CN117033431A - Work order processing method, device, electronic equipment and medium - Google Patents
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Abstract
The method, the device, the electronic equipment and the medium for processing the user by the work order can be applied to the technical field of big data and the technical field of information. The method comprises the following steps: acquiring a work order to be processed, extracting the information of interest in the work order to be processed, matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises a summary data table and field information thereof in a database, a basic data table and field information thereof and association relations between basic data tables in each summary data table and basic data table, and finally outputting a matching result. The processing logic of summarized data is automatically summarized, the data relation knowledge is collected, a corresponding data knowledge base is established, meanwhile, matching of the information of interest and summarized data information is set based on the knowledge base, automatic response of a big data work order is completed, efficiency of big data support staff is released, and work order conversion and closed loop efficiency are accelerated.
Description
Technical Field
The present invention relates to the field of big data technology and the field of information technology, and more particularly, to a method, an apparatus, an electronic device, and a medium for processing a work order.
Background
In the digital economic era, how to convert data elements into data assets and further drive business innovation development by using the data assets has become an important exploration direction of bank digital transformation. The multi-source data can enter the lake in one-stop mode, the problem of data sharing is solved, the data warehouse aggregates the data through aggregation of certain rules, a topic model is built, and aggregation tables corresponding to topics are stored in the model, so that analysts and non-analysts can conveniently and quickly inquire, and great convenience is brought to branch business personnel and data analysts.
While the data warehouse establishes a mapping relationship between multiple tables, the processing logic between the summary table and the underlying tables is only known to each application developer and the data warehouse operation and maintenance developer, and the data of the summary table may originate from multiple applications, thereby forming a knowledge island. In an actual business scenario, business personnel need to customize and process by combining a basic table of data sources on the basis of knowing the summary table. In the present stage, if the business personnel need to know the processing logic and field information of the summary list and the basic list, the large data mailbox needs to acquire the help of the support personnel in a mode of submitting the work list, the support personnel need to contact each application developer to know the processing logic, and the related information is synchronously given to the business personnel to complete the work list closed loop, so that huge burden and pressure are brought to the support personnel and the business personnel.
At present, most work order problems are solved by supporting personnel through personal accumulated experience or a mode of providing logic processing scripts by contacting corresponding application developers, and the processing logics of related summary tables and basic tables are formed as knowledge to be maintained in communities or other sharing media by combining historical work order to carry out manual summary. Although the method can solve the problem of knowledge island to a certain extent, the method is difficult to form scale effect, the cost of manually maintaining the knowledge base is too high, the requirement on data is changed in actual business work, the construction of related applications is also changed, how to efficiently establish the relationship knowledge to form the knowledge base, and how to quickly complete the retrieval of the knowledge base and complete automatic response in big data support work is a problem to be solved.
Disclosure of Invention
In view of the foregoing, according to a first aspect of the present invention, an embodiment of the present invention provides a method for processing a user with a work order, the method including: acquiring a work order to be processed, wherein the work order to be processed comprises a service problem and a problem description of the service problem, and the service problem comprises a service problem related to an assembly data table in a database; extracting the information of interest in the work order to be processed, wherein the information of interest comprises at least one of a data table name and a field name in a data table; matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summarized data tables and field information thereof in a database, N basic data tables and field information thereof in the database and association relations between each summarized data table and K basic data tables in 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 summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
According to some example embodiments, the extracting the information of interest in the work order to be processed comprises: and extracting the table names and/or field names of the data tables appearing in the business problems and the problem descriptions by using regular expressions as the information of interest.
According to some exemplary embodiments, the matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base includes: and under the condition that the information of interest comprises data table names, the data table names are matched with the table names of the M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the data table names in the knowledge base are obtained.
According to some exemplary embodiments, the matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base includes: and under the condition that the information of interest comprises data table field names, the data table field names are matched with the field names of M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the data table field names in the knowledge base are obtained.
According to some exemplary embodiments, pre-building the knowledge base comprises: obtaining target script data, wherein the target script data comprises scripts related to constructing the assembly data table; carrying out grammar analysis on the target script data, and extracting information of a summarized data table, wherein the information of the summarized data table comprises table names and field names of the summarized data table; carrying out grammar analysis on the target script data, and extracting association information between a summary data table and a basic data table; and constructing a knowledge base according to the extracted information of the summarized data table and the association information between the summarized data table and the basic data table.
According to some exemplary embodiments, the parsing the target script data, extracting association information between the summary data table and the base data table includes: retrieving an insert operation in the target script data; and extracting association information between the summary data table and the base data table according to the retrieved insertion operation.
According to some example embodiments, before extracting the information of interest in the work order to be processed, the method further comprises: classifying the work orders to be processed by utilizing a pre-trained machine learning classification model; the extracting the information of interest in the work order to be processed comprises the following steps: and extracting the information of interest in the work order to be processed in response to the work order to be processed being classified into a database work order category.
According to a second aspect of the present invention there is also provided an apparatus for processing a user with a work order, the apparatus comprising: the system comprises a work order acquisition module, a database and a processing module, wherein the work order acquisition module is used for acquiring a work order to be processed, the work order to be processed comprises a service problem and a problem description of the service problem, and the service problem comprises a service problem related to an assembly total data table in the database; the information extraction module is used for extracting the information of interest in the work order to be processed, wherein the information of interest comprises at least one of a data table name and a field name in the data table; the matching module is used for matching the extracted information of interest in the work order to be processed with information in a pre-built knowledge base, wherein the pre-built knowledge base comprises M summarized data tables and field information thereof in a database, N basic data tables and field information thereof in the database and association relations between each summarized data table and K basic data tables in 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 an output module for outputting a matching result, wherein the matching result comprises: p summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
According to a third aspect of the present invention, there is provided an electronic device comprising: one or more processors; and 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.
According to a fourth aspect of the present invention there is provided a computer readable storage medium having stored thereon executable instructions which when executed by a processor cause the processor to perform a method as described above.
According to a fifth aspect of the present invention there is provided a computer program product comprising a computer program which, when executed by a processor, implements a method as described above.
One or more of the above embodiments have the following advantages or benefits: the processing logic of summarized data is automatically summarized, the data relation knowledge is collected, a corresponding data knowledge base is established, meanwhile, matching of the information of interest and summarized data information is set based on the knowledge base, automatic response of a big data work order is completed, efficiency of big data support staff is released, and work order conversion and closed loop efficiency are accelerated.
Drawings
The foregoing and other objects, features and advantages of the invention will be apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:
fig. 1 schematically illustrates an application scenario diagram of a method, an apparatus, an electronic device, and a medium for processing a user by a work order according to an embodiment of the present invention.
Fig. 2 schematically shows a flow chart of a method of processing a user with a work order according to an embodiment of the invention.
FIG. 3 schematically illustrates a flow chart for matching information of interest in an extracted work order to be processed with information in a pre-built knowledge base, in accordance with an embodiment of the invention.
Fig. 4 schematically shows a flow chart of pre-building the knowledge base according to an embodiment of the invention.
Fig. 5 schematically shows a block diagram of an apparatus for processing a user with a work order according to an embodiment of the present invention.
Fig. 6 schematically shows a block diagram of an electronic device adapted to implement a method of processing a user on a work order according to an embodiment of the invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. 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 invention. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The terms "comprises," "comprising," and/or 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 should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having 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.).
In the technical scheme of the invention, the acquisition, storage, application and the like of the related personal information of the user accord with the regulations of related laws and regulations, necessary security measures are taken, and the public order harmony is not violated.
First, technical terms described herein are explained and illustrated as follows.
Work order: i.e. work orders, defining a simple maintenance or manufacturing plan consisting of one or more jobs, with the superior department issuing the task and the inferior department receiving the basis of the task.
Script: is an executable file written according to a certain format using a specific descriptive language.
Based on this, an embodiment of the present invention provides a method of a work order processing method, the method including: acquiring a work order to be processed, wherein the work order to be processed comprises a service problem and a problem description of the service problem, and the service problem comprises a service problem related to an assembly data table in a database; extracting the information of interest in the work order to be processed, wherein the information of interest comprises at least one of a data table name and a field name in a data table; matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summarized data tables and field information thereof in a database, N basic data tables and field information thereof in the database and association relations between each summarized data table and K basic data tables in 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 summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
According to the method, processing logic of summarized data is automatically summarized, data relation knowledge is collected, a corresponding data knowledge base is established, meanwhile, matching of the information of interest and summarized data information is set based on the knowledge base, automatic response of a big data work order is completed, efficiency of big data support staff is released, and work order transfer and closed loop efficiency are accelerated.
It should be noted that the work order processing method and the work order processing device determined by the invention can be used in the technical field of big data and the technical field of information.
Fig. 1 schematically illustrates an application scenario diagram of a method, an apparatus, a device, a medium for worksheet processing according to an embodiment of the present invention.
As shown in fig. 1, an application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as shopping class applications, web browser applications, search class applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only) may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that, the method for processing a work order provided by the embodiment of the present invention may be generally performed by the server 105. Accordingly, the device for processing the user by the work order provided by the embodiment of the present invention may be generally disposed in the server 105. The method for handling users by worksheets provided by the embodiments of the present invention may also be performed 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 apparatus for processing a user by using a work order provided by the embodiment of the present invention may also be provided in a server or a server cluster that is different from the server 105 and is 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.
The method for processing a user of a work order provided by an embodiment of the present invention will be described in detail with reference to fig. 2 to 6 based on the scenario described in fig. 1.
Fig. 2 schematically shows a flow chart of a method of processing a user with a work order according to an embodiment of the invention.
As shown in fig. 2, the method 200 of processing a user with a work order of this embodiment may include operations S210 to S240.
In operation S210, a work order to be processed is acquired, wherein the work order to be processed includes a business problem and a problem description for the business problem, and the business problem includes a business problem related to a total data table in a database.
In an embodiment of the present invention, the business problems include: problems involved in asset transactions, liability transactions, and intermediate transactions. The property business refers to the activities that commercial banks absorb the fund operation and earn interest income or investment income, and mainly comprises loan business, cash-on business, investment business and peer-to-peer removal business. For example, a person's credit to be transacted at a bank is a property business; the liability business refers to the act of borrowing funds with use rights by commercial banks through the compliance of financial license plates, and mainly comprises deposit (deposit) business, homonymy dismantlement and issuing bond business, for example, deposit business handled by individuals at banks belongs to one liability business; the intermediate business refers to the business bank which uses the own network, information, credit or license plate advantages outside the meter to provide the role of an intermediary or proxy for the client, and usually carries out paid services, mainly including the businesses such as guarantee, proxy, consultant, receipt and payment, and the like, for example, the periodic financial business handled by individuals at the bank belongs to an intermediate business.
In the embodiment of the invention, the description of the service problem is a specific information description of the service problem to be processed, and comprises names and/or identification numbers of specific individuals of both service parties, names and/or numbers of units, service processing time, service problem numbers and the like. For example, a person transacting a withdrawal transaction at a bank, and the description of the transaction needs to include information such as the person's name and identification number, the time and place of the transaction, the specific amount of money to be deposited, and the like.
In the embodiment of the invention, a large amount of service information and processing logic summarized by the base layer data are integrated in the database in advance, and the service information and the processing logic are summarized by the developers, data analysts and the like of each application in combination with service experience and are related to data among various tables in the database, so that the database has certain expert rules. In an embodiment of the invention, the summary data table is made based on the business information and processing logic summarized in the database.
In operation S220, information of interest in the work order to be processed is extracted, wherein the information of interest includes at least one of a table name of the data table and a field name in the data table.
In an embodiment of the invention, for example, there is a table in the database, the table name being a corporate customer unified view, the field names in the table including the names of corporate customers. The existing work order to be processed is a liability business work order of a certain company, and the information of interest in the work order comprises information such as names of corporate legal clients.
In operation S230, the extracted information of interest in the work order to be processed is matched with information in a knowledge base constructed in advance.
In an embodiment of the present invention, the pre-constructed knowledge base includes M summary data tables and field information thereof in a database, N basic data tables and field information thereof in the database, and an association relationship between each of the summary data tables and K basic data tables in the N basic data tables, where 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 operation S240, a matching result is output.
In the embodiment of the invention, the matching result comprises P summarized data tables and field information thereof matched with the information of interest in the work order to be processed in the knowledge base; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
In the embodiment of the invention, firstly, a script file which is processed by summarizing the basic data of each application is analyzed by a data warehouse, the relation between the summarized data and the basic data is established, a relational knowledge base is formed, and the problem that the logical relation of processing scripts is limited only by knowledge island mastered by developers is solved. Based on the demand of the data summary layer and the basic layer in the actual business production process, the invention provides an automatic matching method based on the relation knowledge base, which helps business personnel to quickly associate the processing logic of the data basic layer and the processing layer, and the business personnel can perform logic processing based on the processing logic, further exert the value of the data and release the potential of the use number.
Returning to operation S220, the extracting the information of interest in the work order to be processed includes extracting, as the information of interest, table names and/or field names of the data tables appearing in the business problem and the problem description using regular expressions.
In an embodiment of the present invention, a regular expression, also known as a regular expression, is a text pattern that includes common characters (e.g., letters between a and z) and special characters. Regular expressions use a single string to describe, match a series of strings that match a certain syntactic rule, and are typically used to retrieve, replace, text that meets a certain pattern (rule). For example, an ID number consisting of two digits, one hyphen plus 5 digits is verified using the regular expression/\d {2} - \d {5 }.
In the embodiment of the invention, the information of interest can be extracted through the regular expression, so that the required information can be extracted from the vast and miscellaneous data effectively and accurately, and the efficiency of work order processing is improved.
Returning to operation S230, fig. 3 schematically illustrates a flowchart for matching the information of interest in the extracted work order to be processed with the information in the pre-constructed knowledge base according to an embodiment of the present invention. Including operation S310 and operation S320.
In operation S310, table names of the data tables are matched with table names of M summary data tables stored in the knowledge base one by one.
In the embodiment of the invention, when the information of interest includes table names of data tables, the table names of the data tables are matched with the table names of M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the table names of the data tables in the knowledge base are obtained. For example, a work order to be processed is a mortgage loan service of a company, and the information of interest is obtained as corporate legal customer information in the work order problem, wherein the information of interest comprises a database table name of "legal customer information table", and summary tables matched with the table names are matched one by one from a knowledge base.
In operation S320, the table field names are matched with the table names of the M summary data tables stored in the knowledge base one by one.
In the embodiment of the invention, under the condition that the information of interest comprises data table field names, the data table field names are matched with the field names of M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the data table field names in the knowledge base are obtained. For example, a work order to be processed is a periodic financial service of a person, information of interest is acquired as a financial product name in the work order problem, the information of interest comprises a database field name of financial product name, and summary tables matched with the field name are matched one by one from a knowledge base.
In the embodiment of the invention, the table names and the field names included in the information of interest are matched with the table names and the field names of the data tables in the knowledge base one by one, so that the required data information can be quickly and accurately matched on the basis of ensuring that the data information in the knowledge base related to the information of interest is not missed.
Fig. 4 schematically shows a flow chart of pre-building the knowledge base according to an embodiment of the invention. Including operations S410-S440.
In operation S410, target script data is acquired.
In the embodiment of the invention, a large number of data summarization scripts are stored in the data warehouse, and the scripts contain a large number of data information and processing logic, wherein the processing logic is summarized by the combination of service experience of developers, data analysts and the like of various applications and the data among various tables in the associated data lake, and have certain expert rules. In an embodiment of the invention, the target script data includes scripts associated with building the assembly data table.
In operation S420, the target script data is parsed, and table names and field names of the summary data table are extracted.
In the embodiment of the invention, the summary table is created by using a create statement, a database table for summarizing data in the script is extracted, and all information such as table names, field names and the like of the database table is acquired.
In operation S430, the target script data is parsed, and association information of the summary data table is extracted.
In operation S440, a knowledge base is constructed.
In the embodiment of the present invention, the relationship information acquired in operation S420 is combined with the field information acquired in operation S430, and the relationship between the summary table and the base table and the corresponding field information are stored as knowledge, so as to construct a corresponding knowledge base. For example, a summary table includes a corporate customer information table, a base table associated with the summary table includes a corporate customer bank card information table, a corporate customer deposit information table, a corporate customer intermediate business table, and other base tables, and the related information and corresponding field information of the summary table and the base table are stored in a database, so that a corresponding knowledge base is constructed by storing a large amount of similar information.
In the embodiment of the invention, the knowledge base of information such as the relation and the fields of the summary table and the basic table is constructed by analyzing the script logs related to the data warehouse, so that the problems of knowledge island and the like are solved. The method provides a direct and error-free knowledge source for business personnel to solve the work order problem.
Returning to operation S430, performing syntax analysis on the target script data, and extracting association information of the summary data table includes retrieving an insert operation in the target script data and extracting association information between the summary data table and the base data table according to the retrieved insert operation.
In an embodiment of the invention, the fields created by the summary table, the information of which is derived entirely from the Insert operation of the underlying table, i.e., the Insert operation. By retrieving the Insert operation, the summary table and the base table can be associated, thereby finding and extracting the relationship between the summary table and the base table.
In the embodiment of the invention, the relation between the summary table and the basic table can be accurately and rapidly searched and extracted from the script through the search and insertion operation, so that the accuracy of the extracted information is ensured, and meanwhile, the construction efficiency of the knowledge base is improved.
Returning to operation S210, before extracting the information of interest in the work order to be processed, the method further includes classifying the work order to be processed using a pre-trained machine learning classification model.
In the embodiment of the invention, the menu problems are classified by the learning platform of the turing machine first. Specifically, a FastText algorithm is used for training a field classification model, and the model can effectively identify the problem type of the work order according to user description, so that the work order pre-classification is realized. The pre-classification of the worksheets includes big data worksheets, platform problem worksheets, development requirement worksheets, artificial intelligence worksheets and the like.
In the embodiment of the invention, the work order to be processed by the business personnel is a big data work order. The machine learning classification model is utilized to pre-classify the work orders, so that the large data work orders can be effectively screened out, and the work order processing efficiency is improved.
Fig. 5 schematically shows a block diagram of an apparatus for processing a user with a work order according to an embodiment of the present invention.
As shown in fig. 5, the apparatus 500 of the work order processing user according to the embodiment includes a work order acquisition module 510, an information extraction module 520, a matching module 530, and an output module 540.
The work order obtaining module 510 may be configured to obtain a work order to be processed, where the work order to be processed includes a business problem and a problem description for the business problem, and the business problem includes a business problem related to a total data table in a database. In an embodiment of the present invention, the worksheet obtaining module 510 may be configured to perform the operation S210 described above, which is not described herein.
The information extraction module 520 may be configured to extract information of interest in the work order to be processed, where 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 may be configured to perform the operation S220 described above, which is not described herein.
The matching module 530 may be configured to match the extracted information of interest in the work order to be processed with information in a pre-built knowledge base, where the pre-built knowledge base includes M summary data tables and field information thereof in a database, N basic data tables and field information thereof in the database, and association relations between each of the summary data tables and K basic data tables in 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. In an embodiment, the matching module 530 may be configured to perform the operation S230 described above, which is not described herein.
The output module 540 may be configured to output a matching result, where the matching result includes: p summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein 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 may be used to perform the operation S240 described above, which is not described herein.
Fig. 6 schematically shows a block diagram of an electronic device adapted to implement a method of processing a user on a work order according to an embodiment of the invention.
As shown in fig. 6, an electronic device 600 according to an embodiment of the present invention includes a processor 601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 606 into a Random Access Memory (RAM) 603. The processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. Processor 601 may also include on-board memory for caching purposes. Processor 601 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the invention.
In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. The processor 601 performs various operations of the method flow according to an embodiment of the present invention by executing programs in the ROM 602 and/or the RAM 603. Note that the program may be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the method flow according to embodiments of the present invention by executing programs stored in the one or more memories.
According to an embodiment of the invention, the electronic device 600 may also include an input/output (I/O) interface 608, the input/output (I/O) interface 608 also being connected to the bus 604. The electronic device 600 may also include one or more of the following components connected to the I/O interface 608: an input section 608 including a keyboard, a mouse, and the like; an output portion 608 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 608 including a network interface card such as a LAN card, a modem, and the like. The communication section 808 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 608 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
The present invention also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present invention.
According to embodiments of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is 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 context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the invention, the computer-readable storage medium may include ROM 602 and/or RAM 603 and/or one or more memories other than ROM 602 and RAM 603 described above.
Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the method shown in the flowcharts. The program code means for causing a computer system to carry out the methods provided by embodiments of the present invention when the computer program product is run on the computer system.
The above-described functions defined in the system/apparatus of the embodiment of the present invention are performed when the computer program is executed by the processor 601. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the invention.
In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed over a network medium in the form of signals, downloaded and installed via the communication part 608, and/or installed from the removable medium 611. The computer program may include program code that may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 608, and/or installed from the removable media 611. The above-described functions defined in the system of the embodiment of the present invention are performed when the computer program is executed by the processor 601. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the invention.
According to embodiments of the present invention, program code for carrying out computer programs provided by embodiments of the present invention may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or in assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The flowcharts 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 invention. 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.
The embodiments of the present invention are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the invention, and such alternatives and modifications are intended to fall within the scope of the invention.
Claims (11)
1. A method of worksheet processing, the method comprising:
acquiring a work order to be processed, wherein the work order to be processed comprises a service problem and a problem description of the service problem, and the service problem comprises a service problem related to an assembly data table in a database;
extracting the information of interest in the work order to be processed, wherein the information of interest comprises at least one of a data table name and a field name in a data table;
matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base, wherein the pre-constructed knowledge base comprises M summarized data tables and field information thereof in a database, N basic data tables and field information thereof in the database and association relations between each summarized data table and K basic data tables in 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 summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
2. The method of claim 1, wherein the extracting the information of interest in the work order to be processed comprises:
and extracting the table names and/or field names of the data tables appearing in the business problems and the problem descriptions by using regular expressions as the information of interest.
3. The method of claim 2, wherein the matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base comprises:
and under the condition that the information of interest comprises data table names, the data table names are matched with the table names of the M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the data table names in the knowledge base are obtained.
4. The method of claim 2, wherein the matching the extracted information of interest in the work order to be processed with information in a pre-constructed knowledge base comprises:
and under the condition that the information of interest comprises data table field names, the data table field names are matched with the field names of M summarized data tables stored in the knowledge base one by one, and P summarized data tables matched with the data table field names in the knowledge base are obtained.
5. The method of any one of claims 1-4, wherein pre-building the knowledge base comprises:
obtaining target script data, wherein the target script data comprises scripts related to constructing the assembly data table;
carrying out grammar analysis on the target script data, and extracting information of a summarized data table, wherein the information of the summarized data table comprises table names and field names of the summarized data table;
carrying out grammar analysis on the target script data, and extracting association information between a summary data table and a basic data table; and
and constructing a knowledge base according to the extracted information of the summarized data table and the association information between the summarized data table and the basic data table.
6. The method of claim 5, wherein parsing the target script data to extract association information between a summary data table and a base data table comprises:
retrieving an insert operation in the target script data; and
and extracting the association information between the summarized data table and the basic data table according to the retrieved inserting operation.
7. The method of any of claims 1-4 and 6, wherein prior to extracting the information of interest in the work order to be processed, the method further comprises: classifying the work orders to be processed by utilizing a pre-trained machine learning classification model;
the extracting the information of interest in the work order to be processed comprises the following steps: and extracting the information of interest in the work order to be processed in response to the work order to be processed being classified into a database work order category.
8. A work order processing apparatus, the apparatus comprising:
the system comprises a work order acquisition module, a database and a processing module, wherein the work order acquisition module is used for acquiring a work order to be processed, the work order to be processed comprises a service problem and a problem description of the service problem, and the service problem comprises a service problem related to an assembly total data table in the database;
the information extraction module is used for extracting the information of interest in the work order to be processed, wherein the information of interest comprises at least one of a data table name and a field name in the data table;
the matching module is used for matching the extracted information of interest in the work order to be processed with information in a pre-built knowledge base, wherein the pre-built knowledge base comprises M summarized data tables and field information thereof in a database, N basic data tables and field information thereof in the database and association relations between each summarized data table and K basic data tables in 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
the output module is used for outputting a matching result, wherein the matching result comprises: p summarized data tables matched with the information of interest in the work order to be processed in the knowledge base and field information of the P summarized data tables; and the association relation between each of the P summary data tables and the K basic data tables, wherein P is a positive integer greater than or equal to 1 and less than or equal to M.
9. An electronic device, comprising:
one or more processors;
storage means 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 of any of claims 1-7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any of claims 1-7.
11. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.
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| CN117291163B (en) * | 2023-11-24 | 2024-05-28 | 青矩技术股份有限公司 | Data extraction method, device, equipment and storage medium |
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