Work order processing method, apparatus, electronic device, and medium

Abstract

Provided are a method and device for processing a work order, an electronic device and a medium, which can be applied to the fields of big data technology and information technology. The method comprises the following steps: obtaining a to-be-processed work order, extracting information of interest in the to-be-processed work order, matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises summary data tables and field information thereof in a database, basic data tables and field information thereof, and an association relationship between each summary data table and basic data tables in the summary data table, and finally outputting a matching result. Through automatic induction and summary of data processing logic and collection of data relationship knowledge, a corresponding data knowledge base is established, and meanwhile, based on the knowledge base, matching of the information of interest and summary data information is set, automatic answering of the big data work order is completed, the efficiency of big data support personnel is released, and the efficiency of work order circulation and closed loop is accelerated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of big data and the field of information technology, and more particularly to a work order processing method and device, electronic equipment and medium. BACKGROUND

[0002] In the digital economy era, how to convert data elements into data assets, and then use data assets to drive business innovation and development, has become an important exploration direction for bank digital transformation. One-stop data lake entry of multi-source data solves the problem of data sharing, and data warehouse aggregates data through certain rules to build a theme model, and the aggregated table corresponding to the theme in the model facilitates quick queries by analysts and non-analysts, bringing great convenience to business personnel and data analysts.

[0003] Although the data warehouse establishes the mapping relationship between multiple tables, the processing logic between the summary table and the base table is only known to the application developers and data warehouse operation developers, and the data of the summary table may come from multiple applications, forming a knowledge island. In actual business scenarios, business personnel need to customize processing based on the summary table in combination with the base table of the data source. At present, if business personnel need to understand the processing logic and field information of the summary table and the base table, they need to send an email to the big data mailbox to obtain the help of support personnel through the submission of a work order, the support personnel need to contact the application developers to understand the processing logic, and synchronize the relevant information to the business personnel to complete the work order closed loop, which brings a huge burden and pressure to the support personnel and business personnel.

[0004] At present, most work order problems are solved by support personnel through personal accumulated experience or contacting corresponding application developers to provide logic processing scripts to solve business problems, and historical work orders are manually summarized to form the processing logic of the related summary table and base table as knowledge maintained in the community or other shared media. Although this method can solve the problem of knowledge island to some extent, it is difficult to form a scale effect, and the cost of manually maintaining the knowledge base is too high. In actual business work, the demand for data is changing, and the construction of related applications is also changing. How to efficiently establish relationship knowledge to form a knowledge base, and how to quickly complete knowledge base retrieval and automatic response in big data support work, are urgent problems to be solved. SUMMARY

[0005] In view of the above problems, according to a first aspect of the present application, embodiments of the present application provide a method for processing a work order user, the method comprising: obtaining a to-be-processed work order, wherein the to-be-processed work order comprises a business problem and a problem description of the business problem, and the business problem comprises a business problem related to a summary data table in a database; extracting information of interest in the to-be-processed work order, wherein the information of interest comprises at least one of a data table table name and a field name in a data table; matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summary data tables in the database and field information thereof, N basic data tables in the database and field information thereof, and an association relationship between each of the summary data tables and K basic data tables of the N basic data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N; and outputting a matching result, wherein the matching result comprises: P summary data tables and field information thereof in the knowledge base that match the information of interest in the to-be-processed work order; and an association relationship between each of the P summary data tables and the K basic data tables, P is a positive integer greater than or equal to 1 and less than or equal to M.

[0006] According to some example embodiments, the extracting the information of interest in the to-be-processed work order comprises: extracting, as the information of interest, a data table table name and / or a field name appearing in the business problem and the problem description by using a regular expression.

[0007] According to some example embodiments, the matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base comprises: in a case where the information of interest comprises a data table table name, matching the data table table name with table names of M summary data tables stored in the knowledge base one by one, and obtaining P summary data tables in the knowledge base that match the data table table name.

[0008] According to some example embodiments, the matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base comprises: in a case where the information of interest comprises a data table field name, matching the data table field name with field names of M summary data tables stored in the knowledge base one by one, and obtaining P summary data tables in the knowledge base that match the data table field name.

[0009] According to some example embodiments, the pre-constructing the knowledge base comprises: obtaining target script data, wherein the target script data comprises scripts related to constructing the summary data table; performing syntax analysis on the target script data to extract information of the summary data table, wherein the information of the summary data table comprises a table name and a field name of the summary data table; performing syntax analysis on the target script data to extract association information between the summary data table and a base data table; and constructing the knowledge base according to the extracted information of the summary data table and the association information between the summary data table and the base data table.

[0010] According to some example embodiments, the performing syntax analysis on the target script data to extract association information between the summary data table and a base data table comprises: searching for an insert operation in the target script data; and extracting association information between the summary data table and a base data table according to the searched insert operation.

[0011] According to some example embodiments, before the extracting the information of interest in the to-be-processed work order, the method further comprises: classifying the to-be-processed work order by using a pre-trained machine learning classification model; and the extracting the information of interest in the to-be-processed work order comprises: in response to the to-be-processed work order being classified into a database work order category, extracting the information of interest in the to-be-processed work order.

[0012] According to a second aspect of the present disclosure, there is also provided an apparatus of a work order processing user, the apparatus comprising: a work order obtaining module configured to obtain a to-be-processed work order, wherein the to-be-processed work order comprises a business question and a question description of the business question, and the business question comprises a business question related to a summary data table in a database; an information extracting module configured to extract information of interest in the to-be-processed work order, wherein the information of interest comprises at least one of a data table table name and a field name in a data table; a matching module configured to match the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summary data tables in the database and field information thereof, N base data tables in the database and field information thereof, and an association relationship between each of the summary data tables and K base data tables of the N base data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N; and an output module configured to output a matching result, wherein the matching result comprises: P summary data tables and field information thereof in the knowledge base that match the information of interest in the to-be-processed work order; and an association relationship between each of the P summary data tables and the K base data tables, P is a positive integer greater than or equal to 1 and less than or equal to M.

[0013] According to a third aspect of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing 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.

[0014] According to a fourth aspect of the present application, a computer-readable storage medium is provided, having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method as described above.

[0015] According to a fifth aspect of the present application, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method as described above.

[0016] The one or more embodiments described above have the following advantages or beneficial effects: by automatically inducing the processing logic of data and collecting the data relationship knowledge, and establishing a corresponding data knowledge base, and setting a match between the information of interest and the summary data information based on the knowledge base, the automatic answering of the big data work order is completed, the efficiency of the big data support personnel is released, and the efficiency of work order circulation and closed loop is accelerated. BRIEF DESCRIPTION OF DRAWINGS

[0017] The above and other objects, features and advantages of the present application will become more apparent from the following description of embodiments of the present application taken in conjunction with the accompanying drawings, in which:

[0018] Figure 1 An application scenario diagram of a method, device, electronic device and medium of a work order processing user according to an embodiment of the present application is schematically shown.

[0019] Figure 2 A flowchart of a method of a work order processing user according to an embodiment of the present application is schematically shown.

[0020] Figure 3 A flowchart of matching the information of interest in the extracted to-be-processed work order with the information in the pre-constructed knowledge base according to an embodiment of the present application is schematically shown.

[0021] Figure 4 A flowchart of pre-constructing the knowledge base according to an embodiment of the present application is schematically shown.

[0022] Figure 5 A structural block diagram of a device of a work order processing user according to an embodiment of the present application is schematically shown.

[0023] Figure 6 A block diagram of an electronic device suitable for implementing a method of a work order processing user according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0024] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. It is to be understood, however, that these descriptions are merely exemplary and are intended to illustrate the scope of the present application, not to limit it. In the following detailed description of the embodiments, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present application. However, it would be apparent to those skilled in the art that the present application can be practiced without these specific details. In other instances, well-known structures and functions have not been described in detail in order to avoid obscuring the concepts of the present application.

[0025] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the term "comprising" or "comprises" or "including" or "includes" or "containing" or "contains" or "has" or "having" or the like is used to indicate the presence of stated features, steps, operations, or components but does not preclude the presence or addition of one or more other features, steps, operations, or components.

[0026] All terms used herein (including technical and scientific terms) have the meanings commonly understood by one of ordinary skill in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of the specification, and should not be interpreted in an idealized or overly formal manner.

[0027] In the case of using expressions similar to "at least one of A, B, and C, etc.", it is generally to be interpreted as including any one of A, B, or C, etc. or a combination of A, B, and C, etc. (for example, "a system having at least one of A, B, and C" should include a system having A alone, a system having B alone, a system having C alone, a system having A and B together, a system having A and C together, a system having B and C together, and / or a system having A, B, and C together, etc.).

[0028] In the technical solutions of the present application, the acquisition, storage, and application of user personal information comply with relevant laws and regulations, necessary security measures are taken, and the public order and good customs are not violated.

[0029] First, the technical terms described herein are explained and described as follows.

[0030] Work order: that is, a work order, a work order defines a simple maintenance or manufacturing plan consisting of one or more jobs, the superior department issues a task, and the subordinate department receives the task as a basis.

[0031] Script: is an executable file written in a certain format using a specific descriptive language.

[0032] Based on this, the embodiment of the present application provides a method of a work order processing method, the method comprising: obtaining a to-be-processed work order, wherein the to-be-processed work order comprises a business problem and a problem description of the business problem, and the business problem comprises a business problem related to a summary data table in a database; extracting information of interest in the to-be-processed work order, wherein the information of interest comprises at least one of a data table table name and a field name in a data table; matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summary data tables in the database and field information thereof, N basic data tables in the database and field information thereof, and an association relationship between each of the summary data tables and K basic data tables of the N basic data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N; and outputting a matching result, wherein the matching result comprises: P summary data tables and field information thereof in the knowledge base matched with the information of interest in the to-be-processed work order; and an association relationship between each of the P summary data tables and the K basic data tables, and P is a positive integer greater than or equal to 1 and less than or equal to M.

[0033] In the method according to the embodiment of the present application, the processing logic of summarizing data is automatically induced, the data relationship knowledge is collected, the corresponding data knowledge base is established, and the matching of the information of interest and the summary data information is set based on the knowledge base, so that the automatic answering of the big data work order is completed, the efficiency of the big data support personnel is released, and the efficiency of the work order circulation and closed loop is accelerated.

[0034] It should be noted that the work order processing method and device determined by the present application can be used in the field of big data technology and the field of information technology.

[0035] Figure 1 An application scenario diagram of the method, device, equipment and medium for work order processing according to the embodiment of the present application is schematically shown.

[0036] As Figure 1 shown, the application scenario 100 according to the embodiment can comprise terminal equipment 101, 102, 103, a network 104 and a server 105. The network 104 is used as a medium to provide a communication link between the terminal equipment 101, 102, 103 and the server 105. The network 104 can comprise various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0037] The user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0038] The terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smartphones, tablet computers, laptop computers, desktop computers, etc.

[0039] The server 105 can be a server providing various services, such as a background management server providing support for websites browsed by users using the terminal devices 101, 102, 103 (only as an example). The background management server can analyze and process received user requests and other data, and feed back the processing results (such as web pages, information, or data, etc. obtained or generated according to user requests) to the terminal devices.

[0040] It should be noted that the method for processing a work order provided by the embodiments of the present application can generally be executed by the server 105. Accordingly, the device for processing a work order user provided by the embodiments of the present application can generally be arranged in the server 105. The method for processing a work order user provided by the embodiments of the present application can also be executed by a server or 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 device for processing a work order user provided by the embodiments of the present application can also be arranged in a server or server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105.

[0041] It should be understood that the number of terminal devices, networks and servers in Figure 1 is only illustrative. Any number of terminal devices, networks and servers can be provided according to the needs of implementation.

[0042] The method for processing a work order user provided by the embodiments of the present application will be described in detail below based on the scenario described below. Figure 1 Figures 2 to 6 The method for processing a work order user provided by the embodiments of the present application will be described in detail below based on the scenario described below.

[0043] Figure 2 A flowchart of the method for processing a work order user according to the embodiments of the present application is schematically shown.

[0044] As shown in Figure 2 , the method 200 for processing a work order user of this embodiment can include operation S210 to operation S240. ​

[0045] In operation S210, a to-be-processed work order is acquired, wherein the to-be-processed work order includes a business problem and a problem description of the business problem, and the business problem includes a business problem related to a summary data table in a database.

[0046] In an embodiment of the present application, the business problem includes a problem involved in asset business, liability business and intermediate business. The asset business refers to an activity of a commercial bank to absorb funds and operate to earn interest income or investment income, mainly including loan business, discount business, investment business and inter-bank lending business. For example, a personal credit loan handled by a bank is an asset business. The liability business refers to a behavior of a commercial bank to borrow funds with a right to use in compliance with a financial license, mainly including deposit (savings) business, inter-bank lending and bond issuance business. For example, a deposit savings business handled by a bank is a liability business. The intermediate business refers to a role of a commercial bank to provide intermediation or agency for customers outside a table, using its own network, information, credit or license advantage, usually implementing paid service, mainly including guarantee, agency, consultation, payment and collection businesses. For example, a regular financial management business handled by a bank is an intermediate business.

[0047] In an embodiment of the present application, the description of the business problem is a specific information description of the to-be-processed business problem, including names and / or ID numbers of specific individuals of both parties of the business, and / or names and / or numbers of units, business processing time, business problem number, etc. For example, a person handles a withdrawal business in a bank, and the description of the business needs to include the name and ID number of the person, the time and place of the withdrawal business handling, and the specific amount of the withdrawn money, etc.

[0048] In an embodiment of the present application, a large amount of business information and processing logic of a basic layer data summary are pre-integrated in the database, and the business information and processing logic are summarized by developers of various applications, data analysts, etc. in combination with business experience and data between various tables in the database, and have certain expert rules. In an embodiment of the present application, the summary data table is made based on the business information and processing logic summarized in the database.

[0049] In operation S220, interested information in the to-be-processed work order is extracted, wherein the interested information includes at least one of a data table name and a field name in the data table.

[0050] In an embodiment of the present application, for example, there is a data table in the database, the table name is a unified view of a legal person client, and the field name in the data table includes the name of a legal person client. The existing to-be-processed work order is a liability business work order of a company, and the interested information therein includes the name of the legal person client, etc.

[0051] In operation S230, the extracted information of interest in the to-be-processed work order is matched with information in the pre-constructed knowledge base.

[0052] In an embodiment of the present application, the pre-constructed knowledge base includes M summary data tables and field information thereof in a database, N base data tables and field information thereof in the database, and an association relationship between each of the summary data tables and K base data tables of the N base data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N.

[0053] In operation S240, a matching result is output.

[0054] In an embodiment of the present application, the matching result includes P summary data tables and field information thereof in the knowledge base matched with the information of interest in the to-be-processed work order, and an association relationship between each of the P summary data tables and K base data tables, P is a positive integer greater than or equal to 1 and less than or equal to M.

[0055] In an embodiment of the present application, firstly, a relationship knowledge base is established by analyzing script files of data warehouse for summary processing of each application base data, and a knowledge island problem that processing script logical relationship is only mastered by developers is overcome. Secondly, based on data summary layer and base layer use demand in actual business production process, an automatic matching method is provided based on the relationship knowledge base, to help business personnel quickly associate data base layer and processing logic of processing layer, and the business personnel can perform logical processing on this basis, further play the value of data, and release the data use potential.

[0056] Returning to operation S220, the extracting the information of interest in the to-be-processed work order includes extracting a data table name and / or a field name appearing in the business problem and the problem description by using a regular expression as the information of interest.

[0057] In an embodiment of the present application, a regular expression, also known as a rule expression, is a text pattern including ordinary characters (for example, letters between a and z) and special characters. A regular expression uses a single string to describe and match a series of strings matching a certain syntax rule, and is usually used to retrieve and replace text meeting a certain pattern (rule). For example, an ID number composed of two digits, a hyphen, and five digits is verified by using a regular expression / \d{2}-\d{5} / .

[0058] In the embodiment of the present application, the interested information is extracted by regular expression, which can effectively and accurately extract the required information from the complex data, and improve the efficiency of work order processing.

[0059] Returning to operation S230, Figure 3 The flowchart of matching the extracted interested information in the to-be-processed work order with the information in the pre-constructed knowledge base is shown schematically according to the embodiment of the present application. It includes operation S310 and operation S320.

[0060] In operation S310, the data table table name is matched with the table names of the M summary data tables stored in the knowledge base one by one.

[0061] In the embodiment of the present application, when the interested information includes the data table table name, the data table table name is matched with the table names of the M summary data tables stored in the knowledge base one by one, and P summary data tables matching the data table table name in the knowledge base are obtained. For example, a to-be-processed work order is a mortgage loan service of a company, and the interested information obtained in the work order problem is the information of the legal person client of the company, which includes the database table name "legal person client information table", and then the summary tables matching the table name are matched one by one from the knowledge base.

[0062] In operation S320, the data table field name is matched with the field names of the M summary data tables stored in the knowledge base one by one.

[0063] In the embodiment of the present application, when the interested information includes the data table field name, the data table field name is matched with the field names of the M summary data tables stored in the knowledge base one by one, and P summary data tables matching the data table field name in the knowledge base are obtained. For example, a to-be-processed work order is a regular financial product service of a person, and the interested information obtained in the work order problem is the name of the financial product, which includes the database field name "financial product name", and then the summary tables matching the field name are matched one by one from the knowledge base.

[0064] In the embodiment of the present application, by matching the table name and the field name included in the interested information with the table name and the field of the data table in the knowledge base one by one, the required data information can be matched quickly and accurately on the basis of ensuring that the data information related to the interested information in the knowledge base is not missed.

[0065] Figure 4 The flowchart of pre-constructing the knowledge base according to the embodiment of the present application is shown schematically. It includes operation S410 to operation S440.

[0066] In operation S410, target script data is obtained.

[0067] In an embodiment of the present application, a large amount of data summary scripts are stored in the data warehouse, and the scripts contain a large amount of data information and processing logic. The processing logic is summarized by developers of various applications, data analysts, etc. in combination with business experience and data between various tables in the data lake, and has certain expert rules. In an embodiment of the present application, the target script data includes scripts related to building the summary data table.

[0068] In operation S420, the target script data is parsed to extract the table name and field name of the summary data table.

[0069] In an embodiment of the present application, the summary table is created using the creat statement, the database table used for summarizing data in the script is extracted, and all information such as the table name and field name is obtained.

[0070] In operation S430, the target script data is parsed to extract the association information of the summary data table.

[0071] In operation S440, a knowledge base is constructed.

[0072] In an embodiment of the present application, the relationship information obtained through operation S420 is combined with the field information obtained through operation S430, and the relationship between the summary table and the base table and the corresponding field information are stored as knowledge to construct a corresponding knowledge base. For example, a summary table includes a legal person customer information table, and the base tables associated with the summary table include a legal person customer bank card information table, a legal person customer deposit information table, and a legal person customer intermediary business table. The association information and the corresponding field information of the summary table and the base table are saved to the database, and a corresponding knowledge base is constructed by storing a large amount of similar information.

[0073] In an embodiment of the present application, by analyzing the data warehouse related script logs, a knowledge base of the relationship between the summary table and the base table and the field information is constructed, and the problem of knowledge silos is solved. The business personnel are provided with a direct and accurate knowledge source for solving work order problems.

[0074] Returning to operation S430, the target script data is parsed to extract the association information of the summary data table, which includes searching for an insert operation in the target script data and extracting the association information between the summary data table and the base data table according to the searched insert operation.

[0075] In an embodiment of the present application, the field of the summary table is created, and the information of the field is all derived from the insert operation of the base table, i.e. the Insert operation. By searching for the Insert operation, the summary table and the base table can be associated, and the relationship between the summary table and the base table can be found and extracted.

[0076] In the embodiments of the present application, the relationship between the summary table and the base table can be accurately and quickly found and extracted from the script through the retrieval insertion operation, which ensures the accuracy of the extracted information and improves the efficiency of the knowledge base construction.

[0077] Returning to operation S210, before extracting the information of interest in the to-be-processed work order, the to-be-processed work order is classified by using a pre-trained machine learning classification model.

[0078] In the embodiments of the present application, the work order problem is first classified by using a Turing machine learning platform. Specifically, a FastText algorithm is used to train a field classification model, which can effectively identify the type of work order problem according to the user description, thereby realizing pre-classification of the work order. The pre-classification of the work order includes big data work order, platform problem work order, research and development demand work order, artificial intelligence work order, etc.

[0079] In the embodiments of the present application, the work order to be processed by the business personnel is a big data work order. Pre-classification of the work order by using the machine learning classification model can effectively filter out the big data work order, thereby improving the efficiency of work order processing.

[0080] Figure 5 An illustrative structural block diagram of the device of the work order processing user according to the embodiments of the present application is shown.

[0081] As shown in Figure 5 The device 500 of the work order processing user according to the embodiments includes a work order acquisition module 510, an information extraction module 520, a matching module 530, and an output module 540.

[0082] The work order acquisition module 510 can be used to acquire a to-be-processed work order, wherein the to-be-processed work order includes a business problem and a problem description of the business problem, and the business problem includes a business problem related to a summary data table in a database. In the embodiments of the present application, the work order acquisition module 510 can be used to perform the operation S210 described above, and details are not repeated here.

[0083] The information extraction module 520 can be used to extract information of interest in the to-be-processed work order, wherein the information of interest includes at least one of a data table name and a field name in a data table. In an embodiment, the information extraction module 520 can be used to perform the operation S220 described above, and details are not repeated here.

[0084] The matching module 530 can be configured to match the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summary data tables and field information thereof in a database, N base data tables and field information thereof in the database, and an association relationship between each of the summary data tables and K base data tables of the N base data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N. In an embodiment, the matching module 530 can be configured to perform the operation S230 described above, and details are not repeated here.

[0085] The output module 540 can be configured to output a matching result, wherein the matching result comprises P summary data tables and field information thereof in the knowledge base that match the information of interest in the to-be-processed work order, and an association relationship between each of the P summary data tables and K base data tables, P is a positive integer greater than or equal to 1 and less than or equal to M. In an embodiment, the output module 540 can be configured to perform the operation S240 described above, and details are not repeated here.

[0086] Figure 6 A block diagram of an electronic device suitable for implementing the method of processing a work order according to an embodiment of the present application is shown schematically.

[0087] As shown in Figure 6 The electronic device 600 according to an embodiment of the present application comprises a processor 601 which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 602 or loaded from a storage portion 606 into a random access memory (RAM) 603. The processor 601 can comprise, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a special-purpose microprocessor (such as an application-specific integrated circuit (ASIC)), and the like. The processor 601 can further comprise an on-board memory for cache use. The processor 601 can comprise a single processing unit or multiple processing units for performing different actions of the method processes according to embodiments of the present application.

[0088] In the RAM 603, various programs and data required for the operation of the electronic device 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via the bus 604. The processor 601 performs various operations of the method flow according to the embodiments of the present application by executing the programs in the ROM 602 and / or the RAM 603. It should be noted that the programs can also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 can also perform various operations of the method flow according to the embodiments of the present application by executing the programs stored in the one or more memories.

[0089] According to the embodiments of the present application, the electronic device 600 can further include an input / output (I / O) interface 608, which is also connected to the bus 604. The electronic device 600 can further include one or more of the following components connected to the I / O interface 608: an input part 608 including a keyboard, a mouse, etc.; an output part 608 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 608 including a hard disk, etc.; and a communication part 608 including a network interface card such as a LAN card, a modem, etc. The communication part 808 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 608 as necessary. A removable recording medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 610 as necessary, so that a computer program read out therefrom is installed in the storage part 608 as necessary.

[0090] The present application also provides a computer readable storage medium, which can be included in the device / apparatus / system described in the above embodiments; or can exist separately without being assembled into the device / apparatus / system. The above computer readable storage medium carries one or more programs, which when executed, implement the method according to the embodiments of the present application.

[0091] According to an embodiment of the present application, the computer readable storage medium can be a non-transitory computer readable storage medium, for example, can include but not limited to: 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), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present application, the computer readable storage medium can include one or more memories of the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603.

[0092] Embodiments of the present application also include a computer program product that includes a computer program containing program code for executing the methods illustrated in the flowcharts. When the computer program product is run in a computer system, the program code is used to cause the computer system to implement the methods provided by the embodiments of the present application.

[0093] The above-described functions defined in the system / device of the embodiments of the present application are performed when the computer program is executed by the processor 601. According to an embodiment of the present application, the system, device, module, unit, etc. described above can be implemented by computer program modules.

[0094] In one embodiment, the computer program can rely on tangible storage media such as optical storage media, magnetic storage media, etc. In another embodiment, the computer program can also be transmitted, distributed, and downloaded in the form of a signal on a network medium and installed and downloaded through the communication part 608 and / or installed from the detachable medium 611. The program code contained in the computer program can be transmitted by any suitable network medium, including but not limited to wireless, wired, etc., or any suitable combination of the foregoing.

[0095] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 608 and / or installed from the detachable medium 611. When the computer program is executed by the processor 601, the above-described functions defined in the system of the embodiments of the present application are performed. According to an embodiment of the present application, the system, device, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0096] According to an embodiment of the present application, program code for implementing the methods of embodiments of the present application can be written in any combination of one or more programming languages, including a high-level procedural and / or object oriented programming language, and / or an assembly / machine language. Program code can execute entirely on a user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider (ISP). It will be appreciated that program code for implementing embodiments of the present application can be provided on a computer readable medium, which can be any medium, including a magnetic, optical, or semiconductor storage device, including a hard disk, compact disk, DVD, memory stick, etc.

[0097] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0098] The embodiments of the present application described above are merely intended to illustrate the present application. These embodiments are merely for illustrative purposes, and are not intended to limit the scope of the present application. Although each of the embodiments is described above separately, this does not mean that the measures in each of the embodiments cannot be used advantageously in combination. Various alternatives and modifications can be made to the embodiments of the present application by those skilled in the art without departing from the scope of the present application, and such alternatives and modifications shall fall within the scope of the present application.

Claims

1. A work order processing method, characterized by, The method comprises: obtaining a to-be-processed work order, wherein the to-be-processed work order comprises a business problem and a problem description of the business problem, and the business problem comprises a business problem related to a summary data table in a database; extracting information of interest in the to-be-processed work order, wherein the information of interest comprises at least one of a data table table name and a field name in a data table; matching the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summary data tables in the database and field information thereof, N basic data tables in the database and field information thereof, and an association relationship between each of the summary data tables and K basic data tables of the N basic data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N; and outputting a matching result, wherein the matching result comprises: P summary data tables and field information thereof in the knowledge base that match the information of interest in the to-be-processed work order; and an association relationship between each of the P summary data tables and the K basic data tables, P is a positive integer greater than or equal to 1 and less than or equal to M; wherein the pre-constructed knowledge base comprises: obtaining target script data, wherein the target script data comprises a script related to constructing the summary data table; performing syntax analysis on the target script data to extract information of the summary data table, wherein the information of the summary data table comprises a table name and a field name of the summary data table; performing syntax analysis on the target script data to extract association information between the summary data table and a basic data table; and constructing a knowledge base according to the extracted information of the summary data table and the association information between the summary data table and the basic data table.

2. The method of claim 1, wherein, The extracting of the information of interest in the to-be-processed work order comprises: extracting, by using a regular expression, a data table table name and / or a field name appearing in the business problem and the problem description as the information of interest.

3. The method of claim 2, wherein, The matching of the extracted information of interest in the to-be-processed work order with information in the pre-constructed knowledge base comprises: in a case where the information of interest comprises a data table table name, matching the data table table name with table names of M summary data tables stored in the knowledge base one by one to obtain P summary data tables in the knowledge base that match the data table table name.

4. The method of claim 2, wherein, The matching of the extracted information of interest in the to-be-processed work order with information in the pre-constructed knowledge base comprises: in a case where the information of interest comprises a data table field name, matching the data table field name with field names of M summary data tables stored in the knowledge base one by one to obtain P summary data tables in the knowledge base that match the data table field name.

5. The method of claim 1, wherein, The performing of syntax analysis on the target script data to extract association information between the summary data table and a basic data table comprises: searching for an insert operation in the target script data; and According to the retrieved insert operation, association information between the summary data table and the base data table is extracted.

6. The method according to any one of claims 1-5, characterized in that, Before extracting the information of interest in the to-be-processed work order, the method further includes: classifying the to-be-processed work order by using a pre-trained machine learning classification model. The extracting the information of interest in the to-be-processed work order includes: in response to the to-be-processed work order being classified into a database work order category, extracting the information of interest in the to-be-processed work order.

7. A work order processing apparatus characterized by comprising: The device includes: a work order acquisition module configured to acquire a to-be-processed work order, wherein the to-be-processed work order includes a business problem and a problem description of the business problem, and the business problem includes a business problem related to a summary data table in a database; an information extraction module configured to extract information of interest in the to-be-processed work order, wherein the information of interest includes at least one of a data table table name and a field name in a data table; a matching module configured to match the extracted information of interest in the to-be-processed work order with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base includes M summary data tables in the database and field information thereof, N base data tables in the database and field information thereof, and an association relationship between each of the summary data tables and K base data tables of the N base data tables, M is a positive integer greater than or equal to 1, N is a positive integer greater than or equal to 2, and K is a positive integer greater than or equal to 1 and less than or equal to N; and an output module configured to output a matching result, wherein the matching result includes P summary data tables and field information thereof in the knowledge base that match the information of interest in the to-be-processed work order, and an association relationship between each of the P summary data tables and K base data tables, and P is a positive integer greater than or equal to 1 and less than or equal to M. The pre-constructed knowledge base includes: acquiring target script data, wherein the target script data includes a script related to constructing the summary data table; performing syntax analysis on the target script data to extract information of the summary data table, wherein the information of the summary data table includes a table name and a field name of the summary data table; performing syntax analysis on the target script data to extract association information between the summary data table and a base data table; and constructing a knowledge base according to the extracted information of the summary data table and the association information between the summary data table and the base data table.

8. An electronic device, comprising: one or more processors; a storage device for storing 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 according to any one of claims 1-6.

9. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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