CN114647503A

CN114647503A - Asset data filtering method and device, electronic equipment and storage medium

Info

Publication number: CN114647503A
Application number: CN202011518094.3A
Authority: CN
Inventors: 钞娜娜
Original assignee: Jingdong Technology Holding Co Ltd
Current assignee: Jingdong Technology Holding Co Ltd
Priority date: 2020-12-21
Filing date: 2020-12-21
Publication date: 2022-06-21

Abstract

The embodiment of the application provides a method and a device for filtering asset data, electronic equipment and a storage medium, wherein the asset data to be filtered in an asset database and various filtering sequences of the asset data are determined; according to a preset filtering target, performing different filtering processing on the asset data according to different filtering sequences to obtain a plurality of filtering results; and determining an optimal filtering result in the plurality of 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 obtained by the filtering method is marked, so that the distribution of the asset data is optimized, manual adjustment of the result is not needed, the filtering efficiency of the asset data is high, and the process is simple.

Description

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

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for filtering asset data, an electronic device, and a storage medium.

Background

Asset-Backed Securities (ABS for short) is supported by paying back cash flow generated in the future of basic assets, and enterprise financing is realized by issuing Asset support certificates through structured design. The warranty is simply called a payment agency, which means that the seller transfers its current or future accounts receivable to the warranty based on the goods sale/service contract with the buyer.

In the process of protecting the ABS, the asset data is required to be imported into an asset pool of the ABS, and the asset data in the asset pool is filtered according to a preset filtering target, so that a filtering result is obtained. The filter results will be used to tag the asset data in the asset pool for subsequent use.

However, because the data amount of a single asset data of the warranty ABS is large, the randomness of the result obtained during asset filtering is strong, the filtering result is often not the optimal filtering result, and at this time, the filtering result needs to be processed again by means of manual adjustment, so the processing efficiency of the whole filtering process is low.

Disclosure of Invention

The embodiment of the application provides a method and a device for filtering asset data, electronic equipment and a storage medium, and provides a more efficient filtering processing flow for asset data in an ABS (anti-lock braking system) process.

In one aspect, the present application provides a method for filtering asset data, including:

determining each asset data to be filtered in the asset database and a plurality of filtering sequences of each asset data;

according to a preset filtering target, performing different filtering processing on the asset data according to different filtering sequences to obtain a plurality of filtering results;

and determining an optimal filtering result in the plurality of 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.

In alternative embodiments, a plurality of filtering orders for the asset data is determined, including:

arranging and processing each asset data in a preset mode to obtain the multiple filtering sequences; wherein the preset mode comprises one or more of a plurality of sequential arrangement processes and a plurality of non-sequential arrangement processes.

In an optional embodiment, the performing different filtering processes on the asset data according to different filtering orders according to a preset filtering target to obtain a plurality of filtering results includes:

and aiming at any one filtering sequence of the asset data, filtering the asset data in the filtering sequence by adopting a distributed processing mode to obtain a filtering result in the filtering sequence.

In an optional embodiment, the filtering, by using a distributed processing manner, the asset data in the filtering order to obtain the filtering result in the filtering order includes:

based on the filtering sequence, establishing filtering processing tasks corresponding to the asset data and determining corresponding task priorities; wherein the task priority of the filtering processing task is determined according to the filtering order

And sequentially processing the plurality of filtering processing tasks according to the task priority of the filtering processing tasks to obtain a filtering result of each asset data in the filtering sequence.

In an optional embodiment, the sequentially processing the plurality of filtering processing tasks according to the task priorities of the filtering processing tasks to obtain the filtering result of each asset data in the filtering order includes:

determining the processing state of each filtering processing task;

selecting a filtering processing task with the highest task priority from all filtering processing tasks with the processing states to be processed, distributing the filtering processing task to any idle processing server for processing, and updating the processing states of the filtering processing tasks;

and repeating the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks with the processing states to be processed until the processing states of all the filtering processing tasks are processed, wherein the processing structure of each filtering processing task forms the filtering result of each asset data in the filtering sequence.

In an optional embodiment, the filtering method further comprises:

determining a conflict relationship between each filtering result and the optimal filtering result; wherein the conflict relationship is used for indicating that the asset data forming the two filtering results are overlapped;

and keeping the filtering result which has no conflict relation with the optimal filtering result.

In an alternative embodiment, the filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result state of one piece of asset data;

correspondingly, the determining the conflict relationship between each filtering result and the optimal filtering result includes:

comparing the binary character bit of each filtering result with the binary character bit of the optimal filtering result bit by bit;

and determining the conflict relationship between each filtering result and the optimal filtering result according to the bit-by-bit comparison result.

In a second aspect, the present application provides an apparatus for filtering asset data, comprising:

the processing module is used for determining each asset data to be filtered in the asset database and a plurality of filtering sequences of each asset data;

the filtering module is used for executing different filtering processes on the asset data according to different filtering sequences according to a preset filtering target to obtain a plurality of filtering results;

and the marking module is used for determining an optimal filtering result in the plurality of 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.

In an optional embodiment, when determining the plurality of filtering orders of the asset data, the processing module is specifically configured to:

In an optional embodiment, when executing different filtering processes on the asset data according to different filtering orders according to a preset filtering target, and obtaining a plurality of filtering results, the filtering module is specifically configured to:

In an optional embodiment, when the filtering module performs filtering processing on the asset data in the filtering order in a distributed processing manner to obtain a filtering result in the filtering order, the filtering module is specifically configured to:

In an optional embodiment, when the filtering module sequentially processes the plurality of filtering processing tasks according to the task priorities of the filtering processing tasks to obtain the filtering result of each asset data in the filtering order, the filtering module is specifically configured to:

determining the processing state of each filtering processing task;

selecting the filtering processing task with the highest task priority from the filtering processing tasks with the processing states to be processed, distributing the filtering processing task to any idle processing server for processing, and updating the processing states of the filtering processing tasks;

In an optional embodiment, the marking module is further configured to:

the marking module is specifically configured to:

comparing the binary character bit of each filtering result with the binary character bit of the optimal filtering result bit by bit; and determining the conflict relationship between each filtering result and the optimal filtering result according to the bit-by-bit comparison result.

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

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the filtering method of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a processor, implement the filtering method of the first aspect.

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

Drawings

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 application.

FIG. 1 is a schematic diagram of a network architecture on which the present application is based;

FIG. 2 is a schematic flow chart diagram of a method for filtering asset data provided herein;

FIG. 3 is a schematic flow chart diagram illustrating yet another method for filtering asset data provided herein;

FIG. 4 is a schematic structural diagram of an asset data filtering apparatus according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of systems and methods consistent with certain aspects of the present application, as detailed in the appended claims.

Asset-Backed Securities (ABS) is supported by reimbursement of cash flows generated in the future of underlying assets, and enterprise financing is achieved by issuing Asset support certificates through structured design.

However, because the data limit of a single asset data of the warranty ABS is large, the randomness of the result obtained during asset filtering is strong, and the filtering result is often not the optimal filtering result.

For example, taking the asset pool as an example, which includes asset data a (80 ten thousand), asset data B (60 ten thousand), asset data C (40 ten thousand) and asset data D (50 ten thousand), if the filtering target is to select asset data with a total amount of 100 ten thousand and perform data tagging, when filtering is performed by using the existing filtering method, the quota of each asset data is sequentially overlapped according to the sequence of asset data a, asset data B, asset data C and asset data D.

Therefore, after the asset data A is selected, the quota is caused to be excessive by any one of the overlapping asset data B, the asset data C and the asset data D, so that in order to ensure that the overlapping quota meets the filtering condition, the existing filtering method provides a filtering result only by selecting the asset data A as the marking target. However, it is obvious that, based on the above asset data, the combination of the asset data B (60 ten thousand) and the asset data C (40 ten thousand) is better able to satisfy the filtering target, that is, the filtering result given by the existing filtering method is often not the most preferable result.

Therefore, in order to avoid this, in the prior art, when the filtering result is obtained, the filtering result needs to be manually readjusted so that the combination of the asset data B (60 ten thousand) and the asset data C (40 ten thousand) is the final filtering result.

Obviously, the accuracy and the filtering efficiency of the filtering process cannot meet the actual use requirements by adopting the filtering mode, and particularly, under the condition that the asset pool comprises a large amount of asset data, a large amount of manpower is needed to adjust the filtering result, so that the filtering efficiency is very low, and the cost is high.

In order to solve the problems, the scheme based on the application determines the asset data to be filtered in the asset database and a plurality of filtering sequences of the asset data; according to a preset filtering target, performing different filtering processing on the asset data according to different filtering sequences to obtain a plurality of filtering results; and determining an optimal filtering result in the plurality of 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 obtained by the filtering method is marked, so that the distribution of the asset data is optimized, manual adjustment of the result is not needed, the filtering efficiency of the asset data is high, the manual time cost and the financial cost are greatly reduced, and the process is simple

The method provided by the present application will be described below with reference to different implementations.

Referring to fig. 1, fig. 2 is a schematic diagram of a network architecture based on the present application, and the network architecture shown in fig. 2 may specifically include a service system 1 and a server 2.

The service system 1 is specifically a service system for providing ABS front-end services, and may be specifically erected in a service server at the cloud end to provide service support for the ABS front-end services and generate asset data related to the services.

The server 2 is specifically a hardware device installed in the cloud for executing the asset data filtering method of the present application. The server 2 can establish a communication connection with the service system 1 through a network to realize data interaction with the service system 1.

After generating the asset data, the business system 1 may transmit the asset data to the server 2. The server 2 stores the asset data in the asset database after receiving the asset data, and performs corresponding filtering processing according to the asset data filtering method provided by the application.

Example one

Fig. 2 is a schematic flow chart of a method for filtering asset data provided in the present application, as shown in fig. 2, the method includes:

step 101, determining each asset data to be filtered in the asset database and a plurality of filtering sequences of each asset data.

And 102, executing different filtering processes on the asset data according to different filtering sequences according to a preset filtering target, and obtaining a plurality of filtering results.

And 103, determining an optimal filtering result in the plurality of 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.

It should be noted that the asset data filtering method provided in the present application is particularly applicable to a filtering apparatus for asset data, and the filtering apparatus may be particularly disposed in the server 2 shown in fig. 1.

The embodiment of the application provides an asset data filtering method. The filtering method provided by the application is completely different from the prior art in that the asset data to be filtered and various filtering orders of the asset data are firstly determined, and then the asset data to be filtered are subjected to multiple filtering treatments based on different filtering orders.

In particular, asset filtering generally first requires setting a filtering target, as previously described: the asset database includes asset data a (80 ten thousand), asset data B (60 ten thousand), asset data C (40 ten thousand), asset data D (50 ten thousand), and the like, and the filtering target may be "select asset data amounting to 100 ten thousand in total".

Based on the filtering target, the filtering apparatus first selects asset data to be filtered from the asset database, such as asset data a (80 ten thousand), asset data B (60 ten thousand), asset data C (40 ten thousand), and asset data D (50 ten thousand) as the asset data to be filtered.

Then, determining the filtering order of the asset data to be filtered, such as: A-B-C-D as one filtering sequence, C-B-D-A as another filtering sequence, and D-C-B-A as yet another filtering sequence, but is not limited thereto.

Generally, when based on the same filtering rule, changing the filtering order of the asset data causes the data composition constituting the filtering result to be different. For example, in the filtration sequence of A-B-C-D, the filtration result obtained is A; in the case of C-B-D-A as the filtration sequence, the filtration results obtained are B and C; in this filtering order, D-C-B-A, the filtering results obtained were D and C. The greater the number of filtering results, the better the optimal filtering result.

Therefore, in the foregoing step of determining the filtering order, the asset data needs to be sorted as much as possible, and sorted combinations of the asset data are obtained as many as possible, so that filtering according to different sorts obtains different filtering results.

Optionally, in order to obtain different filtering results as much as possible, a plurality of sorting rules are adopted to determine the filtering order: arranging and processing each asset data in a preset mode to obtain the multiple filtering sequences; wherein the preset mode comprises one or more of a plurality of sequential arrangement processes and a plurality of non-sequential arrangement processes.

Specifically, the plurality of permutations may include a sequential permutation, i.e., an ascending or descending permutation, such as an ascending permutation of A-B-C-D, or a descending permutation of D-C-B-A. The plurality of permutations may also include non-sequential permutations, such as A-C-D-B, C-A-B-D, that are not in ascending and descending order.

By performing a plurality of kinds of arrangement processing on the respective asset data, it is possible to obtain as many orders of the respective asset data as possible, each of which is to be subjected to filtering processing as one filtering order.

Then, the filtering device executes different filtering processes to the asset data according to different filtering orders according to a preset filtering target, and a plurality of filtering results are obtained.

In the process of filtering the asset data according to any filtering order, in order to improve the processing efficiency, a distributed processing mode can be adopted for processing.

That is to say, optionally, for any filtering order of the asset data, filtering processing is performed on the asset data in the filtering order in a distributed processing manner, so as to obtain a filtering result in the filtering order.

Specifically, when asset data is processed based on a filtering order, one asset data may establish a corresponding filtering task, and in order to indicate the filtering order, it is also necessary to set a task priority for each filtering task when the filtering tasks are established. That is, the processing device may establish filtering processing tasks corresponding to the asset data based on the filtering order and determine corresponding task priorities; wherein the task priority of the filtering processing task is determined according to the filtering order.

Taking the filtering sequence as D-C-B-a as an example, a filtering processing task is established for each asset data, namely a filtering processing task D, a filtering processing task C, a filtering processing task B, and a filtering processing task a. Then, as the filtering sequence is D-C-B-A, task priority setting is carried out on each filtering processing task, namely the filtering processing task D-is highest, the filtering processing task C-is second, the filtering processing task B-is second and the filtering processing task A-is lowest.

Then, the processing device processes the plurality of filtering processing tasks in sequence according to the task priority of the filtering processing tasks, and obtains the filtering result of each asset data in the filtering sequence.

Specifically, for each filtering processing task, the processing device also stores a processing state of the task, which is used to indicate a current processing stage of the filtering processing task, such as unprocessed, processed, in-process, and so on. The filtering device distributes filtering processing tasks to the processing servers according to the task priority and the processing state of each filtering processing task, so that the processing servers execute filtering processing and output filtering results.

The filtering device firstly determines the processing state of each filtering processing task; selecting the filtering processing task with the highest task priority from the filtering processing tasks with the processing states to be processed, distributing the filtering processing task to any idle processing server for processing, and updating the processing states of the filtering processing tasks; and repeating the process of selecting the filtering processing task with the highest task priority from the filtering processing tasks with the processing states to be processed until the processing states of all the filtering processing tasks are processed, wherein the processing structure of each filtering processing task forms the filtering result of each asset data in the filtering sequence.

And finally, after the plurality of filtering results are obtained, determining an optimal filtering result in the plurality of filtering results according to the data dimension weight of the asset data by the filtering device, and marking the asset data in the asset database according to the optimal filtering result.

Specifically, the results of processing the filtering processing tasks by the processing servers are recorded in the detail table in real time, and the detail table including all the filtering results is finally formed. And then, analyzing the degree of the filtering result based on the preset data dimension weight of the asset data, and selecting the optimal filtering result. For example, the data dimension of the payback fund has a weight of 0.8, and the data dimension of the profitability has a weight of 0.2.

For the filtering result a, the value of the principal to be returned is 10000, the value of the profitability is 0.8, and the scoring result of the filtering result a is 10000 × 0.8+0.8 × 0.2 ═ 8000.16 by using the weight.

For the filtering result B, the value of the remaining principal is 10000, the value of the profitability is 0.81, and the scoring result of the filtering result B is 10000 × 0.8+0.81 × 0.2 × 8000.162 by using the weight.

According to the scoring result, the filtering result B is the optimal filtering result under the current weight configuration. At this time, the asset data in the asset database will be marked according to the asset data in the filtering result B.

Based on the embodiment shown in fig. 2, fig. 3 is a schematic flow chart of another asset data filtering method provided by the present application, and as shown in fig. 3, the method includes:

step 201, determining each asset data to be filtered in the asset database and a plurality of filtering sequences of each asset data.

And step 202, performing different filtering processes on the asset data according to different filtering sequences according to a preset filtering target to obtain a plurality of filtering results.

And 203, determining an optimal filtering result in the plurality of 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.

Step 204, determining a conflict relationship between each filtering result and the optimal filtering result;

and step 205, reserving the filtering result which has no conflict relation with the optimal filtering result. Wherein the conflict relationship is used for indicating that the asset data forming the two filtering results are overlapped.

In an actual scenario, in order to avoid repeated marking of assets, the same asset data can be marked only once, that is, after the asset data a is marked in the asset database as one of the asset data of the filtering result B, the asset data a will not be used as the asset data to be filtered in the next filtering, so as to enter the filtering process flow.

Therefore, unlike the previous embodiment, after the optimal filtering result is selected and marked on the asset database, the filtering result having a conflicting relationship with the optimal filtering result needs to be determined and discarded.

The conflict relationship is as follows: when the same asset data is included in both the filtering results, the two filtering results have a conflict relationship; when the same asset data is not included in the two filter results, there is no conflict relationship between the two filter results.

For example, if the asset data a is selected by the filtering result a and is selected by the filtering result B, the filtering result a and the filtering result B are considered to have a conflict relationship.

In order to quickly determine whether there is a conflicting relationship between the filter results, a two-level system character bit may be used to represent each filter result in the present application.

Specifically, if there are 20 asset data, 20 character bits can be set to represent the hit of each asset data, and the combination of the 20 character bits will constitute the filter result. That is, for a filtering result, it can be represented by only 20 bytes, which saves the cache greatly.

Correspondingly, when the conflict relationship is determined, the binary character bit of each filtering result can be compared with the binary character bit of the optimal filtering result bit by bit; and determining the conflict relationship between each filtering result and the optimal filtering result according to the bit-by-bit comparison result.

For example, if [ asset data a, asset data B, asset data C, asset data D ] is used as all asset data, when asset data a and asset data C are selected in filter result a, filter result a may be represented as [1,0,1,0], and when asset data a and asset data D are selected in filter result B, filter result a may be represented as [1,0,0,1 ]; where a 1 indicates a hit in the asset data and a 0 indicates a miss in the asset data.

When the conflict relationship is determined, the two character bits can be compared based on each secondary system character bit, and finally the two character bits are known to hit the asset data A, namely the two character bits have the conflict relationship.

By the method, the conflict relationship among the filtering results can be quickly determined under the condition of occupying small cache, and repeated asset marking is avoided.

The embodiment of the application provides a method for filtering asset data, which comprises the steps of determining asset data to be filtered in an asset database and various filtering sequences of the asset data; according to a preset filtering target, performing different filtering processing on the asset data according to different filtering sequences to obtain a plurality of filtering results; and determining an optimal filtering result in the plurality of 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 obtained by the filtering method is marked, so that the distribution of the asset data is optimized, manual adjustment of the result is not needed, the filtering efficiency of the asset data is high, and the process is simple.

Example two

Fig. 4 is a schematic structural diagram of an asset data filtering apparatus according to an embodiment of the present application, and as shown in fig. 4, the asset data filtering apparatus includes: a processing module 10, a filtering module 20 and a labeling module 30.

A processing module 10, configured to determine asset data to be filtered in an asset database and multiple filtering orders of the asset data;

a filtering module 20, configured to perform different filtering processes on the asset data according to different filtering orders according to a preset filtering target, so as to obtain multiple filtering results;

and the marking module 30 is configured to determine an optimal filtering result from the multiple filtering results according to the data dimension weight of the asset data, and mark the asset data in the asset database according to the optimal filtering result.

In an alternative embodiment, the processing module 10 is specifically configured to, when determining multiple filtering orders of the asset data:

and randomly arranging the asset data to obtain the multiple filtering sequences.

In an optional embodiment, when executing different filtering processes on the asset data according to different filtering orders according to a preset filtering target, and obtaining a plurality of filtering results, the filtering module 20 is specifically configured to:

In an optional embodiment, when the filtering module 20 performs filtering processing on the asset data in the filtering order in a distributed processing manner to obtain the filtering result in the filtering order, the method is specifically configured to:

In an optional embodiment, when the filtering module 20 sequentially processes the plurality of filtering processing tasks according to the task priorities of the filtering processing tasks to obtain the filtering result of each asset data in the filtering order, the filtering module is specifically configured to:

determining the processing state of each filtering processing task;

In an optional embodiment, the marking module 30 is further configured to:

determining a conflict relationship between each filtering result and the optimal filtering result;

the marking module 30 is specifically configured to:

The embodiment of the application provides a device for filtering asset data, which is characterized in that various asset data to be filtered in an asset database and various filtering sequences of the various asset data are determined; according to a preset filtering target, performing different filtering processing on the asset data according to different filtering sequences to obtain a plurality of filtering results; and determining an optimal filtering result in the plurality of 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 obtained by the filtering method is marked, so that the distribution of the asset data is optimized, manual adjustment of the result is not needed, the filtering efficiency of the asset data is high, and the process is simple.

EXAMPLE III

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 5, an electronic device 1400 according to an embodiment of the present invention includes: memory 1401, processor 1402, and computer programs.

Wherein a computer program is stored in the memory 1401 and is configured to be executed by the processor 1402 to implement the processing method of the question and answer session provided by any one of the embodiments of the present invention. The related descriptions and effects corresponding to the steps in the drawings can be correspondingly understood, and redundant description is not repeated here.

In this embodiment, the memory 1401 and the processor 1402 are connected by a bus.

Example four

Embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the asset data filtering method provided by any one of the embodiments of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, a division of modules is merely a logical division, and other divisions may be realized in practice, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or modules, and may be in an electrical, mechanical or other form.

Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware form, and can also be realized in a form of hardware and a software functional module.

Program code for implementing the methods 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, special purpose computer, or other programmable question answering system, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device. The 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, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Furthermore, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the method of filtering asset data as described above.

Further, while operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.

Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A method for filtering asset data, comprising:

2. The filtering method of claim 1, wherein determining a plurality of filtering orders for each asset data comprises:

3. The filtering method according to claim 1, wherein the performing different filtering processes on the asset data according to different filtering orders according to preset filtering targets to obtain a plurality of filtering results comprises:

4. The filtering method according to claim 3, wherein the filtering the asset data in the filtering order in a distributed processing manner to obtain the filtering result in the filtering order comprises:

based on the filtering sequence, establishing filtering processing tasks corresponding to the asset data and determining corresponding task priorities; wherein the task priority of the filtering processing task is determined according to the filtering order;

5. The filtering method according to claim 4, wherein the sequentially processing the plurality of filtering processing tasks according to the task priorities of the filtering processing tasks to obtain the filtering results of the asset data in the filtering order includes:

determining the processing state of each filtering processing task;

and repeating the process of selecting the filtering processing task with the highest task priority from all the filtering processing tasks with the processing states to be processed until the processing states of all the filtering processing tasks are processed, wherein the processing structure of each filtering processing task forms the filtering result of each asset data in the filtering sequence.

6. The filtration method according to any one of claims 1 to 5, further comprising:

7. The filtering method according to claim 6, wherein the filtering result is represented by binary character bits, wherein each binary character bit of the filtering result corresponds to a result status of one piece of asset data;

8. An apparatus for filtering asset data, comprising:

9. An electronic device, comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the filtering method of any of claims 1-7.

10. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a processor, implement the filtering method of any one of claims 1-7.

11. A computer program product comprising a computer program, characterized in that the computer program realizes the filtering method of any one of claims 1-7 when executed by a processor.