CN112800739A - Excel-based standing book generation method and device and electronic equipment - Google Patents
Excel-based standing book generation method and device and electronic equipment Download PDFInfo
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Abstract
One or more embodiments of the present specification provide a method, an apparatus, and an electronic device for generating a ledger based on Excel, where the method for generating includes acquiring original data; inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions; calculating the amount of the income increase and the expenditure saving of the amount data according to the audit items, the audit item records, the policy basis and the audit processing suggestions; and inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the additional income and expenditure amount into an initial template, and outputting the ledger meeting the requirements of the client. According to the embodiment of the invention, the keyword can be accurately extracted from the data through the pre-trained machine learning algorithm model, and the extracted keyword is input into the matched initial template, so that the code is prevented from being modified again, and the diversity of the Excel template is effectively improved.
Description
Technical Field
One or more embodiments of the present specification relate to the technical field of data processing, and in particular, to a method and an apparatus for generating a ledger based on Excel, and an electronic device.
Background
In daily office, data needing to be processed in batch is often arranged by using Excel forms, when the data are processed in batch, an Excel form template needs to be established in advance, and then the data needing to be processed are imported into the established Excel form template.
In the prior art, an Excel template is established according to the requirements of a client, data to be processed is processed and input into the template, and a data definition Excel document is obtained.
The inventor finds that in the prior art, an Excel document generally adopts a fixed template, the template can only display documents with single requirements, the diversity of the template is low, when the requirements of a client are changed, a code needs to be modified to load a new document template, and the requirement of the client on the diversity of the Excel template cannot be met.
Disclosure of Invention
In view of this, one or more embodiments of the present disclosure provide a method, an apparatus, and an electronic device for generating a ledger based on Excel, so as to solve the problem of uniqueness of an Excel template.
In view of the above, one or more embodiments of the present specification provide a method for generating an account based on Excel, including:
acquiring original data;
inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions;
calculating the amount of the income increase and the expenditure saving of the amount data according to the audit items, the audit item records, the policy basis and the audit processing suggestions;
and inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the additional income and expenditure amount into an initial template, and outputting the ledger meeting the requirements of the client.
As an optional implementation, the machine learning algorithm model is a decision tree algorithm model;
the training method of the machine learning algorithm model comprises the following steps:
acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data;
and obtaining a trained decision tree model.
As an alternative embodiment, the initial template includes a fill space with audit entries, audit entry records, policy grounds, audit process recommendations, the amount of the additional savings and the raw data information.
As an optional implementation manner, data transmission of the generation method adopts Java technology.
Corresponding to the generation method, an embodiment of the present invention further provides an Excel-based machine account generation apparatus, which is characterized by including:
the first acquisition module is used for acquiring original data;
the first calculation module is used for inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions;
the second calculation module is used for calculating the income increasing and expenditure saving amount of the amount data according to the audit item, the audit item record, the policy basis and the audit processing suggestion;
and the output module is used for inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the income-increasing and expenditure-reducing amount into an initial template and outputting the ledger meeting the requirements of the client.
As an optional implementation, the machine learning algorithm model is a decision tree algorithm model;
the generating means further comprises:
the second acquisition module is used for acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
the training module is used for selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data exist;
and the obtaining module is used for obtaining the trained decision tree model.
As an optional implementation manner, the initial template includes a unit to be filled in, which is used for filling out audit items, audit item records, policy bases, audit processing suggestions, income increasing and saving amounts and original data information.
As an optional implementation manner, the generating device further includes a data transmission unit, and the data transmission unit transmits data by using Java technology.
Corresponding to the above generation method, an embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the above method.
As can be seen from the above, according to the method, the device and the electronic device for generating an Excel-based ledger provided by one or more embodiments of the present specification, through a pre-trained machine learning algorithm model, keywords can be accurately extracted from data, and the extracted keywords are input into a matched initial template, so that code re-modification is avoided, and the diversity of the Excel template is effectively improved.
Drawings
In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only one or more embodiments of the present specification, and that other drawings may be obtained by those skilled in the art without inventive effort from these drawings.
FIG. 1 is a schematic illustration of a method of generation according to one or more embodiments of the present disclosure;
FIG. 2 is a schematic diagram of a generating device according to one or more embodiments of the present disclosure;
FIG. 3 is a schematic view of an electronic device of one or more embodiments of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the present disclosure more apparent, the present disclosure is further described in detail below with reference to specific embodiments.
In order to achieve the above object, an embodiment of the present invention provides a method for generating a ledger based on Excel, including:
acquiring original data;
inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions;
calculating the amount of the income increase and the expenditure saving of the amount data according to the audit items, the audit item records, the policy basis and the audit processing suggestions;
and inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the additional income and expenditure amount into an initial template, and outputting the ledger meeting the requirements of the client.
In the embodiment of the invention, aiming at the original data, the audit items, the audit item records, the policy basis and the audit processing suggestion in the original data can be extracted, the income increasing and expenditure saving amount is calculated according to the extracted content, and then the extracted content and the calculation result are input into the initial template, thereby outputting the ledger meeting the requirements of the client. In the embodiment of the invention, the pre-trained machine learning algorithm model can accurately extract the keywords from the data, and the extracted keywords are input into the matched initial template, so that the code is prevented from being modified again, and the diversity of the Excel template is effectively improved.
Referring to fig. 1, an embodiment of the present invention provides a method for generating a standing book based on Excel, including:
and S100, acquiring original data.
Optionally, the original data is edited by the manuscript data filled by the client, so as to form original data in the form of SQL data.
S200, inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions.
As an optional implementation, the machine learning algorithm model is a decision tree algorithm model;
the training method of the machine learning algorithm model comprises the following steps:
acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data;
and obtaining a trained decision tree model.
Optionally, the contents provided in the data set are classified, the classification result is used as a node, and the classification level size is used as a feature set to classify the node, for example, the first class classification and the second class classification are performed, where the first class classification may include a triple one-decision mechanism, a decision program, a major decision item, a triple one-decision mechanism and other, and the second class classification is used as a child node of the first class classification.
As an optional implementation manner, data transmission of the generation method adopts Java technology.
Optionally, according to the text content filled by the user, an OutputMessage interface function is written by using a JavaScript technology, data is transmitted to a background database, meanwhile, a corresponding SQL statement automatically generated in a program is transmitted to a background, information extraction is performed by using a machine learning algorithm model, and then the extracted information is converted, transmitted and built in an Excel template by using an inputmessage interface function.
And S300, calculating the income increasing and saving amount of the amount data according to the audit item, the audit item record, the policy basis and the audit processing suggestion.
And S400, inputting the audit matters, the audit matter records, the policy basis, the audit processing proposal and the income increasing and saving amount into an initial template, and outputting the ledger meeting the requirements of the client.
As an alternative embodiment, the initial template includes a fill space with audit entries, audit entry records, policy grounds, audit process recommendations, the amount of the additional savings and the raw data information.
Optionally, different types of original templates are matched according to different customer requirements, and the obtained information is imported into the template to obtain an Excel template meeting customer requirements.
It should be noted that the method of one or more embodiments of the present disclosure may be performed by a single device, such as a computer or server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the devices may perform only one or more steps of the method of one or more embodiments of the present disclosure, and the devices may interact with each other to complete the method.
Based on any one of the embodiments of the method for generating a standing book described above, the present invention further provides an apparatus for generating a standing book based on Excel, as shown in fig. 2, including:
a first obtaining module 10, configured to obtain original data;
the first calculation module 20 is configured to input the original data into a trained machine learning algorithm model, and obtain audit items, audit item records, policy bases, and audit processing suggestions;
the second calculation module 30 is used for calculating the amount of the income increase and the expenditure reduction of the amount data according to the audit items, the audit item records, the policy basis and the audit processing suggestions;
and the output module 40 is used for inputting the audit matters, the audit matter records, the policy basis, the audit processing proposal and the income-increasing and expenditure-reducing amount into an initial template and outputting the ledger meeting the requirements of the client.
In the embodiment of the invention, aiming at the original data, the audit items, the audit item records, the policy basis and the audit processing suggestion in the original data can be extracted, the income increasing and expenditure saving amount is calculated according to the extracted content, and then the extracted content and the calculation result are input into the initial template, thereby outputting the ledger meeting the requirements of the client. In the embodiment of the invention, the pre-trained machine learning algorithm model can accurately extract the keywords from the data, and the extracted keywords are input into the matched initial template, so that the code is prevented from being modified again, and the diversity of the Excel template is effectively improved.
As an optional implementation, the machine learning algorithm model is a decision tree algorithm model;
the generating means further comprises:
the second acquisition module is used for acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
the training module is used for selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data exist;
and the obtaining module is used for obtaining the trained decision tree model.
As an optional implementation manner, the initial template includes a unit to be filled in, which is used for filling out audit items, audit item records, policy bases, audit processing suggestions, income increasing and saving amounts and original data information.
As an optional implementation manner, the generating device further includes a data transmission unit, and the data transmission unit transmits data by using Java technology.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in one or more embodiments of the specification is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
Based on any one of the embodiments of the method for generating the standing book, the present invention further provides a more specific hardware structure diagram of an electronic device, as shown in fig. 3, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (random access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the spirit of the present disclosure, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present description as described above, which are not provided in detail for the sake of brevity.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of one or more embodiments of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (9)
1. A generation method of an Excel-based standing book is characterized by comprising the following steps:
acquiring original data;
inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions;
calculating the amount of the income increase and the expenditure saving of the amount data according to the audit items, the audit item records, the policy basis and the audit processing suggestions;
and inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the additional income and expenditure amount into an initial template, and outputting the ledger meeting the requirements of the client.
2. The Excel-based standing book generation method according to claim 1, characterized in that the machine learning algorithm model is a decision tree algorithm model;
the training method of the machine learning algorithm model comprises the following steps:
acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data;
and obtaining a trained decision tree model.
3. The method for generating an Excel-based ledger according to claim 1, characterized in that the initial template includes a filling space with audit matters, audit matter records, policy grounds, audit processing suggestions, earnings and savings amounts and raw data information.
4. The Excel-based standing book generation method according to claim 1, characterized in that data transmission of the generation method employs Java technology.
5. An Excel-based machine account generation device is characterized by comprising:
the first acquisition module is used for acquiring original data;
the first calculation module is used for inputting the original data into a trained machine learning algorithm model to obtain audit items, audit item records, policy bases and audit processing suggestions;
the second calculation module is used for calculating the income increasing and expenditure saving amount of the amount data according to the audit item, the audit item record, the policy basis and the audit processing suggestion;
and the output module is used for inputting the audit items, the audit item records, the policy basis, the audit processing proposal and the income-increasing and expenditure-reducing amount into an initial template and outputting the ledger meeting the requirements of the client.
6. The Excel-based standing book generation apparatus in accordance with claim 5, wherein the machine learning algorithm model is a decision tree algorithm model;
the generating means further comprises:
the second acquisition module is used for acquiring a training set, wherein the training set comprises training data with audit items, audit item records, policy bases and audit processing suggestions;
the training module is used for selecting feature sets from the training set, taking the optimal feature set as a first leaf node, taking other feature sets as a second leaf node or a third leaf node, and traversing until all the leaf nodes output or no data exist;
and the obtaining module is used for obtaining the trained decision tree model.
7. The Excel-based ledger generation apparatus according to claim 5, wherein the initial template includes a unit to be filled in, and the unit to be filled in is used for filling in audit matters, audit matter records, policy bases, audit processing suggestions, income-increasing and expenditure-reducing amounts and original data information.
8. The Excel-based ledger generation apparatus according to claim 5, characterized in that, the generation apparatus further comprises a data transmission unit, and the data transmission unit adopts Java technology for data transmission.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 4 when executing the program.
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