Asset data filtering method, device, electronic device and storage medium

Abstract

The embodiments of the present application provide a filtering method, device, electronic device and storage medium for asset data, which determines each asset data to be filtered in an asset database, and multiple filtering orders for each asset data; performs different filtering processes on each asset data in different filtering orders according to a preset filtering target to obtain multiple filtering results; determines the optimal filtering result among the multiple filtering results according to the data dimension weight of the asset data, and marks the asset data in the asset database according to the optimal filtering result. Compared with the prior art, the asset data marked by such a filtering method optimizes the distribution of the asset data, and there is no need to manually adjust the result. The filtering efficiency of the asset data is high and the process is simple.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, electronic device and storage medium for filtering asset data. Background Art

[0002] Asset-backed securities (ABS) are used to achieve corporate financing by issuing asset-backed securities with the future cash flow generated by the underlying assets as repayment support. Factoring is the abbreviation of factoring, which means that the seller transfers its current or future accounts receivable generated by the goods sales / service contracts signed with the buyer to the factor.

[0003] In the process of factoring ABS, it is necessary to import the asset data into the asset pool of ABS, and filter the asset data in the asset pool according to the preset filtering target to obtain the filtering result. The filtering result will be used to mark the asset data in the asset pool for subsequent use.

[0004] However, since the data amount of a single asset of factoring ABS is large, the results obtained when filtering assets are highly random, and the filtering results are often not optimal. At this time, it is necessary to reprocess the filtering results through manual adjustment, and the processing efficiency of the entire filtering process is low. Summary of the invention

[0005] The embodiments of the present application provide a method, device, electronic device and storage medium for filtering asset data, so as to provide a more efficient filtering process for asset data in the process of factoring ABS.

[0006] On the one hand, the present application provides a method for filtering asset data, comprising:

[0007] Determine each asset data to be filtered in the asset database, and multiple filtering orders for each asset data;

[0008] According to the preset filtering target, the asset data are subjected to different filtering processes in different filtering orders to obtain multiple filtering results;

[0009] According to the data dimension weights of the asset data, an optimal filtering result is determined among the multiple filtering results, and the asset data in the asset database is marked according to the optimal filtering result.

[0010] In an optional embodiment, multiple filtering orders of each asset data are determined, including:

[0011] Each asset data is arranged and processed in a preset manner to obtain the multiple filtering sequences; wherein the preset manner includes one or more of multiple sequential arrangement processes and multiple non-sequential arrangement processes.

[0012] In an optional embodiment, the asset data are subjected to different filtering processes in different filtering orders according to the preset filtering targets to obtain multiple filtering results, including:

[0013] For any filtering order of each asset data, a distributed processing method is used to filter each asset data under the filtering order to obtain a filtering result under the filtering order.

[0014] In an optional embodiment, the distributed processing method is used to filter the asset data in the filtering order to obtain the filtering results in the filtering order, including:

[0015] Based on the filtering order, establish the filtering processing tasks corresponding to each asset data and determine the corresponding task priority; wherein the task priority of the filtering processing task is determined according to the filtering order

[0016] According to the task priorities of the filtering processing tasks, the multiple filtering processing tasks are processed in sequence to obtain the filtering results of the asset data in the filtering order.

[0017] In an optional embodiment, the processing of the plurality of filtering processing tasks in sequence according to the task priorities of the filtering processing tasks to obtain filtering results of the asset data in the filtering order includes:

[0018] Determining the processing status of each filtering processing task;

[0019] Selecting the filtering processing task with the highest task priority from the filtering processing tasks in the processing status of pending, assigning the filtering processing task to any idle processing server for processing, and updating the processing status of the filtering processing task;

[0020] Repeat the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks whose processing status is pending, until the processing status of all filtering processing tasks is processed, and the processing structure of each filtering processing task constitutes the filtering result of each asset data in the filtering order.

[0021] In an optional embodiment, the filtering method further includes:

[0022] Determine the conflict relationship between each filtering result and the optimal filtering result; wherein the conflict relationship is used to indicate that the asset data constituting the two filtering results overlap;

[0023] The filtering results that do not conflict with the optimal filtering result are retained.

[0024] In an optional embodiment, the filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result status of an asset data;

[0025] Accordingly, determining the conflict relationship between each filtering result and the optimal filtering result includes:

[0026] Compare the binary character bits of each filtering result with the binary character bits of the optimal filtering result bit by bit;

[0027] According to the bit-by-bit comparison result, the conflict relationship between each filtering result and the optimal filtering result is determined.

[0028] In a second aspect, the present application provides a device for filtering asset data, comprising:

[0029] A processing module, used for determining each asset data to be filtered in the asset database, and multiple filtering orders for each asset data;

[0030] A filtering module, used to perform different filtering processes on the asset data in different filtering orders according to preset filtering targets, and obtain multiple filtering results;

[0031] The marking module is used to determine the optimal filtering result among the multiple filtering results according to the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

[0032] In an optional embodiment, when determining the multiple filtering orders of each asset data, the processing module is specifically used to:

[0033] Each asset data is arranged and processed in a preset manner to obtain the multiple filtering sequences; wherein the preset manner includes one or more of multiple sequential arrangement processes and multiple non-sequential arrangement processes.

[0034] In an optional embodiment, the filtering module, when performing different filtering processes on the asset data in different filtering orders according to the preset filtering target to obtain multiple filtering results, is specifically used to:

[0035] For any filtering order of each asset data, a distributed processing method is used to filter each asset data under the filtering order to obtain a filtering result under the filtering order.

[0036] In an optional embodiment, when the filtering module performs filtering processing on each asset data in the filtering order in a distributed processing manner to obtain the filtering result in the filtering order, it is specifically used to:

[0037] Based on the filtering order, establish the filtering processing tasks corresponding to each asset data and determine the corresponding task priority; wherein the task priority of the filtering processing task is determined according to the filtering order

[0038] According to the task priorities of the filtering processing tasks, the multiple filtering processing tasks are processed in sequence to obtain the filtering results of the asset data in the filtering order.

[0039] In an optional embodiment, when the filtering module processes the multiple filtering processing tasks in sequence according to the task priorities of the filtering processing tasks to obtain the filtering results of the asset data in the filtering order, it is specifically used to:

[0040] Determining the processing status of each filtering processing task;

[0041] Selecting the filtering processing task with the highest task priority from the filtering processing tasks in the processing status of pending, assigning the filtering processing task to any idle processing server for processing, and updating the processing status of the filtering processing task;

[0042] Repeat the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks whose processing status is pending, until the processing status of all filtering processing tasks is processed, and the processing structure of each filtering processing task constitutes the filtering result of each asset data in the filtering order.

[0043] In an optional embodiment, the marking module is further used for:

[0044] Determine the conflict relationship between each filtering result and the optimal filtering result; wherein the conflict relationship is used to indicate that the asset data constituting the two filtering results overlap;

[0045] The filtering results that do not conflict with the optimal filtering result are retained.

[0046] In an optional embodiment, the filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result status of an asset data;

[0047] The marking module is specifically used for:

[0048] The binary character bits of each filtering result are compared bit by bit with the binary character bits of the optimal filtering result; and the conflict relationship between each filtering result and the optimal filtering result is determined according to the bit by bit comparison result.

[0049] In a third aspect, the present application provides an electronic device, comprising: at least one processor and a memory;

[0050] The memory stores computer-executable instructions;

[0051] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the filtering method as described in the first aspect.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When a processor executes the computer-executable instructions, the filtering method of the first aspect is implemented.

[0053] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the filtering method of the first aspect when executed by a processor.

[0054] The embodiments of the present application provide a filtering method, device, electronic device and storage medium for asset data, which determines each asset data to be filtered in an asset database, and multiple filtering orders for each asset data; performs different filtering processes on each asset data in different filtering orders according to a preset filtering target to obtain multiple filtering results; determines the optimal filtering result among the multiple filtering results according to the data dimension weight of the asset data, and marks the asset data in the asset database according to the optimal filtering result. Compared with the prior art, the asset data marked by such a filtering method optimizes the distribution of the asset data, and there is no need to manually adjust the result. The filtering efficiency of the asset data is high and the process is simple. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0056] Figure 1 A schematic diagram of a network architecture on which this application is based;

[0057] Figure 2 It is a flowchart of a method for filtering asset data provided by this application;

[0058] Figure 3 is a flowchart of another method for filtering asset data provided by the present application;

[0059] Figure 4 A schematic diagram of the structure of a device for filtering asset data provided in an embodiment of the present application;

[0060] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0061] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0062] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of systems and methods consistent with some aspects of the present application as detailed in the appended claims.

[0063] Asset-Backed Securities (ABS) uses the future cash flows of underlying assets as repayment support and issues asset-backed securities through structured design to achieve corporate financing.

[0064] In the process of factoring ABS, it is necessary to import the asset data into the asset pool of ABS, and filter the asset data in the asset pool according to the preset filtering target to obtain the filtering result. The filtering result will be used to mark the asset data in the asset pool for subsequent use.

[0065] However, since the data amount of a single asset of factoring ABS is large, the results obtained when filtering assets are highly random, and the filtering results are often not optimal.

[0066] For example, taking the asset pool including asset data A (800,000), asset data B (600,000), asset data C (400,000) and asset data D (500,000), if the filtering target is to select asset data with a total amount of 1 million and mark the data, when the existing filtering method is used for filtering, the amount of each asset data will be superimposed in the order of asset data A-asset data B-asset data C-asset data D.

[0067] This will result in that after selecting asset data A, the amount will be exceeded due to the superposition of any one of asset data B, asset data C, and asset data D. Therefore, in order to ensure that the superposition amount meets the filtering conditions, the existing filtering method will give a filtering result that only selects asset data A as the marking target. However, it is obvious that based on the above asset data, the combination of asset data B (600,000) and asset data C (400,000) can better meet the filtering target, that is, the filtering result given by the existing filtering method is often not the most preferred result.

[0068] Therefore, in order to avoid this situation, in the prior art, when the filtering results are obtained, it is necessary to manually readjust the filtering results to use the combination of asset data B (600,000) and asset data C (400,000) as the final filtering result.

[0069] Obviously, the accuracy and efficiency of filtering processing using this filtering method cannot meet the actual usage requirements, especially when the asset pool includes a large amount of asset data. It takes a lot of manpower to adjust the filtering results, and the filtering efficiency is very low and the cost is high.

[0070] In response to the above problems, the solution on which the present application is based is to determine the asset data to be filtered in the asset database, as well as multiple filtering orders for each asset data; perform different filtering processes on the asset data in different filtering orders according to preset filtering targets to obtain multiple filtering results; determine the optimal filtering result from the multiple filtering results based on the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

[0071] Compared with the existing technology, the asset data obtained by marking using this filtering method optimizes the distribution of asset data, and there is no need to manually adjust the results. The filtering efficiency of asset data is high, which greatly reduces the time and financial costs of labor. The process is simple

[0072] The method provided in this application will be described below in combination with different implementation modes.

[0073] refer to Figure 1 , Figure 2 A schematic diagram of a network architecture based on this application, Figure 2 The network architecture shown may specifically include a business system 1 and a server 2 .

[0074] Among them, the business system 1 specifically refers to a service system that provides ABS front-end business, which can be specifically set up in a business server in the cloud to provide business support for ABS front-end business and generate business-related asset data.

[0075] The server 2 specifically refers to a hardware device set up in the cloud for executing the asset data filtering method of the present application. The server 2 can establish a communication connection with the business system 1 through the network to achieve data interaction with the business system 1.

[0076] After generating the asset data, the business system 1 may send the asset data to the server 2. After receiving the asset data, the server 2 stores it in the asset database and performs corresponding filtering processing according to the asset data filtering method provided in this application.

[0077] Embodiment 1

[0078] Figure 2 This is a flowchart of a method for filtering asset data provided by this application, such as Figure 2 As shown, the method includes:

[0079] Step 101: determine each asset data to be filtered in the asset database, and multiple filtering orders for each asset data.

[0080] Step 102: Perform different filtering processes on the asset data in different filtering orders according to preset filtering targets to obtain multiple filtering results.

[0081] Step 103: Determine an optimal filtering result from the multiple filtering results according to the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

[0082] It should be noted that the asset data filtering method provided in the present application can be specifically applied to an asset data filtering device, which can be specifically arranged in Figure 1 In server 2 shown.

[0083] The embodiment of the present application provides a method for filtering asset data. Completely different from the prior art, in the filtering method provided by the present application, it is first necessary to determine the asset data to be filtered and the multiple filtering orders of each asset data, and then perform multiple filtering processes on the asset data to be filtered based on different filtering orders.

[0084] Specifically, for asset filtering, you generally need to set a filtering target first, as mentioned earlier: the asset database includes asset data A (800,000), asset data B (600,000), asset data C (400,000), asset data D (500,000), etc. The filtering target can be "select asset data with a total amount of 1 million."

[0085] Based on the filtering target, the filtering device will first select the asset data to be filtered from the asset database, such as selecting asset data A (800,000), asset data B (600,000), asset data C (400,000), and asset data D (500,000) as the asset data to be filtered.

[0086] Then determine the filtering order of the asset data to be filtered, such as: ABCD as one filtering order, CBDA as another filtering order, DCBA as another filtering order, but not limited to this.

[0087] Generally speaking, based on the same filtering rules, changing the filtering order of each asset data will make the data composition of the filtering results different. For example, under the filtering order of ABCD, the filtering result is A; under the filtering order of CBDA, the filtering results are B and C; and under the filtering order of DCBA, the filtering results are D and C. The more filtering results there are, the more conducive it is to obtaining the optimal filtering result.

[0088] Therefore, in the aforementioned step of determining the filtering order, it is necessary to sort the asset data as much as possible to obtain as many sorting combinations of the asset data as possible, so that different filtering results can be obtained by filtering according to different sortings.

[0089] Optionally, in order to obtain as many different filtering results as possible, multiple sorting rules will be used to determine the filtering order: each asset data is arranged and processed in a preset manner to obtain the multiple filtering orders; wherein the preset method includes one or more of multiple sequential arrangement processing and multiple non-sequential arrangement processing.

[0090] Specifically, the various arrangements may include sequential arrangements, that is, arrangements in ascending or descending order, such as ascending arrangement of ABCD, or descending arrangement of DCBA. The various arrangements may also include non-sequential arrangements, such as ACDB, CABD, etc., which are not ascending lists or descending arrangements.

[0091] By performing multiple arrangement processes on each asset data, as many sortings of each asset data as possible can be obtained, and each sorting will be used as a filtering order to perform filtering processing.

[0092] Then, the filtering device performs different filtering processes on the asset data in different filtering orders according to the preset filtering targets to obtain multiple filtering results.

[0093] In the process of filtering asset data according to any filtering order, in order to improve processing efficiency, distributed processing can be used for processing.

[0094] That is to say, optionally, for any filtering order of each asset data, a distributed processing method is used to filter each asset data under the filtering order to obtain a filtering result under the filtering order.

[0095] Specifically, when processing each asset data based on the filtering order, a corresponding filtering processing task can be established for each asset data, and in order to indicate the filtering order, the task priority of each filtering processing task needs to be set when establishing the filtering processing task. That is, the processing device can establish the filtering processing task corresponding to each asset data based on the filtering order and determine the corresponding task priority; wherein the task priority of the filtering processing task is determined according to the filtering order.

[0096] Taking the filtering order as DCBA as an example, for each asset data, a filtering task is established, that is, filtering task D, filtering task C, filtering task B, and filtering task A. Then, because the filtering order is DCBA, the task priority of each filtering task is set, that is, filtering task D is the highest, filtering task C is the second, filtering task B is the third, and filtering task A is the lowest.

[0097] Then, the processing device will process the multiple filtering processing tasks in sequence according to the task priorities of the filtering processing tasks to obtain the filtering results of the asset data in the filtering order.

[0098] Specifically, for each filtering task, the processing device also stores the task processing status, which is used to indicate the current processing stage of the filtering task, such as unprocessed, processed, processing, etc. The filtering device will allocate filtering tasks to each processing server according to the task priority and processing status of each filtering task, so that the processing server performs filtering and outputs filtering results.

[0099] The filtering device first determines the processing status of each filtering processing task; selects the filtering processing task with the highest task priority from the filtering processing tasks with a processing status of pending, allocates the filtering processing task to any idle processing server for processing and updates the processing status of the filtering processing task; repeats the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks with a processing status of pending, until the processing status of all filtering processing tasks is processed, and the processing structure of each filtering processing task constitutes the filtering result of each asset data in the filtering order.

[0100] Finally, after obtaining multiple filtering results, the filtering device will also determine the optimal filtering result among the multiple filtering results based on the data dimension weights of the asset data, and mark the asset data in the asset database based on the optimal filtering result.

[0101] Specifically, the results of the filtering tasks processed by each processing server will be recorded in a detailed table in real time, and finally a detailed table including all the filtering results will be formed. Then, based on the preset data dimension weights of the asset data, the quality of the filtering results is analyzed, and the best filtering result is selected. For example, the weight of the data dimension of the principal to be repaid is 0.8, and the weight of the data dimension of the rate of return is 0.2.

[0102] For the filtering result A, the value of the principal to be repaid is 10000, and the value of the rate of return is 0.8. Using the weight, the score of the filtering result A is 10000*0.8+0.8*0.2=8000.16.

[0103] For the filtering result B, the value of the principal to be repaid is 10000, and the yield value is 0.81. Using the weight, the score of the filtering result B is 10000*0.8+0.81*0.2=8000.162.

[0104] From the above scoring results, it can be seen that under the current weight configuration, filtering result B is the optimal filtering result. At this time, the asset data in the asset database will be marked according to the asset data in filtering result B.

[0105] exist Figure 2 Based on the embodiment shown, Figure 3 FIG. 4 is a flow chart of another method for filtering asset data provided by the present application. Figure 3 As shown, the method includes:

[0106] Step 201: determine each asset data to be filtered in the asset database, and multiple filtering orders for each asset data.

[0107] Step 202: Perform different filtering processes on the asset data in different filtering orders according to preset filtering targets to obtain multiple filtering results.

[0108] Step 203: Determine an optimal filtering result from the multiple filtering results according to the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

[0109] Step 204: determining the conflict relationship between each filtering result and the optimal filtering result;

[0110] Step 205: retain the filtering results that do not have a conflict relationship with the optimal filtering result, wherein the conflict relationship is used to indicate that the asset data constituting the two filtering results overlap.

[0111] In actual scenarios, in order to avoid repeated asset tagging, the same asset data can only be marked once. That is, when asset data A is used as one of the asset data in the filtering result B and is marked in the asset database, the next time the asset data is filtered, the asset data A will not be used as the asset data to be filtered and will not enter the filtering process.

[0112] Therefore, different from the above-mentioned embodiment, after the optimal filtering result is selected and the asset database is marked, it is also necessary to determine the filtering results that conflict with the optimal filtering result and abolish them.

[0113] The conflict relationship means that when two filtering results both include the same asset data, there is a conflict relationship between the two filtering results; when the two filtering results do not include the same asset data, there is no conflict relationship between the two filtering results.

[0114] For example, if asset data A is selected by filter result A and is also selected by filter result B, it is considered that filter result A and filter result B have a conflicting relationship.

[0115] In order to quickly determine whether there is a conflict relationship between the filtering results, in the present application, a binary character bit can be used to represent each filtering result.

[0116] Specifically, if there are 20 asset data in total, 20 character bits can be set to represent the hit results of each asset data, and the character values ​​of the 20 character bits are combined to form the filtering result. In other words, for a filtering result, it can be represented by only 20 bytes, which greatly saves cache.

[0117] Accordingly, when determining the conflict relationship, the binary character bits of each filtering result may be compared bit by bit with the binary character bits of the optimal filtering result; and the conflict relationship between each filtering result and the optimal filtering result may be determined based on the bit by bit comparison result.

[0118] For example, taking [asset data A, asset data B, asset data C, asset data D] as all asset data, when asset data A and asset data C are selected in filter result A, filter result A can be expressed as [1,0,1,0], and when asset data A and asset data D are selected in filter result B, filter result A can be expressed as [1,0,0,1]; 1 indicates that the asset data is hit, and 0 indicates that the asset data is not hit.

[0119] When determining the conflict relationship, a comparison can be performed based on each binary character position, and it can be finally determined that both of them hit the asset data A, that is, there is a conflict relationship between the two.

[0120] In this way, the conflict relationship between filtering results can be quickly determined while occupying a small cache, avoiding repeated labeling of assets.

[0121] The embodiment of the present application provides a method for filtering asset data, by determining each asset data to be filtered in an asset database, and multiple filtering orders for each asset data; performing different filtering processes on each asset data in different filtering orders according to a preset filtering target to obtain multiple filtering results; determining the optimal filtering result among the multiple filtering results according to the data dimension weight of the asset data, and marking the asset data in the asset database according to the optimal filtering result. Compared with the prior art, the asset data marked by such a filtering method optimizes the distribution of the asset data, and there is no need to manually adjust the result, the filtering efficiency of the asset data is high, and the process is simple.

[0122] Embodiment 2

[0123] Corresponding to the asset data filtering method of the above embodiment, Figure 4 A structural diagram of a device for filtering asset data provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the device for filtering asset data includes: a processing module 10 , a filtering module 20 and a marking module 30 .

[0124] The processing module 10 is used to determine each asset data to be filtered in the asset database, and multiple filtering orders for each asset data;

[0125] The filtering module 20 is used to perform different filtering processes on the asset data in different filtering orders according to the preset filtering targets to obtain multiple filtering results;

[0126] The marking module 30 is used to determine the optimal filtering result among the multiple filtering results according to the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

[0127] In an optional embodiment, when determining the multiple filtering orders of each asset data, the processing module 10 is specifically used to:

[0128] The asset data are randomly arranged to obtain the multiple filtering orders.

[0129] In an optional embodiment, the filtering module 20, when performing different filtering processes on the asset data in different filtering orders according to the preset filtering target to obtain multiple filtering results, is specifically used to:

[0130] For any filtering order of each asset data, a distributed processing method is used to filter each asset data under the filtering order to obtain a filtering result under the filtering order.

[0131] In an optional embodiment, the filtering module 20 performs filtering processing on each asset data in the filtering order in a distributed processing manner to obtain the filtering result in the filtering order, specifically for:

[0132] Based on the filtering order, establish the filtering processing tasks corresponding to each asset data and determine the corresponding task priority; wherein the task priority of the filtering processing task is determined according to the filtering order

[0133] According to the task priorities of the filtering processing tasks, the multiple filtering processing tasks are processed in sequence to obtain the filtering results of the asset data in the filtering order.

[0134] In an optional embodiment, when the filtering module 20 processes the multiple filtering processing tasks in sequence according to the task priorities of the filtering processing tasks and obtains the filtering results of the asset data in the filtering order, it is specifically used to:

[0135] Determining the processing status of each filtering processing task;

[0136] Selecting the filtering processing task with the highest task priority from the filtering processing tasks in the processing status of pending, assigning the filtering processing task to any idle processing server for processing, and updating the processing status of the filtering processing task;

[0137] Repeat the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks whose processing status is pending, until the processing status of all filtering processing tasks is processed, and the processing structure of each filtering processing task constitutes the filtering result of each asset data in the filtering order.

[0138] In an optional embodiment, the marking module 30 is further used for:

[0139] Determining the conflict relationship between each filtering result and the optimal filtering result;

[0140] The filtering results that do not conflict with the optimal filtering result are retained.

[0141] In an optional embodiment, the filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result status of an asset data;

[0142] The marking module 30 is specifically used for:

[0143] The binary character bits of each filtering result are compared bit by bit with the binary character bits of the optimal filtering result; and the conflict relationship between each filtering result and the optimal filtering result is determined according to the bit by bit comparison result.

[0144] The embodiment of the present application provides a filtering device for asset data, which determines each asset data to be filtered in an asset database, and multiple filtering orders for each asset data; performs different filtering processes on each asset data in different filtering orders according to a preset filtering target to obtain multiple filtering results; determines the optimal filtering result among the multiple filtering results according to the data dimension weight of the asset data, and marks the asset data in the asset database according to the optimal filtering result. Compared with the prior art, the asset data marked by such a filtering method optimizes the distribution of the asset data, and there is no need to manually adjust the result. The filtering efficiency of the asset data is high and the process is simple.

[0145] Embodiment 3

[0146] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 5 As shown, an embodiment of the present invention further provides an electronic device 1400, including: a memory 1401, a processor 1402 and a computer program.

[0147] The computer program is stored in the memory 1401 and is configured to be executed by the processor 1402 to implement the method for processing a question-and-answer session provided by any embodiment of the present invention. The relevant description can be understood by referring to the relevant descriptions and effects corresponding to the steps in the accompanying drawings, and no further details are given here.

[0148] In this embodiment, the memory 1401 and the processor 1402 are connected via a bus.

[0149] Embodiment 4

[0150] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor to implement the asset data filtering method provided by any embodiment of the present invention.

[0151] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0152] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0153] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0154] The program code for implementing the method of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable question-answering system, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0155] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, system, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0156] In addition, the present application provides a computer program product, including a computer program, which implements the above-mentioned asset data filtering method when executed by a processor.

[0157] In addition, although each operation is described in a specific order, this should be understood as requiring such operation to be performed in the specific order shown or in a sequential order, or requiring that all illustrated operations should be performed to obtain desired results. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation can also be implemented in multiple implementations individually or in any suitable sub-combination mode.

[0158] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A method for filtering asset data, characterized in that: include: Determine each asset data to be filtered in the asset database, and multiple filtering orders for each asset data; According to the preset filtering target, the asset data are subjected to different filtering processes in different filtering orders to obtain multiple filtering results; According to the data dimension weights of the asset data, an optimal filtering result is determined among the multiple filtering results, and the asset data in the asset database is marked according to the optimal filtering result.

2. The filtering method according to claim 1, characterized in that: Determines multiple filter orders for each asset data, including: Arrange and process each asset data in a preset manner to obtain the multiple filtering sequences; wherein the preset manner includes one or more of multiple sequential arrangement processes and multiple non-sequential arrangement processes.

3. The filtering method according to claim 1, characterized in that: The method further comprises performing different filtering processes on the asset data in different filtering orders according to the preset filtering targets to obtain multiple filtering results, including: For any filtering order of each asset data, a distributed processing method is used to filter each asset data under the filtering order to obtain a filtering result under the filtering order.

4. The filtering method according to claim 3, characterized in that: The distributed processing method is used to filter the asset data in the filtering order to obtain the filtering results in the filtering order, including: Based on the filtering order, establish filtering processing tasks corresponding to each asset data and determine corresponding task priorities; wherein the task priorities of the filtering processing tasks are determined according to the filtering order; According to the task priorities of the filtering processing tasks, the multiple filtering processing tasks are processed in sequence to obtain the filtering results of the asset data in the filtering order.

5. The filtering method according to claim 4, characterized in that: The step of processing the plurality of filtering processing tasks in sequence according to the task priorities of the filtering processing tasks to obtain filtering results of the asset data in the filtering order includes: Determining the processing status of each filtering processing task; Selecting the filtering processing task with the highest task priority from the filtering processing tasks with a processing status of pending, assigning the filtering processing task to any idle processing server for processing, and updating the processing status of the filtering processing task; Repeat the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks whose processing status is pending, until the processing status of all filtering processing tasks is processed, and the processing structure of each filtering processing task constitutes the filtering result of each asset data in the filtering order.

6. The filtering method according to any one of claims 1 to 5, characterized in that: Also includes: Determine the conflict relationship between each filtering result and the optimal filtering result; wherein the conflict relationship is used to indicate that the asset data constituting the two filtering results overlap; The filtering results that do not conflict with the optimal filtering result are retained.

7. The filtering method according to claim 6, characterized in that: The filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result status of an asset data; Accordingly, determining the conflict relationship between each filtering result and the optimal filtering result includes: Compare the binary character bits of each filtering result with the binary character bits of the optimal filtering result bit by bit; According to the bit-by-bit comparison result, the conflict relationship between each filtering result and the optimal filtering result is determined.

8. A device for filtering asset data, characterized in that: include: A processing module, used for determining each asset data to be filtered in the asset database, and multiple filtering orders for each asset data; A filtering module, used to perform different filtering processes on the asset data in different filtering orders according to preset filtering targets, and obtain multiple filtering results; The marking module is used to determine the optimal filtering result among the multiple filtering results according to the data dimension weights of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

9. An electronic device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the filtering method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the processor executes the computer-executable instructions, the filtering method according to any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the filtering method according to any one of claims 1 to 7 is implemented.

Images