: According to the financial data stored in the dimension tag of financial data analysis, traverse the retrieved financial data and analyze the reading recommendation degree of each financial data;

[0085] Step 4: Generate a descending queue based on the recommendation degree of financial data reading, retrieve financial data from the queue and feed it back to the user end;

[0086] Step 5: Refresh execution of the step.

[0087] In summary, the method in the above embodiment labels the analysis dimensions of the collected financial data, so that users of the system can provide financial data with high reference value based on label selection, reading recommendation analysis and queue processing of financial data in the system, so as to help users of the system understand financial stock market information more quickly and make more financial decisions with higher accuracy. At the same time, a comprehensive analysis method based on financial data is used to provide further operation data support for the above system, ensuring that the technical solution composed of the above system and method can be better applied to financial data analysis.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A comprehensive analysis system based on financial data, characterized in that: include: The collection module is used to set the collection logic and collect financial data based on the collection logic; The acquisition module is provided with submodules at the lower level, including: A setting unit, used to set a corresponding time threshold for the collection module to collect financial data, and feed back the set time threshold to the collection module; A storage unit, used to receive the financial data collected by the collection module and store and process the financial data; Among them, the collection module set in the setting unit runs the corresponding time threshold for collecting financial data, that is, the collection logic set in the collection module, the setting unit is manually controlled by the system end user, and executes the setting of the corresponding time threshold for the collection module to run and collect financial data, the collection module is connected to the financial data output APP specified by the system end user through the wireless network, and data is exchanged with the financial data output APP based on the wireless network, and the financial data output APP is any stock-related application included in the application store installed on the current mobile phone or computer; Create a module for creating dimension labels for financial data analysis; An analysis module is used to retrieve the financial data collected by the collection module, traverse the retrieved financial data, and analyze the reading recommendation degree of each financial data in the retrieved financial data; The financial data is a K-line chart, and the analysis logic of the reading recommendation degree of the financial data in the analysis module is expressed as follows: Where: P(a) is the reading recommendation of financial data a; n is the set of intervals in the K-line chart corresponding to financial data a; dE is the absolute value of the difference between the entity lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(E i ,E i+1 ) is the maximum entity length value between interval i and interval i+1; dU is the absolute value of the difference between the upper shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(U i ,U i+1 ) is the maximum upper shadow length between interval i and interval i+1; dL is the absolute value of the difference between the lower shadow lengths of the K-line segments in interval i and interval i+1 in the K-line chart; max(L i ,L i+1 ) is the maximum length of the lower and upper shadows in interval i and interval i+1; q(max) i ,q(max) i+1 The maximum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; qmin i 、q(min) i+1 It is the minimum length of the entity of the K-line segment in interval i and interval i+1 in the K-line chart; ω is the weight; Among them, based on the above formula, the reading recommendation degree of each financial data is obtained; A queue module, used to receive the financial data reading recommendation degree analyzed by the analysis module, and arrange the retrieved financial data based on the financial data reading recommendation degree; The retrieval module is used to obtain the arrangement results of the financial data in the queue module, retrieve the arranged financial data, and provide feedback to the system end user; Reset module, used to reset the system and run it again; Among them, the retrieval module is connected to the mobile computer device held by the system end user through a wireless network, takes the mobile computer device held by the system end user as the feedback target, transmits the retrieved financial data to the mobile computer, and the system end user reads the retrieved financial data on the mobile computer.

2. A comprehensive analysis system based on financial data according to claim 1, characterized in that: The financial data analysis dimension labels created in the creation module are derived from the financial data; The financial data analysis dimension label is text information extracted from the financial data. When the financial data analysis dimension label is created, the text information is extracted from each group of financial data, and the same text information in the text information corresponding to each group of financial data is further identified. The identified same text information from two or more groups of financial data is used as the financial data analysis dimension label and stored in the creation module; Among them, the financial data analysis dimension labels stored in the creation module are deleted or retained by the system end users. The financial data analysis dimension labels stored in the creation module are words of no less than two characters and are all different. There are no less than three groups of financial data analysis dimension labels stored in the creation module.

3. A comprehensive analysis system based on financial data according to claim 1, characterized in that: The analysis module is internally provided with submodules, including: A retrieving unit, used to retrieve the financial data stored in the storage unit; In the operation phase of the retrieval unit, the system end user applies the retrieval unit to select one or more financial data analysis dimension tags in the creation module, and retrieves the financial data containing the selected financial data analysis dimension tags in the storage unit based on the selected financial data analysis dimension tags.

4. A comprehensive analysis system based on financial data according to claim 1, characterized in that: During the financial data collection phase, the collection module binds a distinguishing mark to the collected financial data, and the distinguishing mark is a digital serial number. After retrieving the financial data, the analysis module distinguishes the retrieved financial data based on the distinguishing mark bound to the financial data. After the distinction processing is completed, the analysis operation of reading the recommendation degree of the financial data is further performed; In the analysis phase of the financial data reading recommendation, the analysis module no longer performs the retrieval and traversal operations of the financial data.

5. A comprehensive analysis system based on financial data according to claim 1, characterized in that: The higher or lower the reading recommendation degree of financial data, the more reference value the financial data has. Conversely, the lower the reference value of the financial data, the queue module arranges the retrieved financial data in descending order based on the reading recommendation degree of the financial data, so that the financial data with a high reading recommendation degree is arranged in front and the financial data with a low reading recommendation degree is arranged in the back.

6. A comprehensive analysis system based on financial data according to claim 1, characterized in that: The amount of financial data retrieved by the retrieval module is customized by the system end user. The source of the retrieved financial data is the front-most and the back-most financial data in the financial data queue, and the ratio of the front-most financial data to the back-most financial data in the retrieved financial data is 1:

1. The reset module is internally provided with submodules, including: A monitoring unit, used to monitor the running status of the calling module; The monitoring unit runs in real time in the system, and after monitoring that the calling module runs and ends, it triggers the reset module to run.

7. A comprehensive analysis system based on financial data according to claim 1, characterized in that: The acquisition module is interactively connected to a setting unit and a storage unit at the lower level through a wireless network, the acquisition module is interactively connected to a creation module and an analysis module through a wireless network, the analysis module is interactively connected to a retrieval unit through a wireless network, the retrieval unit is interactively connected to the storage unit through a wireless network, the analysis module is interactively connected to a queue module, a retrieval module and a reset module through a wireless network, and the reset module is interactively connected to a monitoring unit through a wireless network.

8. A comprehensive analysis method based on financial data, the method being an implementation method of a comprehensive analysis system based on financial data as claimed in any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: Set the financial data collection logic and apply the financial data collection logic to collect financial data; Step 2: Store the collected financial data, traverse the stored financial data, extract text information from the stored financial data, set the judgment logic of the financial data analysis dimension label, and select text from the extracted text information as the financial data analysis dimension label based on the judgment logic; Step 3: According to the financial data stored in the dimension tag of financial data analysis, traverse the retrieved financial data and analyze the reading recommendation degree of each financial data; Step 4: Generate a descending queue based on the recommendation degree of financial data reading, retrieve financial data from the queue and feed it back to the user end; Step 5: Refresh execution of the step.

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