CN112950382A - Transaction business matching method and device, electronic equipment and medium - Google Patents
Transaction business matching method and device, electronic equipment and medium Download PDFInfo
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Abstract
The disclosure provides a transaction business matching method, a transaction business matching device, electronic equipment and a transaction business matching medium, and relates to the field of computer big data mining and artificial intelligence. The transaction service matching method comprises the following steps: judging whether the bank transaction business file to be matched meets the preset processing requirement or not; if the transaction business file meets the first preset standard format, performing first preset standard format conversion on the transaction business file, and screening feature file data from the converted transaction business file by using a data import tool; carrying out simulation matching on the investor information and the investment target object information in the feature file data by using a matching model, predicting matching success rate after matching, wherein the matching model is a neural network model; and generating an automatic recommendation service list according to the matching success rate after matching.
Description
Technical Field
The present disclosure relates to the field of computer big data mining and artificial intelligence, and in particular, to a transaction service matching method, apparatus, electronic device, and medium.
Background
At present, investment banks belong to important financial intermediaries in the capital market, and matching transactions are the basic functions of investment banking. However, in the aspect of investment banking, the investment banking business is still in a relatively original manual matching stage, and the promotion of the business by information technology is usually limited to establishing an investment target information base and an investor information base, and the key link of "matching of investment target objects and investors" still depends heavily on the working experience and manual analysis of business personnel.
With the increasing size of investment subject matter information bases and investor information bases and the increasing number of cross-region matching situations, the existing matching mode based on manual analysis of business personnel is difficult to meet the practical situation of business development and the requirements of customers, and how to quickly mine effective project and investor information and conduct feasibility analysis of matching becomes a problem to be solved urgently in business development.
Disclosure of Invention
Technical problem to be solved
In view of the above disadvantages of the prior art, the present disclosure provides a transaction service matching method, device, electronic device, and medium, so as to quickly, efficiently, and accurately implement mining of investment targets and investor information and provide business personnel with guidance for actual matching service.
(II) technical scheme
One aspect of the present disclosure provides a transaction service matching method, including: judging whether the bank transaction business file to be matched meets the preset processing requirement or not; if the transaction business file meets the first preset standard format, performing first preset standard format conversion on the transaction business file, and screening feature file data from the converted transaction business file by using a data import tool; carrying out simulation matching on the investor information and the investment target object information in the feature file data by using a matching model, predicting matching success rate after matching, wherein the matching model is a neural network model; and generating an automatic recommendation service list according to the matching success rate after matching.
According to the embodiment of the disclosure, the preset processing requirements comprise a preset file storage format requirement, a preset file name requirement and a preset file content requirement; the preset file storage format requirement comprises EXCEL, DBF, TXT or CSV, and the first preset standard format is TXT format.
According to the embodiment of the disclosure, judging whether the banking transaction business file to be matched meets the requirement of the preset file name comprises the following steps: and judging whether the banking transaction file to be matched accords with a preset file name rule text or not by using a regular expression, wherein the preset file name rule text is obtained by sequentially combining a preset file name prefix, file receiving date information and a file extension name.
According to an embodiment of the present disclosure, the preset file content requirement includes: at least one of length, delimiter, number of fields, format of each field, and dictionary value of each field of each record in the file content.
According to the embodiment of the present disclosure, before the step of performing the first preset standard format conversion on the transaction service file, the method further includes: and acquiring the transaction service file meeting the preset processing requirement by using a file reading tool.
According to the embodiment of the disclosure, before the step of performing simulation matching on the investor information and the investment target object information in the profile data by using the matching model, the method further comprises the following steps: acquiring structure information and file loading control information in a transaction service file which meets the preset processing requirement; and adding, deleting or modifying the structure information and the file loading control information in the transaction service file.
According to the embodiment of the disclosure, the matching model is used for simulating and matching the investor information and the investment target object information in the feature file data, and the matching success rate after matching is predicted, which comprises the following steps: importing investor information, investment target object information and matched business information in a bank transaction business file by using a data importing tool, analyzing a correlation mode among the investor information, the investment target object information and matched matching success rate, and establishing a matching model; and (4) according to the matching model, carrying out simulation matching on the investor information in the characteristic file data and the investment target object information, and predicting the matching success rate after matching.
According to an embodiment of the disclosure, the method further comprises: periodically acquiring and importing the information of the matched services; and according to the matched business information, learning the association mode among the investor information, the investment target object information and the matched matching success rate, and updating a matching model.
According to the embodiment of the disclosure, according to the matching success rate after matching, an automatic recommendation service list is generated, which includes: and when the matching success rate after matching is greater than or equal to a preset success rate threshold value, sequencing and sorting the matched investor information, the investment target object information and the matching success rate after matching, and generating an automatic recommendation service list according to a second preset standard format.
According to the embodiment of the disclosure, the preset success rate threshold is 50% -100%.
According to the embodiment of the disclosure, an automatic recommendation service list is generated according to the matching success rate after matching, and the method further comprises the following steps: and when the matching success rate after matching is smaller than a preset success rate threshold value, filtering the investor information subjected to analog matching, the investment target object information and the matching success rate after matching.
Another aspect of the present disclosure provides a transaction service matching apparatus, including: the file judging module is used for judging whether the bank transaction business file to be matched meets the preset processing requirement or not; the file processing module is used for performing first preset standard format conversion on the transaction business file when the bank transaction business file to be matched meets the preset processing requirement, and screening feature file data from the converted transaction business file by using a data import tool; the matching prediction module is used for performing simulation matching on the investor information and the investment target object information in the feature file data by using a matching model, predicting matching success rate after matching, and taking the matching model as a neural network model; and the list generation module is used for generating an automatic recommendation service list according to the matching success rate after matching.
Another aspect of the present disclosure provides an electronic device including: one or more processors; a storage device to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method as described above.
Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.
Another aspect of the disclosure provides a computer program comprising computer executable instructions for implementing the method as described above when executed.
(III) advantageous effects
The transaction business matching method, the transaction business matching device, the electronic equipment and the medium have the following beneficial effects at least:
(1) the method realizes automatic matching and matching of the investment banking business through big data and artificial intelligence technology, can quickly, efficiently and accurately realize the mining of investment objects and investor information, quickly generates a simulation matching business list with high success rate, and provides business personnel with guidance for the development of actual matching business;
(2) according to the method, the actual matching business information of the investment bank after simulation matching generated by the system is continuously fed back into the system, so that the longer the system running time is, the more the matching times are, the more accurate the matching analysis result is, and the self-iteration and function enhancement of the automatic simulation matching function of the investment bank matching transaction are ensured.
Drawings
For a more complete understanding of the present disclosure and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:
fig. 1 schematically shows a system architecture of a transaction traffic match matching method and apparatus according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a transaction service match matching method according to an embodiment of the present disclosure;
FIG. 3 schematically shows a flow chart of a file determination process according to an embodiment of the present disclosure;
FIG. 4 schematically shows a flow diagram of a file processing procedure according to an embodiment of the present disclosure;
FIG. 5 schematically shows a flow chart of a file usage process according to an embodiment of the present disclosure;
FIG. 6 schematically illustrates a flow chart of a simulated matching process according to an embodiment of the disclosure;
fig. 7 schematically shows a block diagram of a transaction traffic match matching apparatus according to an embodiment of the present disclosure;
FIG. 8 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
Some block diagrams and/or flow diagrams are shown in the figures. It will be understood that some blocks of the block diagrams and/or flowchart illustrations, or combinations thereof, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the instructions, which execute via the processor, create means for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks. The techniques of this disclosure may be implemented in hardware and/or software (including firmware, microcode, etc.). In addition, the techniques of this disclosure may take the form of a computer program product on a computer-readable storage medium having instructions stored thereon for use by or in connection with an instruction execution system.
The embodiment of the disclosure provides a transaction service matching method, which may include: judging whether the bank transaction business file to be matched meets the preset processing requirement or not; if the transaction business file meets the first preset standard format, performing first preset standard format conversion on the transaction business file, and screening feature file data from the converted transaction business file by using a data import tool; carrying out simulation matching on the investor information and the investment target object information in the feature file data by using a matching model, and predicting matching success rate after matching; and generating an automatic recommendation service list according to the matching success rate after matching.
Before describing in detail specific embodiments of the present invention, technical terms are first explained to facilitate a better understanding of the present invention.
Financial matching, which is typical of one of the many matching services, is also one of the matching services that is most active, frequent and most needed in modern economic activities. The method mainly aims at financing, finds a fund supplier for a fund demander by matching a fund demander with the fund supplier, helps to realize financing, finds a proper project for the fund supplier, and realizes the maximum effect of resources.
The embodiment of the disclosure relates to the field of computer big data mining and artificial intelligence, is particularly suitable for the field of finance, and mainly aims at a financial matching scene. The investor information/investment target information described in the present disclosure may also be understood as a buyer/seller in financial transactions, and has versatility, and the present disclosure is mainly described by taking the investor information/investment target information as an example.
Fig. 1 schematically illustrates an exemplary system architecture 100 of a transaction traffic match matching method and apparatus according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as a shopping application, a web browser application, a search application, an instant messaging tool, a mailbox client, and/or social platform software.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server that provides various services, such as a background management server that provides support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the transaction service matching method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the transaction service matching device provided by the embodiment of the present disclosure may be generally disposed in the server 105. The transaction service matching method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the transaction service matching device provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically shows a flow chart of a transaction traffic match matching method according to an embodiment of the present disclosure.
As shown in fig. 2, the transaction service matching method of the embodiment of the present disclosure may include operations S201 to S204.
In operation S201, it is determined whether the banking transaction file to be matched meets a preset processing requirement.
The preset processing requirements comprise a preset file storage format requirement, a preset file name requirement and a preset file content requirement.
In operation S202, if the transaction service file meets the first predetermined standard format, a data import tool is used to screen feature file data from the converted transaction service file.
In operation S203, the matching model is used to perform simulation matching on the investor information and the investment target information in the profile data, and a matching success rate after matching is predicted.
In operation S204, an automatic recommended service list is generated according to the matching success rate after matching.
Through the embodiment, the transaction business matching method provided by the disclosure realizes automatic matching of investment banking business through big data and artificial intelligence technology, can quickly, efficiently and accurately realize mining of investment targets and investor information, quickly generates a simulation matching business list with high success rate, and provides business personnel with guidance for development of actual matching business.
Fig. 3 schematically shows a flow chart of a file determination process according to an embodiment of the present disclosure.
As shown in fig. 3, operation S201 may include sub-operations S2011-S2013, for example.
In operation S2011, it is determined whether the banking transaction file to be matched meets the requirement of the preset file storage format.
The operation is used for judging the storage format adopted by the file. The preset file storage format requirements may include, for example, EXCEL, DBF, TXT, or CSV.
The storage format adopted by the file is identified by reading the binary coding characteristics of the file, so that the content of the file can be conveniently and accurately read subsequently, and the integrity of data analysis is ensured.
For example, files in the DBF storage format have binary encoding characteristics as shown in table 1 below.
TABLE 1 binary encoding characteristics of files in DBF storage format
Therefore, whether the file adopts the DBF storage format or not can be judged by reading the binary coding characteristics of the file and combining the matching relation between the header information of the DBF file and the record field.
In other embodiments, the binary coding feature of the EXCEL, the TXT, or the CSV may be determined according to actual needs to determine whether the file adopts a storage format of the EXCEL, the TXT, or the CSV, which is not described in detail herein.
In operation 2012, it is determined whether the banking transaction file to be matched meets the predetermined file name requirement.
The preset file name rule text is obtained by sequentially combining a preset file name prefix, file receiving date information and a file extension name.
For example, the preset file name rule text of the investment subject matter information may be sequentially combined with a file name prefix TZBDW _ MX, file reception date information "yyyymmdd", and a file extension ". dbf". For another example, in the preset file name rule text of the investment target object information, the file reception date information may be provided with 4-year, 2-month and 2-date information.
For example, the received file name may be set to TZBDW _ mx20170101.dbf for the investment target detail information sent on 1/2017.
In this embodiment, the regular expression is used to determine whether the banking transaction file to be matched conforms to the preset file name rule text. And continuing to take the received detailed information of the investment target objects as an example, and judging whether the banking transaction business file to be matched conforms to TZBDW _ MX +8 year, month and day +. dbf.
In operation 2013, it is determined whether the banking transaction file to be matched meets the preset file content requirement.
In this embodiment, the preset file content requirement includes: at least one of length, delimiter, number of fields, format of each field, and dictionary value of each field of each record in the file content.
For example, if the content of the banking transaction file to be matched is a record with a fixed length, the length of each record needs to be determined. If the banking transaction file to be matched contains the dictionary value of each field, a determination needs to be made for each field dictionary value.
Taking the investment target detail information tzbddw _ MX as an example, the document has the content elements shown in table 2 below.
TABLE 2 content elements of investment target detail information
Through the file judgment of the sub-operations S2011 to S2013, it can be determined whether the banking transaction file to be matched meets the preset processing requirement, and if the banking transaction file to be matched meets the preset processing requirement, the subsequent operation S202 can be executed. And if the preset processing requirement is not met, ending the processing of the file.
It should be noted that the sub-operations S2012 and S2013 are both located after the sub-operation S2011, but the sub-operations S2012 and S2013 may be executed in parallel, that is, there is no explicit order of sequence between the two sub-operations.
FIG. 4 schematically shows a flow diagram of a file processing procedure according to an embodiment of the disclosure.
As shown in fig. 4, operation S202 may include, for example, sub-operations S2021 to S2023.
In operation S2021, a transaction service file meeting the preset processing requirement is acquired using a file reading tool.
Based on the preset file storage format requirement determined in operation S2011, which may include, for example, EXCEL, DBF, TXT, or CSV, this step calls a read function by using a file reading tool to read the EXCEL, DBF, TXT, or CSV storage format file record.
In operation S2022, a first preset standard format conversion is performed on the transaction service file.
And converting the read file record of the transaction service file according to a first preset standard format so as to facilitate the import of subsequent file data. The first predetermined standard format may be a TXT format.
In operation S2023, the profile data is screened out of the converted transaction service profile using the data import tool.
To improve the efficiency of data batch processing to ensure that the investment business is normally used, the data import tool may be, for example, an sql lldr tool.
It can be understood that the sqlldr tool is a high-speed batch data loading tool carried by the Oracle database, can load data into the Oracle database from various flat file formats, can load huge amounts of data in a very short time, and is high in efficiency.
In this embodiment, the converted transaction service file, that is, the standard TXT format file, is subjected to data storage by using the data import tool.
FIG. 5 schematically shows a flow chart of a file usage process according to an embodiment of the disclosure.
As shown in fig. 5, before operation S203, sub-operations S301 to S303 may also be included.
In operation S301, structure information and file loading control information in a transaction service file that meets a preset processing requirement are acquired.
According to the processing of the sub-operations S2021 to S2023, the structure information and the file loading control information of the transaction service file meeting the preset processing requirements are acquired. The structural information is file data format or content information.
In operation S302, structure information and file loading control information in the transaction service file are added, deleted or modified.
The step is used for adding, deleting or modifying the structure information and the file loading control information in the transaction service file according to the requirement in the actual transaction service transaction process. The adding or modifying function is only used for transaction service initialization or operation process of operation and maintenance personnel, and is not directly called by other devices. In particular, the deleting function is only used in the operation process of the operation and maintenance personnel and is not directly called by other devices.
Fig. 6 schematically shows a flow chart of a simulated matching process according to an embodiment of the disclosure.
As shown in fig. 6, operation S203 may include sub-operations S2031 to S2032.
In operation S2031, the data import tool is used to import the investor information, the investment target object information, and the matching service information in the banking transaction file, analyze the association pattern between the investor information, the investment target object information, and the matching success rate after matching, and establish a matching model.
According to the investor information, the investment target object information and the matched service information which are imported by using the data import tool, the correlation mode among the investor information, the investment target object information and the matched matching success rate is analyzed through key word extraction, comparison and other operations, and then a matching model is established.
In operation S2032, according to the matching model, matching is performed on the investor information in the profile data and the investment target information in a simulation manner, and a matching success rate after matching is predicted.
As the characteristic file data is derived from the bank transaction business files to be matched, the step is based on the information of the investment targets which do not have matching business or wait for matching and the information of investors, the information of the investment targets which do not have matching business and the information of the investors are simulated and matched according to the matching model, and after the simulated matching, the predicted matching success rate is given.
In this embodiment, the matching model may also be updated periodically in the following manner:
periodically acquiring and importing the information of the matched services;
and according to the matched business information, learning the association mode among the investor information, the investment target object information and the matched matching success rate, and updating a matching model.
It can be understood that the matching service information is in a dynamic modification state in the transaction service processing process, so that the matching service information is obtained periodically, the matching service information is fed back to the matching model dynamically, the longer the running time of the matching model is, the more the matching times are, the more accurate the matching analysis result is, and the self-iteration and function enhancement of the investment bank matching transaction automatic analysis matching module are ensured.
In this embodiment, when the matching success rate after matching is greater than or equal to the preset success rate threshold, after sorting and sorting the matching investor information, the investment target information, and the matching success rate after matching, an automatic recommendation service list is generated according to a second preset standard format.
The second preset standard format may be an Excel format. The preset success rate threshold may be set according to the actual situation of matching the matching model, and may be set to 50% to 100%, for example.
In addition, when the matching success rate is smaller than the preset success rate threshold after matching, the information of the investors, the investment target object and the matching success rate after matching are filtered.
Therefore, the investment target information subjected to simulation matching, the investor information and the corresponding simulation matching success rate information are collected, information lower than a preset success rate threshold value is filtered out, and the information is output as an automatic recommendation service list file according to an Excel standard format and can be used by operation and maintenance personnel or operating personnel.
Fig. 7 schematically shows a block diagram of a transaction traffic match matching apparatus according to an embodiment of the present invention.
As shown in fig. 7, the transaction traffic match matching device 700 may include a document determination module 710, a document processing module 720, a match prediction module 730, and a list generation module 740.
The file judging module 710 is used for judging whether the banking transaction file to be matched meets the preset processing requirement;
the file processing module 720 is used for performing first preset standard format conversion on the transaction business file when the bank transaction business file to be matched meets the preset processing requirement, and screening feature file data from the converted transaction business file by using a data import tool;
the matching prediction module 730 is used for performing simulation matching on the investor information and the investment target object information in the feature file data by using a matching model, predicting matching success rate after matching, and taking the matching model as a neural network model; and
and the list generating module 740 is configured to generate an automatic recommended service list according to the matching success rate after matching.
It should be noted that, the transaction service matching device part in the embodiment of the present disclosure corresponds to the transaction service matching method part in the embodiment of the present disclosure, and the description of the transaction service matching device part specifically refers to the transaction service matching method part, and is not described herein again.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
For example, any number of the file determination module 710, the file processing module 720, the matching prediction module 730, and the manifest generation module 740 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the file determination module 710, the file processing module 720, the match prediction module 730, and the manifest generation module 740 may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or may be implemented in any one of three implementations of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the file determination module 710, the file processing module 720, the match prediction module 730, and the manifest generation module 740 may be implemented at least in part as a computer program module that, when executed, may perform a corresponding function.
Fig. 8 schematically shows a block diagram of an electronic device according to an embodiment of the invention. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, electronic device 800 includes a processor 810, a computer-readable storage medium 820. The electronic device 800 may perform a method according to an embodiment of the disclosure.
In particular, processor 810 may include, for example, a general purpose microprocessor, an instruction set processor and/or related chip set and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), and/or the like. The processor 810 may also include on-board memory for caching purposes. Processor 810 may be a single processing unit or a plurality of processing units for performing different actions of a method flow according to embodiments of the disclosure.
Computer-readable storage medium 820, for example, may be a non-volatile computer-readable storage medium, specific examples including, but not limited to: magnetic storage devices, such as magnetic tape or Hard Disk Drives (HDDs); optical storage devices, such as compact disks (CD-ROMs); a memory, such as a Random Access Memory (RAM) or a flash memory; and so on.
The computer-readable storage medium 820 may include a computer program 821, which computer program 821 may include code/computer-executable instructions that, when executed by the processor 810, cause the processor 810 to perform a method according to an embodiment of the present disclosure, or any variation thereof.
The computer program 821 may be configured with, for example, computer program code comprising computer program modules. For example, in an example embodiment, code in computer program 821 may include one or more program modules, including for example 821A, modules 821B, … …. It should be noted that the division and number of modules are not fixed, and those skilled in the art may use suitable program modules or program module combinations according to actual situations, and when the program modules are executed by the processor 810, the processor 810 may execute the method according to the embodiment of the present disclosure or any variation thereof.
According to an embodiment of the present disclosure, at least one of the file determination module 710, the file processing module 720, the match prediction module 730, and the manifest generation module 740 may be implemented as a computer program module described with reference to fig. 8, which when executed by the processor 810 may implement the respective operations described above.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (14)
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