CN112529664A - Method and device for comparing commodities sold in advance, storage medium and electronic equipment - Google Patents
Method and device for comparing commodities sold in advance, storage medium and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to a commodity-in-sale comparison method, a commodity-in-sale comparison device, a storage medium and electronic equipment. The method comprises the following steps: acquiring all incoming invoice information and all sales invoice information of a target enterprise, wherein the incoming invoice information comprises first commodity types, and the sales invoice information comprises second commodity types; aiming at a target enterprise, sellers in all the invoice information and buyers in all the invoice information, constructing a commodity knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise; in the commodity sales knowledge graph, target second commodities which are different from the first commodities in all the second commodities are marked to be in an abnormal state, and a commodity sales comparison knowledge graph of a target enterprise is obtained. The method can intuitively display the commodity sale-sale comparison relation of the target enterprise.
Description
Technical Field
The disclosure relates to the technical field of knowledge maps, in particular to a commodity-to-stock comparison method, a commodity-to-stock comparison device, a storage medium and electronic equipment.
Background
In the related art, the tax system displays commodity sales information of a taxpayer in forms of a table, a bar graph, a sector graph, a line graph and the like, but the relationship between commodity sales cannot be visually displayed in such a manner.
Disclosure of Invention
The invention aims to provide a method and a device for comparing commodity sales, a storage medium and electronic equipment, which are used for visually displaying commodity sales comparison relations of taxpayers and enabling users to quickly acquire abnormal commodity item information from the displayed commodity sales comparison relations of the taxpayers.
In order to achieve the above object, in a first aspect of the embodiments of the present disclosure, a method for matching incoming and outgoing commodities is provided, where the method includes:
acquiring all goods incoming invoice information and all sales invoice information of a target enterprise, wherein each goods incoming invoice information comprises a first goods purchased by the target enterprise and a name of a seller enterprise selling the first goods to the target enterprise, and each sales invoice information comprises a second goods sold by the target enterprise and a name of a buyer enterprise purchasing the second goods from the target enterprise;
aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, constructing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information;
in the sales commodity knowledge graph, a target second commodity different from each first commodity in all the second commodities is marked to be in an abnormal state, and a sales commodity comparison knowledge graph of the target enterprise is obtained.
Optionally, the method further comprises:
in the comparison knowledge graph of the commodity sold, a target first commodity which is different from each second commodity in all the first commodities is marked as the abnormal state, and a new comparison knowledge graph of the commodity sold is obtained.
Optionally, the method further comprises:
determining a first sub-map comprising the target enterprise, the target second category of commodities and buyer enterprises related to the target enterprise through the target second category of commodities from the marketing commodity comparison knowledge map;
determining a second sub-map comprising the target enterprise, the target first category commodity and a seller enterprise related to the target enterprise through the target first category commodity from the sales commodity comparison knowledge map;
and taking the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
Optionally, the method further comprises:
taking all enterprises in the abnormal enterprise knowledge graph as enterprises to be checked;
and carrying out tax information inspection on each enterprise to be inspected.
Optionally, the performing tax information check on each enterprise to be checked includes:
and when the enterprise to be checked is the target enterprise, carrying out tax information check on the incoming invoice information of the target enterprise corresponding to the target first commodity and/or carrying out tax information check on the sales invoice information of the target enterprise corresponding to the target second commodity.
According to a second aspect of the embodiments of the present disclosure, there is provided a comparison apparatus for incoming and outgoing commodities, the apparatus including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire all incoming invoice information and all sales invoice information of a target enterprise, each incoming invoice information comprises a first commodity purchased by the target enterprise and a name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and a name of a buyer enterprise purchasing the second commodity from the target enterprise;
a construction module, configured to construct, for the target enterprise, all seller enterprises in all invoice information, and all buyer enterprises in all invoice information, a commodity-to-be-sold knowledge graph of the target enterprise according to first association information between the target enterprise and each seller enterprise and second association information between the target enterprise and each buyer enterprise, where the first association information is a first commodity in the invoice information, and the second association information is a second commodity in the invoice information;
the first marking module is configured to mark target second-class commodities, which are different from the first-class commodities, in all the second-class commodities as abnormal states in the marketing commodity knowledge graph, so as to obtain a marketing commodity comparison knowledge graph of the target enterprise.
Optionally, the apparatus further comprises:
the second marking module is configured to mark, in the sales commodity comparison knowledge graph, a target first commodity which is different from each second commodity in all the first commodities as the abnormal state, so as to obtain a new sales commodity comparison knowledge graph.
Optionally, the apparatus further comprises:
a first determining module configured to determine, from the comparison knowledge graph of commodities sold, a first sub-graph including the target enterprise, the target second class of commodities, and a buyer enterprise associated with the target enterprise through the target second class of commodities;
a second determining module configured to determine, from the comparison knowledge graph of the sold commodities, a second sub-graph including the target enterprise, the target first commodity and a seller enterprise associated with the target enterprise through the target first commodity;
a first execution module configured to use the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
Optionally, the apparatus further comprises:
the second execution module is configured to take each enterprise in the abnormal enterprise knowledge graph as an enterprise to be checked;
and the checking module is configured for checking the tax information of each enterprise to be checked.
Optionally, the inspection module comprises:
and the checking sub-module is configured to, when the enterprise to be checked is the target enterprise, perform tax information check on the invoice information of the target enterprise corresponding to the target first commodity, and/or perform tax information check on the invoice information of the target enterprise corresponding to the target second commodity.
According to a third aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any one of the above-mentioned first aspects.
According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the method of any of the first aspects above.
By adopting the technical scheme, the following technical effects can be at least achieved:
the method comprises the steps of obtaining all incoming invoice information and all sales invoice information of a target enterprise, wherein each incoming invoice information comprises a first commodity purchased by the target enterprise and a name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and a name of a buyer enterprise purchasing the second commodity from the target enterprise. And aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, establishing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information. In the commodity sales knowledge graph, target second commodities which are different from the first commodities in all the second commodities are marked to be in an abnormal state, and a commodity sales comparison knowledge graph of a target enterprise is obtained. The mode of displaying the commodity marketing comparison relation of the target enterprise by using the knowledge graph is more intuitive than the mode of displaying the commodity marketing information of the taxpayers in the modes of tables, column graphs, sector graphs, line graphs and the like in the related technology. In addition, the intuitive display mode enables a user to quickly determine the abnormal selling item with the abnormal state mark from the selling commodity comparison knowledge graph.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is a flowchart illustrating a method for matching items sold according to an exemplary embodiment of the present disclosure.
FIG. 2 is a diagram illustrating a commodity for sale knowledge map according to an exemplary embodiment of the present disclosure.
FIG. 3 is a diagram illustrating a comparison knowledge graph of items sold according to an exemplary embodiment of the present disclosure.
FIG. 4 is another illustration of a commodity for sale knowledge map according to an exemplary embodiment of the present disclosure.
FIG. 5 is another commodity as sold comparison knowledge graph shown in accordance with an exemplary embodiment of the present disclosure.
FIG. 6 is yet another commodity as sold comparison knowledge graph shown in accordance with an exemplary embodiment of the present disclosure.
FIG. 7 is an illustration of an abnormal enterprise knowledge graph in accordance with an exemplary embodiment of the present disclosure.
Fig. 8 is a block diagram illustrating a comparison apparatus for incoming and outgoing goods according to an exemplary embodiment of the present disclosure.
Fig. 9 is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
In the related art, the tax system displays commodity sales information of a taxpayer in forms of a table, a bar graph, a sector graph, a line graph and the like, but the commodity sales information cannot be displayed intuitively in the forms, namely, the display mode is not intuitive, the attribute is single, and the attribute of the relationship cannot be displayed. Specifically, the user needs to further analyze whether each commodity sales item of the taxpayer has an abnormality or not based on the taxpayer commodity sales information displayed in the form of a table, a bar graph, a sector graph, a line graph, and the like. It is obvious that such a manner of presenting sales information of taxpayers in the related art does not enable a user to quickly determine specific abnormal sales items from tables, bar charts, sector charts, and line charts.
In view of the above, the embodiments of the present disclosure provide a method, an apparatus, a storage medium, and an electronic device for comparing commodity sales, which utilize a knowledge graph technology and combine with invoice sales data of taxpayers to display commodity sales relationships of the taxpayers and compare the commodity sales relationships, thereby solving the problems in the related art.
Firstly, explaining an application scenario of the present disclosure, the technical scheme of the present disclosure is directed to a dealer who purchases goods and directly reshuffles the purchased goods without processing to earn a difference, generates a commodity selling comparison relation diagram of the dealer, and determines abnormal selling commodity items in each selling commodity of the dealer. Furthermore, after the abnormal commodity items sold in each commodity sold by the distributor are determined, the abnormal commodity items sold by the distributor can be finely compared, so that whether the distributor is suspected of illegal phenomena such as tax stealing, tax leakage, tax evasion, money laundering and the like can be verified.
Fig. 1 is a flowchart illustrating a method for comparing incoming and outgoing commodities according to an exemplary embodiment of the present disclosure, as shown in fig. 1, including the following steps:
s11, obtaining all incoming invoice information and all sales invoice information of a target enterprise, wherein each incoming invoice information comprises a first commodity purchased by the target enterprise and a name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and a name of a buyer enterprise purchasing the second commodity from the target enterprise.
The target enterprise goods-feeding invoice is an invoice which is issued to the target enterprise by the seller enterprise when the target enterprise purchases goods. The sales invoice of the target enterprise refers to an invoice issued by the target enterprise to the buyer enterprise when the target enterprise sells goods. Each piece of incoming invoice information and each piece of sales invoice information are information corresponding to one invoice.
It should be understood that any invoice includes a buyer name identifier, a seller name identifier, and a commodity class identifier or service identifier for the transaction. It should be noted that the transaction goods in one invoice may be one kind of goods or multiple kinds of goods.
Therefore, in step S11, each of the obtained invoice information of the target enterprise includes the first category of goods purchased by the target enterprise and the name of the seller enterprise selling the first category of goods to the target enterprise, and each of the invoice information of the target enterprise includes the second category of goods sold by the target enterprise and the name of the buyer enterprise purchasing the second category of goods from the target enterprise. The first category of goods represents goods purchased by the target enterprise, and the first category of goods may be one kind of goods or multiple kinds of goods. The second category of goods represents goods sold by the target enterprise, and the second category of goods can also be one or more. The present disclosure is not particularly limited.
S12, aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, constructing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information.
In one implementation, for each piece of incoming invoice information, the first category of goods in the incoming invoice information is used as first association information for associating the target enterprise and the seller enterprise in the incoming invoice information, so that triple data corresponding to the incoming invoice information can be obtained, namely (seller enterprise, first category of goods, target enterprise), and the triple data represents that the target enterprise purchases the first category of goods from the seller enterprise. It should be further noted that when the first category product in the piece of receipt information is A, B, C three types of products, all the triple data corresponding to the receipt information are (seller company, a, target company), (seller company, B, target company), (seller company, C, target company).
Similarly, for each piece of sales invoice information, the second category of commodity in the sales invoice information is used as second association information for associating the target enterprise and the buyer enterprise in the sales invoice information, so that ternary group data corresponding to the sales invoice information can be obtained, namely (the target enterprise, the second category of commodity and the buyer enterprise), and the ternary group data represents that the target enterprise sells the second category of commodity to the buyer enterprise. It should be noted that, when the second category product in the piece of sales invoice information is D, E, F three types of products, all the triple data corresponding to the piece of sales invoice information are (target enterprise, D, purchaser enterprise), (target enterprise, E, purchaser enterprise), (target enterprise, F, purchaser enterprise).
Further, aiming at the target enterprise, all seller enterprises in all the invoice information and all buyer enterprises in all the invoice information, the commodity-to-be-sold knowledge graph of the target enterprise can be constructed according to the first correlation information between the target enterprise and each seller enterprise and the second correlation information between the target enterprise and each buyer enterprise. In detail, the specific implementation of generating the knowledge graph of the commodity sold is similar to the method for generating the knowledge graph based on the triple data in the related art, and details are not repeated here.
For example, assume that the target business has three incoming invoices and two sales invoices in total. The first invoice is an invoice which is provided by a seller enterprise 1 and sells first-class commodities to a target enterprise in gold, the second invoice is an invoice which is provided by a seller enterprise 2 and sells the first-class commodities to the target enterprise in gold, the third invoice is an invoice which is provided by a seller enterprise 3 and sells the first-class commodities to the target enterprise in gold, the first invoice is an invoice which is provided by the target enterprise and sells the second-class commodities to a buyer enterprise 1 in gold, and the second invoice is an invoice which is provided by the target enterprise and sells the second-class commodities to the buyer enterprise 2 by a mobile phone. Based on the manner of step S12, a commodity-for-sale knowledge map of the target enterprise as shown in fig. 2 can be obtained.
And S13, in the sales commodity knowledge graph, marking target second commodity different from the first commodities in all the second commodities as an abnormal state to obtain a sales commodity comparison knowledge graph of the target enterprise.
The identification mode of the abnormal state can be highlight, red mark, symbol mark and the like. The present disclosure is not particularly limited thereto. Also, the present disclosure does not limit the number of product types of the target second product.
For example, with reference to fig. 2, all the second-class commodities, that is, gold and the target second-class commodities, which are different from the first-class commodity in gold, in the mobile phone are marked as an abnormal state, so that the comparison knowledge graph of the incoming and outgoing commodities shown in fig. 3 can be obtained. In fig. 3, the target second-category product mobile phone is marked for an abnormal state in a dotted line marking manner.
Optionally, the target second category commodity marked as the abnormal state in the comparison knowledge graph of the commodity sold and sold is used as an abnormal comparison result item of the commodity sold and sold of the target enterprise. Specifically, the target second commodity marked as an abnormal state in the commodity comparison knowledge graph is used as an abnormal commodity item for sale of the target enterprise.
By adopting the method, all the incoming invoice information and all the sales invoice information of the target enterprise are obtained, wherein each incoming invoice information comprises a first commodity purchased by the target enterprise and the name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and the name of a buyer enterprise purchasing the second commodity from the target enterprise. And aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, establishing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information. In the commodity sales knowledge graph, target second commodities which are different from the first commodities in all the second commodities are marked to be in an abnormal state, and the commodity sales comparison knowledge graph of the target enterprise is obtained. The mode of displaying the commodity marketing comparison relation of the target enterprise by using the knowledge graph is more intuitive than the mode of displaying the commodity marketing information of the taxpayers in the modes of tables, column graphs, sector graphs, line graphs and the like in the related technology. In addition, the intuitive display mode enables a user to quickly determine the abnormal selling item with the abnormal state mark from the selling commodity comparison knowledge graph. The problem of low-efficiency processing of further analyzing whether each commodity sales entry of the taxpayer is abnormal or not based on the taxpayer commodity sales entry information displayed in the forms of tables, column graphs, sector graphs, line graphs and the like in the related technology is solved.
In an implementation manner, the step S13 may be replaced by labeling, in the sales commodity knowledge graph, a target first commodity different from each second commodity in all the first commodities as the abnormal state, and obtaining the sales commodity comparison knowledge graph.
For example, assuming that the commodity-to-be-sold map of the target enterprise is shown in fig. 4, in the commodity-to-be-sold map, the target first-class commodity watch different from each second-class commodity in all the first-class commodities is marked as an abnormal state, and the commodity-to-be-sold comparison map shown in fig. 5 can be obtained. Based on fig. 5, the target first category commodity watch marked as abnormal state in the comparison commodity comparison knowledge graph can be used as an abnormal commodity item of the target enterprise.
Here, the target first product and the target second product marked as abnormal states are products that may have an illegal operation, and are not necessarily products that have an illegal operation. The target first-class commodity marked as abnormal state in the comparison knowledge graph of the commodity sold and sold of the target enterprise may be a commodity abnormally stocked and pressed by the target enterprise, and of course, may also be a commodity used as the welfare of internal employees.
By adopting the method, partial inlet and outlet commodity items without violation can be eliminated from the inlet and outlet commodities with complicated types of the target enterprises, and all inlet and outlet commodity items with possible violation can be determined. Therefore, in the application scene of verifying whether the target enterprise is suspected of illegal phenomena such as tax evasion, tax leakage, tax evasion, money laundering and the like, the mode can effectively reduce the workload of illegal commodity inspection.
Optionally, S13 in the method for comparing the sold commodities may further include:
in the comparison knowledge graph of the commodity to be sold, a target second commodity different from each first commodity in all the second commodities is marked as an abnormal state, a target first commodity different from each second commodity in all the first commodities is marked as the abnormal state, and the comparison knowledge graph of the commodity to be sold is obtained. As one possible scenario, a comparison knowledge graph of the incoming and outgoing commodities as shown in FIG. 6 may be obtained.
Optionally, any of the above listed commodity comparison methods may further include the following steps:
determining a first sub-map comprising the target enterprise, the target second category of commodities and buyer enterprises related to the target enterprise through the target second category of commodities from the marketing commodity comparison knowledge map; determining a second sub-map comprising the target enterprise, the target first category commodity and a seller enterprise related to the target enterprise through the target first category commodity from the sales commodity comparison knowledge map; and taking the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
Specifically, a first sub-map comprising the target enterprise, the target second category of commodities and the buyer enterprise related to the target enterprise through the target second category of commodities is determined from the comparison knowledge map of the commodity sold and sold of the target enterprise. And determining a second sub-map comprising the target enterprise, the target first-class commodity and a seller enterprise related to the target enterprise through the target first-class commodity from the comparison knowledge map of the commodity sold and sold of the target enterprise. And further, taking the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
For example, the abnormal enterprise knowledge graph shown in fig. 7 can be determined from the target enterprise commodity-sold comparison knowledge graph shown in fig. 6.
In this way, all other suspect enterprises associated with the anomalous marketing goods may be identified based on the anomalous marketing items of the target enterprise. And abnormal enterprises can be displayed very intuitively in a knowledge graph mode.
Alternatively, in an implementation manner, the target enterprise may be used as an origin, and the abnormal enterprise knowledge graph with the upstream and downstream enterprises of the target enterprise as the origin is mined according to the invoice information of the upstream and downstream enterprises of the target enterprise, so that the abnormal enterprise knowledge graph with the association relationship can be determined from a large number of enterprises. By adopting the method, the abnormal enterprise chain with the hidden relation (or without the direct association relation) can be mined and visually displayed as the abnormal enterprise knowledge graph.
Optionally, the method further comprises:
taking all enterprises in the abnormal enterprise knowledge graph as enterprises to be checked; and carrying out tax information inspection on each enterprise to be inspected.
In one implementation, when the enterprise to be checked is a target enterprise, the tax information check is performed on the incoming invoice information of the target enterprise corresponding to the target first commodity, and/or the tax information check is performed on the sales invoice information of the target enterprise corresponding to the target second commodity.
It is easy to understand that, in the case where the target first category product and the target second category product are abnormal sale products, the invoice corresponding to the target first category product and the target second category product may also be an abnormal invoice.
Based on the same inventive concept, the embodiment of the present disclosure further provides a comparison apparatus for incoming and outgoing commodities, as shown in fig. 8, the apparatus 800 includes:
an obtaining module 810, configured to obtain all incoming invoice information and all sales invoice information of a target enterprise, where each of the incoming invoice information includes a first category of goods purchased by the target enterprise and a name of a seller enterprise that sells the first category of goods to the target enterprise, and each of the sales invoice information includes a second category of goods sold by the target enterprise and a name of a buyer enterprise that purchases the second category of goods from the target enterprise;
a construction module 820 configured to construct a sales commodity knowledge graph of the target enterprise according to first correlation information between the target enterprise and each seller enterprise and second correlation information between the target enterprise and each buyer enterprise, wherein the first correlation information is a first category commodity in the invoice information, and the second correlation information is a second category commodity in the invoice information, for the target enterprise, all sellers in all invoice information, and all buyers in all invoice information;
the first marking module 830 is configured to mark, in the sales commodity knowledge graph, a target second commodity different from each of the first commodities in all the second commodities as an abnormal state, so as to obtain a sales commodity comparison knowledge graph of the target enterprise.
With the adoption of the device, all the incoming invoice information and all the sales invoice information of the target enterprise are acquired, wherein each incoming invoice information comprises a first commodity purchased by the target enterprise and the name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and the name of a buyer enterprise purchasing the second commodity from the target enterprise. And aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, establishing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information. In the commodity sales knowledge graph, target second commodities which are different from the first commodities in all the second commodities are marked to be in an abnormal state, and the commodity sales comparison knowledge graph of the target enterprise is obtained. The mode of displaying the commodity marketing comparison relation of the target enterprise by using the knowledge graph is more intuitive than the mode of displaying the commodity marketing information of the taxpayers in the modes of tables, column graphs, sector graphs, line graphs and the like in the related technology. In addition, the intuitive display mode enables a user to quickly determine the abnormal selling item with the abnormal state mark from the selling commodity comparison knowledge graph. The problem of low-efficiency processing of further analyzing whether each commodity sales entry of the taxpayer is abnormal or not based on the taxpayer commodity sales entry information displayed in the forms of tables, column graphs, sector graphs, line graphs and the like in the related technology is solved.
Optionally, the apparatus further comprises:
the second marking module is configured to mark, in the sales commodity comparison knowledge graph, a target first commodity which is different from each second commodity in all the first commodities as the abnormal state, so as to obtain a new sales commodity comparison knowledge graph.
Optionally, the apparatus further comprises:
a first determining module configured to determine, from the comparison knowledge graph of commodities sold, a first sub-graph including the target enterprise, the target second class of commodities, and a buyer enterprise associated with the target enterprise through the target second class of commodities;
a second determining module configured to determine, from the comparison knowledge graph of the sold commodities, a second sub-graph including the target enterprise, the target first commodity and a seller enterprise associated with the target enterprise through the target first commodity;
a first execution module configured to use the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
Optionally, the apparatus further comprises:
the second execution module is configured to take each enterprise in the abnormal enterprise knowledge graph as an enterprise to be checked;
and the checking module is configured for checking the tax information of each enterprise to be checked.
Optionally, the inspection module comprises:
and the checking sub-module is configured to, when the enterprise to be checked is the target enterprise, perform tax information check on the invoice information of the target enterprise corresponding to the target first commodity, and/or perform tax information check on the invoice information of the target enterprise corresponding to the target second commodity.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Fig. 9 is a block diagram illustrating an electronic device 700 in accordance with an example embodiment. As shown in fig. 9, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input/output (I/O) interface 704, and a communication component 705.
The processor 701 is configured to control the overall operation of the electronic device 700 to complete all or part of the steps of the sold commodity comparison method. The memory 702 is used to store various types of data to support operation at the electronic device 700, such as instructions for any application or method operating on the electronic device 700 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 702 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia components 703 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 702 or transmitted through the communication component 705. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 704 provides an interface between the processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, which is not limited herein. The corresponding communication component 705 may thus include: Wi-Fi module, Bluetooth module, NFC module, etc.
In an exemplary embodiment, the electronic Device 700 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-described commodity-by-commodity comparison method.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the above-described marketed article comparison method is also provided. For example, the computer readable storage medium may be the memory 702 comprising program instructions executable by the processor 701 of the electronic device 700 to perform the sold product comparison method described above.
In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above mentioned incoming and outgoing commodity comparison method when executed by the programmable apparatus.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, various possible combinations will not be separately described in this disclosure.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (10)
1. A commodity comparison method for sale and sale is characterized by comprising the following steps:
acquiring all goods incoming invoice information and all sales invoice information of a target enterprise, wherein each goods incoming invoice information comprises a first goods purchased by the target enterprise and a name of a seller enterprise selling the first goods to the target enterprise, and each sales invoice information comprises a second goods sold by the target enterprise and a name of a buyer enterprise purchasing the second goods from the target enterprise;
aiming at the target enterprise, all seller enterprises in all invoice information and all buyer enterprises in all invoice information, constructing a commodity-to-be-sold knowledge graph of the target enterprise according to first associated information between the target enterprise and each seller enterprise and second associated information between the target enterprise and each buyer enterprise, wherein the first associated information is a first commodity in the invoice information, and the second associated information is a second commodity in the invoice information;
in the sales commodity knowledge graph, a target second commodity different from each first commodity in all the second commodities is marked to be in an abnormal state, and a sales commodity comparison knowledge graph of the target enterprise is obtained.
2. The method of claim 1, further comprising:
in the comparison knowledge graph of the commodity sold, a target first commodity which is different from each second commodity in all the first commodities is marked as the abnormal state, and a new comparison knowledge graph of the commodity sold is obtained.
3. The method of claim 2, further comprising:
determining a first sub-map comprising the target enterprise, the target second category of commodities and buyer enterprises related to the target enterprise through the target second category of commodities from the marketing commodity comparison knowledge map;
determining a second sub-map comprising the target enterprise, the target first category commodity and a seller enterprise related to the target enterprise through the target first category commodity from the sales commodity comparison knowledge map;
and taking the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
4. The method of claim 3, further comprising:
taking all enterprises in the abnormal enterprise knowledge graph as enterprises to be checked;
and carrying out tax information inspection on each enterprise to be inspected.
5. The method of claim 4, wherein the performing tax information check on each of the enterprises to be checked comprises:
and when the enterprise to be checked is the target enterprise, carrying out tax information check on the incoming invoice information of the target enterprise corresponding to the target first commodity and/or carrying out tax information check on the sales invoice information of the target enterprise corresponding to the target second commodity.
6. A comparison device for incoming and outgoing commodities, characterized in that the device comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire all incoming invoice information and all sales invoice information of a target enterprise, each incoming invoice information comprises a first commodity purchased by the target enterprise and a name of a seller enterprise selling the first commodity to the target enterprise, and each sales invoice information comprises a second commodity sold by the target enterprise and a name of a buyer enterprise purchasing the second commodity from the target enterprise;
a construction module, configured to construct, for the target enterprise, all seller enterprises in all invoice information, and all buyer enterprises in all invoice information, a commodity-to-be-sold knowledge graph of the target enterprise according to first association information between the target enterprise and each seller enterprise and second association information between the target enterprise and each buyer enterprise, where the first association information is a first commodity in the invoice information, and the second association information is a second commodity in the invoice information;
the first marking module is configured to mark target second-class commodities, which are different from the first-class commodities, in all the second-class commodities as abnormal states in the marketing commodity knowledge graph, so as to obtain a marketing commodity comparison knowledge graph of the target enterprise.
7. The apparatus of claim 6, further comprising:
the second marking module is configured to mark, in the sales commodity comparison knowledge graph, a target first commodity which is different from each second commodity in all the first commodities as the abnormal state, so as to obtain a new sales commodity comparison knowledge graph.
8. The apparatus of claim 7, further comprising:
a first determining module configured to determine, from the comparison knowledge graph of commodities sold, a first sub-graph including the target enterprise, the target second class of commodities, and a buyer enterprise associated with the target enterprise through the target second class of commodities;
a second determining module configured to determine, from the comparison knowledge graph of the sold commodities, a second sub-graph including the target enterprise, the target first commodity and a seller enterprise associated with the target enterprise through the target first commodity;
a first execution module configured to use the first sub-graph and/or the second sub-graph as an abnormal enterprise knowledge graph corresponding to the target enterprise.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
10. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 5.
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| CN202011480238.0A CN112529664A (en) | 2020-12-15 | 2020-12-15 | Method and device for comparing commodities sold in advance, storage medium and electronic equipment |
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| CN110019798A (en) * | 2017-11-20 | 2019-07-16 | 航天信息股份有限公司 | It is a kind of for the method and system measured into pin item type of merchandize difference |
| CN109993644A (en) * | 2017-12-29 | 2019-07-09 | 航天信息股份有限公司 | A kind of portrait determines method, apparatus, electronic equipment and storage medium |
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