CN113344511A - Intelligent order examination method and device - Google Patents
Intelligent order examination method and device Download PDFInfo
- Publication number
- CN113344511A CN113344511A CN202110600713.1A CN202110600713A CN113344511A CN 113344511 A CN113344511 A CN 113344511A CN 202110600713 A CN202110600713 A CN 202110600713A CN 113344511 A CN113344511 A CN 113344511A
- Authority
- CN
- China
- Prior art keywords
- result
- information
- determining
- accessory
- accessory information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Economics (AREA)
- Marketing (AREA)
- Data Mining & Analysis (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The application relates to an intelligent document examination method and device, wherein the intelligent document examination method comprises the following steps: acquiring order information and accessory information uploaded by a user; loading a corresponding configuration rule according to the order information; determining whether the attachment information needs to be subjected to false detection according to a configuration rule; if the false detection is needed, the attachment information is subjected to the false detection to obtain a first result; determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result; determining a template to be extracted according to the configuration rule, and marking required information from the second result based on the template to be extracted to obtain a third result; extracting required information from the third result, and matching the required information with information to be verified in the order information to obtain a fourth result; and obtaining and outputting the order examination result according to the first result, the third result and the fourth result. The payment materials can be quickly audited through the configuration rules, the labor cost is reduced, and the auditing efficiency is improved.
Description
Technical Field
The application relates to the technical field of information auditing, in particular to an intelligent examination method and device.
Background
Along with the development of society and the improvement of living standard of people, people pay more and more attention to education. In which, going abroad, study is a way to continue to be deeply made and is selected by more and more learners.
Students need to face the problem of paying the school fee when seeking to learn abroad. Generally, when a student pays a reserved school charge, because the amount of the school charge is relatively large, the payment materials and the offer of the student need to be strictly checked, for example, whether the student name is included, whether a school logo is present, whether a bill has the payment amount and student information, and whether the bill is consistent with the order of the payment, so as to eliminate the suspicion of anti-money laundering. In addition, it is necessary to check whether the materials provided by the user are the standard document templates of the school, whether the offer and the bill are available, whether the information necessary for paying the fee is included, and the like, so as to prevent the occurrence of payment errors.
However, the existing auditing for the payment materials and offer submitted by students is still in the stage of manual auditing, and because the materials to be audited are comparatively, the auditing unit usually needs to invest more manpower, and consumes more time to mark and identify each accessory uploaded by the user, so as to judge whether the accessories are in compliance, and the auditing efficiency is comparatively low.
Disclosure of Invention
In view of this, the present application aims to overcome the deficiencies of the prior art and provide an intelligent document examination method and apparatus.
In order to achieve the purpose, the following technical scheme is adopted in the application:
a first aspect of the present application provides a method of intelligent billing, comprising:
acquiring order information and accessory information uploaded by a user;
loading corresponding configuration rules according to the order information;
determining whether the attachment information needs to be subjected to false detection or not according to the configuration rule;
if false detection is needed, false detection is carried out on the accessory information to obtain a first result;
determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result;
determining a template to be extracted according to the configuration rule, and marking required information from the second result based on the template to be extracted to obtain a third result;
extracting the required information from the third result, and matching the extracted required information with information to be verified in the order information to obtain a fourth result;
and obtaining and outputting an examination result according to the first result, the third result and the fourth result.
Optionally, the performing false detection on the accessory information to obtain a first result includes:
carrying out false detection on the accessory information, and judging whether the accessory information is suspected to be false;
if the accessory information is suspected to be fake, determining that the first result is that the accessory information has a fake risk; and if the accessory information is not suspected to be false, determining that the first result is that the accessory information is not suspected to be false.
Optionally, the performing false detection on the accessory information and determining whether the accessory information is suspected to be false includes:
reading binary data of the accessory information, and detecting whether an external operation trace exists;
detecting whether the accessory information has PS traces or not by using an optical technology;
if the external operation trace is not detected and the PS trace is not detected, determining that the accessory information is not suspected to be false; otherwise, determining that the accessory information is suspected to be false.
Optionally, the accessory information includes offer and bill;
classifying the attachment information by using the classification template to obtain a second result, wherein the second result comprises:
identifying offer and bill in the accessory information using the classification template;
type tagging and storing the offer and the bill identified as the second result.
Optionally, the matching the extracted required information with the information to be verified in the order information to obtain a fourth result includes:
matching the extracted required information with information to be verified in the order information, and judging whether the matching result is inconsistent;
if the matching results are inconsistent, determining that the fourth result is unqualified; and if the matching result is not inconsistent, determining that the fourth result is qualified.
Another aspect of the application provides an apparatus for intelligent billing, comprising:
the acquisition module is used for acquiring order information and accessory information uploaded by a user;
the loading module is used for loading the corresponding configuration rule according to the order information;
the determining module is used for determining whether the attachment information needs to be subjected to false detection or not according to the configuration rule;
the false detection module is used for carrying out false detection on the accessory information if the false detection is required to be carried out, so as to obtain a first result;
the classification module is used for determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result;
the marking module is used for determining a template to be extracted according to the configuration rule, and marking required information from the second result based on the template to be extracted to obtain a third result;
the matching module is used for extracting the required information from the third result, and matching the extracted required information with the information to be verified in the order information to obtain a fourth result;
and the output module is used for obtaining and outputting the order examination result according to the first result, the third result and the fourth result.
Optionally, the false detection module includes a detection unit and a determination unit;
the detection unit is used for carrying out false detection on the accessory information and judging whether the accessory information is suspected to be false;
the determining unit is used for determining that the first result is that the accessory information has a counterfeiting risk if the accessory information is suspected to be fake; and if the accessory information is not suspected to be false, determining that the first result is that the accessory information is not suspected to be false.
Optionally, the detection unit includes a first detection subunit, a second detection subunit, and a determination subunit;
the first detection subunit is used for reading binary data of the accessory information and detecting whether an external operation trace exists;
the second detection subunit is used for detecting whether the accessory information has PS traces or not by utilizing an optical technology;
the determining subunit is configured to determine that the accessory information is not suspect if the external operation trace is not detected and the PS trace is not detected; otherwise, determining that the accessory information is suspected to be false.
Optionally, the classification module includes an identification sub-module and a marking sub-module;
the identification submodule is used for identifying offer and bills in the accessory information by utilizing the classification template;
the classification submodule is used for carrying out type marking and storing on the identified offer and the bill as the second result.
Optionally, the matching module includes a matching subunit and a result subunit;
the matching subunit is configured to match the extracted required information with information to be verified in the order information, and determine whether a matching result is inconsistent;
the result subunit is configured to determine that the fourth result is not qualified if the matching results are inconsistent; and if the matching result is not inconsistent, determining that the fourth result is qualified.
The technical scheme provided by the application can comprise the following beneficial effects:
according to the scheme, after the order information and the accessory information uploaded by the user are obtained, the corresponding configuration rule can be determined according to the order information and loaded, so that the accessory information can be checked according to the corresponding configuration rule. After the corresponding configuration rule is loaded, whether the attachment information needs to be subjected to false detection or not can be determined according to the configuration rule, and if so, the attachment information can be subjected to false detection to obtain a first result. And then, determining a classification template according to the configuration rule so as to classify the accessory information to obtain a second result. Similarly, according to the configuration rule, a template to be extracted may also be determined, and based on the template to be extracted, the required information may be marked in the second result to obtain a third result. And extracting the required information from the third result, and matching the extracted required information with the information to be verified in the order information to obtain a fourth result. According to the first result, the third result and the fourth result, the order examination result aiming at the order information and the accessory information can be obtained and output. Therefore, manual audit is not needed, and rapid and automatic audit on order information and accessory information can be realized only by presetting configuration rules, so that the labor cost is reduced, and the working efficiency is improved. In addition, the accuracy of auditing can be greatly improved through automatic false detection and identification, and the safety of intelligent examination order is guaranteed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for intelligent billing according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an apparatus for intelligent document examination according to another embodiment of the present application.
Fig. 3 is a schematic structural diagram of an apparatus for intelligent document examination according to another embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a flowchart of a method for intelligent billing according to an embodiment of the present application. As shown in the figure, the method may at least include the following implementation steps, for example, when executed by the background management side:
and step 11, obtaining order information and accessory information uploaded by a user.
When a user pays on line, the user firstly needs to make an order. When placing an order, the accessory information needs to be uploaded, and the order information and the accessory information are uploaded to the background management side together, so that the background management side can conveniently check the uploaded order information and the uploaded accessory information.
The accessory information can comprise two parts, wherein one part is the offer of the student to be paid, and the other part is the bill to be paid.
And step 12, loading corresponding configuration rules according to the order information.
In practice, the order information may include information such as country of study, school name, school logo, currency, charge type, student name, student number, payment time, payment amount, and specialty. Different configuration rules are correspondingly provided for different countries, different schools and different payment types. That is, each fee type for each school is associated with its unique configuration rules.
And step 13, determining whether the attachment information needs to be subjected to false detection or not according to the configuration rule.
The configuration rule is configured with whether to perform false detection on the attachment information.
And 14, if the false detection is required, performing the false detection on the accessory information to obtain a first result.
And step 15, determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result.
And step 16, determining a template to be extracted according to the configuration rule, and marking the required information from the second result based on the template to be extracted to obtain a third result.
In implementation, the configuration rule includes configuration elements, and the configuration elements are mainly used for configuring templates to be extracted and information to be extracted, for example, in the united states, payment material I20 templates need to be set. According to specific materials of the United states, information marking is carried out, such as I20, information of names of students, student numbers, payment time, payment amount, school names and specialties is marked.
The desired information in defer and bill may be marked based on the template to be extracted, resulting in a third result.
And step 17, extracting the required information from the third result, and matching the extracted required information with the information to be verified in the order information to obtain a fourth result.
And step 18, obtaining and outputting the order examination result according to the first result, the third result and the fourth result.
The order examination result mainly comprises three parts, wherein the first part is to show whether the accessory material has a risk of being counterfeited; the second part is showing the labeled offer and bill; and the third part is to show whether the audit result is qualified.
In this embodiment, after the order information and the accessory information uploaded by the user are obtained, the corresponding configuration rule may be determined according to the order information and loaded, so that the accessory information is checked according to the corresponding configuration rule. After the corresponding configuration rule is loaded, whether the attachment information needs to be subjected to false detection or not can be determined according to the configuration rule, and if so, the attachment information can be subjected to false detection to obtain a first result. And then, determining a classification template according to the configuration rule so as to classify the accessory information to obtain a second result. Similarly, according to the configuration rule, a template to be extracted may also be determined, and based on the template to be extracted, the required information may be marked in the second result to obtain a third result. And extracting the required information from the third result, and matching the extracted required information with the information to be verified in the order information to obtain a fourth result. According to the first result, the third result and the fourth result, the order examination result aiming at the order information and the accessory information can be obtained and output. Therefore, manual audit is not needed, and rapid and automatic audit on order information and accessory information can be realized only by presetting configuration rules, so that the labor cost is reduced, and the working efficiency is improved. In addition, the accuracy of auditing can be greatly improved through automatic false detection and identification, and the safety of intelligent examination order is guaranteed.
It should be noted that the execution subject in the present application may be a background management system, a software or hardware based functional module in the background management system, or other devices.
In some embodiments, when the attachment information is subjected to false detection to obtain a first result, whether the attachment information is suspected to be false or not can be judged; if the accessory information is suspected to be fake, determining that the first result is that the accessory information has a fake risk; if the accessory information is not suspect, determining that the first result is that the accessory information is not suspect.
During implementation, the attachment information is subjected to false detection, and whether the attachment information is suspected of being false or not is judged, which specifically includes: reading binary data of the accessory information, and detecting whether an external operation trace exists; detecting whether the accessory information has PS traces or not by using an optical technology; if no external operation trace is detected and no PS trace is detected, determining that the accessory information is not suspected to be false; otherwise, the attachment information is determined to be suspect.
For a specific implementation manner of detecting whether there is a foreign operation trace by reading binary data, reference may be made to the prior art, which is not described herein again.
Similarly, the specific implementation manner of detecting whether the accessory information has PS traces by using the optical technology can also refer to the prior art, and is not described herein again.
In step 15, when the classification template is used to classify the accessory information to obtain the second result, the classification template can be used to identify offer and bill in the accessory information; the identified offer and bill are type-tagged and stored as a second result.
During specific implementation, the offer and the bill in the accessory information can be classified by utilizing the classification template, and the uploaded accessory information is identified to be the offer and the bill, so that the offer and the bill can be respectively presented to the next staff when the examination result is presented.
After identifying the offer and the bill in the accessory information, the template to be extracted is determined, and the needed information can be marked from the identified offer and bill.
In order to realize the auditing of the required information, after the offer and the bill marked with the required information are obtained, the marked required information can be extracted, then the information to be verified in the bill information is matched with the required information, if the matching result is inconsistent, the situation that the information in the currently submitted accessory material and the order information is inconsistent is indicated, and the fourth result is unqualified; if the matching results are all consistent, the currently submitted accessory materials are consistent with the order information, the order has no problem, and the fourth result is qualified. For example, the required information is the name of the school, the name of the student, the number of the student, the payment amount and the payment type in the accessory information, and correspondingly, the information to be verified is the name of the school, the name of the student, the number of the student, the payment amount and the payment type in the order information. After the required information is obtained, matching the required information with the information to be verified in the order information one by one, detecting whether the name of a school, the name of a student, the number of the student, the payment amount and the payment type in the two materials are consistent, and if the two materials are completely consistent, judging that the fourth result is qualified; if not, the fourth result is not good.
After the first result, the third result and the fourth result are obtained, the examination result of the examination order can be determined and output, so that a background worker can conveniently check the examination result, and guarantee is provided for follow-up payment.
Based on the same technical concept, this embodiment further provides an intelligent examination order device, as shown in fig. 2, the device may specifically include: an obtaining module 201, configured to obtain order information and accessory information uploaded by a user; a loading module 202, configured to load a corresponding configuration rule according to the order information; a determining module 203, configured to determine whether to perform false detection on the accessory information according to the configuration rule; a falsification detection module 204, configured to perform falsification detection on the accessory information if falsification detection is needed, so as to obtain a first result; the classification module 205 is configured to determine a corresponding classification template according to the configuration rule, and classify the accessory information by using the classification template to obtain a second result; the marking module 206 is configured to determine a template to be extracted according to the configuration rule, and mark the required information from the second result based on the template to be extracted to obtain a third result; the matching module 207 is configured to extract the required information from the third result, and match the extracted required information with the information to be verified in the order information to obtain a fourth result; and the output module 208 is configured to obtain and output the order examination result according to the first result, the third result, and the fourth result.
Optionally, the false detection module 204 may include a detection unit and a determination unit; the detection unit is used for carrying out false detection on the accessory information and judging whether the accessory information is suspected to be false; the determining unit is used for determining that the first result is that the accessory information has a counterfeiting risk if the accessory information is suspected to be fake; if the accessory information is not suspect, determining that the first result is that the accessory information is not suspect.
Optionally, the detection unit may include a first detection subunit, a second detection subunit, and a determination subunit; the first detection subunit is used for reading binary data of the accessory information and detecting whether an external operation trace exists; the second detection subunit is used for detecting whether the accessory information has PS traces or not by utilizing an optical technology; the determining subunit is configured to determine that the accessory information is not suspect of being false if the external operation trace is not detected and the PS trace is not detected; otherwise, the attachment information is determined to be suspect.
Optionally, the classification module 205 may include an identification sub-module and a labeling sub-module; the identification submodule is used for identifying offer and bills in the accessory information by utilizing the classification template; and the classification submodule is used for carrying out type marking and storing on the identified offer and the bill as a second result.
Optionally, the matching module 207 may include a matching subunit and a result subunit; the matching subunit is used for matching the extracted required information with the information to be verified in the order information and judging whether the matching result is inconsistent; the result subunit is used for determining that the fourth result is unqualified if the matching results are inconsistent; and if the matching result is not inconsistent, determining that the fourth result is qualified.
For a specific implementation of the apparatus for intelligent document examination provided in the embodiment of the present application, reference may be made to the implementation of the method for intelligent document examination described in any of the above embodiments, and details are not described here.
An embodiment of the present application further provides an apparatus for intelligent document examination, as shown in fig. 3, the apparatus may specifically include: a processor 301, and a memory 302 connected to the processor 301; the memory 302 is used to store computer programs; the processor 301 is adapted to invoke and execute a computer program in the memory 302 to perform the method of intelligent ticketing as described in any of the embodiments above.
For a specific implementation of the intelligent document examination device provided in the embodiment of the present application, reference may be made to the implementation of the intelligent document examination method described in any of the above embodiments, and details are not described here.
Embodiments of the present application further provide a storage medium storing a computer program, which when executed by a processor, implements the steps of the method of intelligent checklist as described in any of the above embodiments.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. An intelligent waybill method, comprising:
acquiring order information and accessory information uploaded by a user;
loading corresponding configuration rules according to the order information;
determining whether the attachment information needs to be subjected to false detection or not according to the configuration rule;
if false detection is needed, false detection is carried out on the accessory information to obtain a first result;
determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result;
determining a template to be extracted according to the configuration rule, and marking required information from the second result based on the template to be extracted to obtain a third result;
extracting the required information from the third result, and matching the extracted required information with information to be verified in the order information to obtain a fourth result;
and obtaining and outputting an examination result according to the first result, the third result and the fourth result.
2. The method of claim 1, wherein the performing a false detection on the attachment information to obtain a first result comprises:
carrying out false detection on the accessory information, and judging whether the accessory information is suspected to be false;
if the accessory information is suspected to be fake, determining that the first result is that the accessory information has a fake risk; and if the accessory information is not suspected to be false, determining that the first result is that the accessory information is not suspected to be false.
3. The method of claim 2, wherein the performing false detection on the accessory information and determining whether the accessory information is suspected of being false comprises:
reading binary data of the accessory information, and detecting whether an external operation trace exists;
detecting whether the accessory information has PS traces or not by using an optical technology;
if the external operation trace is not detected and the PS trace is not detected, determining that the accessory information is not suspected to be false; otherwise, determining that the accessory information is suspected to be false.
4. The method of intelligent billing according to claim 1 wherein the attachment information includes offer and bill;
classifying the attachment information by using the classification template to obtain a second result, wherein the second result comprises:
identifying offer and bill in the accessory information using the classification template;
type tagging and storing the offer and the bill identified as the second result.
5. The method for intelligent billing inspection according to claim 1, wherein the matching the extracted required information with the information to be verified in the order information to obtain a fourth result comprises:
matching the extracted required information with information to be verified in the order information, and judging whether the matching result is inconsistent;
if the matching results are inconsistent, determining that the fourth result is unqualified; and if the matching result is not inconsistent, determining that the fourth result is qualified.
6. An apparatus for intelligent document examination, comprising:
the acquisition module is used for acquiring order information and accessory information uploaded by a user;
the loading module is used for loading the corresponding configuration rule according to the order information;
the determining module is used for determining whether the attachment information needs to be subjected to false detection or not according to the configuration rule;
the false detection module is used for carrying out false detection on the accessory information if the false detection is required to be carried out, so as to obtain a first result;
the classification module is used for determining a corresponding classification template according to the configuration rule, and classifying the accessory information by using the classification template to obtain a second result;
the marking module is used for determining a template to be extracted according to the configuration rule, and marking required information from the second result based on the template to be extracted to obtain a third result;
the matching module is used for extracting the required information from the third result, and matching the extracted required information with the information to be verified in the order information to obtain a fourth result;
and the output module is used for obtaining and outputting the order examination result according to the first result, the third result and the fourth result.
7. The apparatus for intelligent billing of claim 6 wherein the fraud detection module comprises a detection unit and a determination unit;
the detection unit is used for carrying out false detection on the accessory information and judging whether the accessory information is suspected to be false;
the determining unit is used for determining that the first result is that the accessory information has a counterfeiting risk if the accessory information is suspected to be fake; and if the accessory information is not suspected to be false, determining that the first result is that the accessory information is not suspected to be false.
8. The apparatus for intelligent billing of claim 7 wherein the detection unit comprises a first detection subunit, a second detection subunit, and a determination subunit;
the first detection subunit is used for reading binary data of the accessory information and detecting whether an external operation trace exists;
the second detection subunit is used for detecting whether the accessory information has PS traces or not by utilizing an optical technology;
the determining subunit is configured to determine that the accessory information is not suspect if the external operation trace is not detected and the PS trace is not detected; otherwise, determining that the accessory information is suspected to be false.
9. The apparatus of claim 6, wherein the classification module comprises an identification sub-module and a labeling sub-module;
the identification submodule is used for identifying offer and bills in the accessory information by utilizing the classification template;
the classification submodule is used for carrying out type marking and storing on the identified offer and the bill as the second result.
10. The apparatus of claim 6, wherein the matching module comprises a matching subunit and a results subunit;
the matching subunit is configured to match the extracted required information with information to be verified in the order information, and determine whether a matching result is inconsistent;
the result subunit is configured to determine that the fourth result is not qualified if the matching results are inconsistent; and if the matching result is not inconsistent, determining that the fourth result is qualified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110600713.1A CN113344511A (en) | 2021-05-31 | 2021-05-31 | Intelligent order examination method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110600713.1A CN113344511A (en) | 2021-05-31 | 2021-05-31 | Intelligent order examination method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113344511A true CN113344511A (en) | 2021-09-03 |
Family
ID=77472661
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110600713.1A Pending CN113344511A (en) | 2021-05-31 | 2021-05-31 | Intelligent order examination method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113344511A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108765085A (en) * | 2018-05-30 | 2018-11-06 | 杭州骑轻尘信息技术有限公司 | Vehicle order checking method, device and readable storage medium storing program for executing |
| CN111738724A (en) * | 2020-07-31 | 2020-10-02 | 支付宝(杭州)信息技术有限公司 | Cross-border resource transfer authenticity auditing method and device, and electronic equipment |
| CN112053124A (en) * | 2020-08-06 | 2020-12-08 | 中信银行股份有限公司 | Online on-line payment method and device, electronic equipment and medium |
| CN112561524A (en) * | 2020-12-10 | 2021-03-26 | 中信银行股份有限公司 | Payment method and device, storage medium and electronic device |
| CN112686244A (en) * | 2020-12-29 | 2021-04-20 | 平安银行股份有限公司 | Automatic approval method, device, equipment and medium based on picture processing interface |
| CN112712429A (en) * | 2020-12-28 | 2021-04-27 | 中电金信软件有限公司 | Remittance service auditing method, remittance service auditing device, computer equipment and storage medium |
| CN112801658A (en) * | 2020-07-31 | 2021-05-14 | 支付宝(杭州)信息技术有限公司 | Cross-border resource transfer authenticity auditing method and device and electronic equipment |
-
2021
- 2021-05-31 CN CN202110600713.1A patent/CN113344511A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108765085A (en) * | 2018-05-30 | 2018-11-06 | 杭州骑轻尘信息技术有限公司 | Vehicle order checking method, device and readable storage medium storing program for executing |
| CN111738724A (en) * | 2020-07-31 | 2020-10-02 | 支付宝(杭州)信息技术有限公司 | Cross-border resource transfer authenticity auditing method and device, and electronic equipment |
| CN112801658A (en) * | 2020-07-31 | 2021-05-14 | 支付宝(杭州)信息技术有限公司 | Cross-border resource transfer authenticity auditing method and device and electronic equipment |
| CN112053124A (en) * | 2020-08-06 | 2020-12-08 | 中信银行股份有限公司 | Online on-line payment method and device, electronic equipment and medium |
| CN112561524A (en) * | 2020-12-10 | 2021-03-26 | 中信银行股份有限公司 | Payment method and device, storage medium and electronic device |
| CN112712429A (en) * | 2020-12-28 | 2021-04-27 | 中电金信软件有限公司 | Remittance service auditing method, remittance service auditing device, computer equipment and storage medium |
| CN112686244A (en) * | 2020-12-29 | 2021-04-20 | 平安银行股份有限公司 | Automatic approval method, device, equipment and medium based on picture processing interface |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8155423B2 (en) | System and method for tracing bank notes | |
| CN108734702A (en) | Vehicle damages determination method, server and storage medium | |
| CN103440507A (en) | Bill information verifying device and method for verifying bill information | |
| CN111428599A (en) | Bill identification method, device and equipment | |
| US20140207631A1 (en) | Systems and Method for Analyzing and Validating Invoices | |
| CN106327546A (en) | Face detection algorithm test method and device | |
| CN110634223A (en) | Bill verification method and device | |
| US9436937B1 (en) | Highlight-based bill processing | |
| CN103235934A (en) | Comparison method and system of seal images | |
| CN112883858A (en) | Reimbursement invoice auditing method and device and storage medium | |
| CN111858698B (en) | Data checking method, data checking device and terminal equipment | |
| CN114038080A (en) | Anti-cheating safety inspection method and system based on micro-service architecture | |
| CN103646464B (en) | The method of smart point cash inspecting machine identification counterfeit money auto-update | |
| CN112508039B (en) | Image detection method and device | |
| CN113344511A (en) | Intelligent order examination method and device | |
| CN111784423B (en) | Invoice matching method and device, electronic equipment and storage medium | |
| CN106250755A (en) | For generating the method and device of identifying code | |
| CN112307101A (en) | Project pricing auditing method, device, computer equipment and system | |
| CN111985936A (en) | Method, device and equipment for checking merchant certificate information | |
| CN109359683B (en) | Target detection method, device, terminal and computer-readable storage medium | |
| CN114638597A (en) | Intelligent government affair handling application system, method, terminal and medium | |
| CN113327023A (en) | Traversal test method and device, electronic equipment and computer readable storage medium | |
| CN114663899A (en) | Financial bill processing method, device, equipment and medium | |
| CN114092765A (en) | Wood quality detection method and device, electronic equipment and storage medium | |
| CN114187116A (en) | Method and apparatus for managing account information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210903 |