CN111309950A - E-commerce transaction information interaction method, e-commerce platform and readable storage medium - Google Patents
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Abstract
The invention discloses an e-commerce transaction information interaction method, an e-commerce platform and a readable storage medium, wherein the e-commerce transaction information interaction method comprises the following steps: the method comprises the steps of obtaining transaction information on an e-commerce platform, wherein the transaction information comprises character information, images and position information corresponding to the images, obtaining convolution kernels corresponding to the images according to the position information, obtaining corresponding characteristic information of the images by adopting the convolution kernels, matching the characteristic information with the character information, and outputting the transaction information to a platform service center when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information. The image is subjected to feature extraction by adopting the convolutional neural network so as to automatically extract feature information, and the extracted feature information is matched with the character information, so that the efficiency can be greatly improved.
Description
Technical Field
The invention relates to the technical field of E-commerce transaction information interaction, in particular to an E-commerce transaction information interaction method, an E-commerce platform and a readable storage medium.
Background
Electronic commerce is called e-commerce for short, which means that transaction activities and related service activities are carried out in an electronic transaction mode on the internet, an intranet and a value-added network, and is the electronization and networking of each link of the traditional commercial activities, wherein the electronic commerce comprises electronic money exchange, supply chain management, electronic transaction market, network marketing, online transaction processing, electronic data Exchange (EDI), inventory management and an automatic data collection system, and in the process, the utilized information technology comprises the following steps: internet, extranet, email, database, electronic directory and mobile phone.
With the development of internet technology, online shopping has become one of people's daily life style, therefore, massive transaction information is generated every day, wherein the transaction information comprises text information and image information, and the text information and the image information are often related information, and how to judge whether the text information and the image information are matched meets the requirements.
Disclosure of Invention
The invention mainly aims to provide an E-commerce transaction information interaction method, an E-commerce platform and a readable storage medium, aiming at extracting the characteristics of an image by adopting a convolutional neural network so as to automatically extract the characteristic information, and matching the extracted characteristic information with character information, so that the efficiency can be greatly improved.
In order to achieve the purpose, the invention provides an e-commerce transaction information interaction method, which comprises the following steps:
acquiring transaction information on an e-commerce platform, wherein the transaction information comprises character information, images and position information corresponding to the images;
acquiring a convolution kernel corresponding to the image according to the position information;
performing the image by adopting the convolution kernel to acquire corresponding characteristic information;
matching the characteristic information with the character information;
and when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information, outputting the transaction information to a platform service center.
Optionally, before the step of acquiring image information on the e-commerce platform, where the image information includes an image and position information corresponding to the image, the method further includes:
receiving images uploaded by a user side or a business side;
judging whether the image meets the set requirements or not;
if yes, storing the image in a set area;
if not, reminding the user terminal or the merchant terminal to input the image again.
Optionally, the setting requirements include requirements for image size and requirements for sharpness.
Optionally, the convolution kernel comprises a first convolution kernel and a second convolution kernel, wherein the second convolution kernel is larger than the first convolution kernel;
adopting the convolution kernel to extract the features of the image and obtain corresponding feature information:
performing first convolution neural network processing on the image by adopting a first convolution kernel so as to extract first characteristic information;
performing second convolution neural network processing on the image by adopting a second convolution kernel to extract second characteristic information;
judging whether the similarity of the first characteristic information and the second characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the second feature information as the feature information.
Optionally, the convolution kernel further comprises a third convolution kernel, the third convolution kernel being larger than the second convolution kernel;
after the step of determining whether the similarity between the first feature information and the second feature information is greater than a set feature similarity threshold, the method further includes:
if not, performing third convolution neural network processing on the image by adopting a third convolution kernel so as to extract third characteristic information;
judging whether the similarity of the second characteristic information and the third characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the third feature information as the feature information.
Optionally, after the step of matching the feature information with the text information, the method further includes:
and when the matching degree of the two is smaller than a set value, sending a prompt message for inputting 'transaction information is wrong' to the user terminal or the merchant terminal.
The invention further provides a computer-readable storage medium, wherein an e-commerce transaction information interaction program is stored on the computer-readable storage medium, and when the e-commerce transaction information interaction program is executed, the steps of the e-commerce transaction information interaction method are realized.
The invention also provides an e-commerce platform which comprises a memory, a processor and an e-commerce transaction information interaction program which is stored on the memory and can be operated on the processor, wherein the e-commerce transaction information interaction program realizes the steps of the e-commerce transaction information interaction method in any one of the above steps when being executed.
In the technical scheme of the invention, transaction information on an e-commerce platform is obtained, wherein the transaction information comprises character information, an image and position information corresponding to the image, a convolution kernel corresponding to the image is obtained according to the position information, the image is processed by adopting the convolution kernel to obtain corresponding characteristic information, the characteristic information is matched with the character information, and when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information, the transaction information is output to a platform service center. The image is subjected to feature extraction by adopting the convolutional neural network so as to automatically extract feature information, and the extracted feature information is matched with the character information, so that the efficiency can be greatly improved.
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In order to more clearly illustrate the embodiments of the present invention 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 invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a block diagram of an embodiment of an e-commerce platform provided by the present invention;
FIG. 2 is a flowchart illustrating an e-commerce transaction information interaction method according to an embodiment of the present invention;
fig. 3 is an embodiment of step S30 in fig. 2.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that all the directional indicators (such as up, down, left, right, front, and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
In addition, the descriptions related to "first", "second", etc. in the present invention are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
As shown in fig. 1, fig. 1 is a schematic structural diagram of an e-commerce platform of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the e-commerce platform includes: a processor 1001, such as a CPU, a communication bus 1002, a data interface 1003, and a memory 1004. Wherein a communication bus 1002 is used to enable connective communication between these components. The data interface 1003 may also include a standard wired interface (e.g., a USB interface or an IO interface), a wireless interface (e.g., a WI-FI interface). The memory 1004 may be a high-speed RAM memory or a non-volatile memory (e.g., a disk memory). The memory may alternatively be a storage device separate from the aforementioned processor.
Those skilled in the art will appreciate that the e-commerce platform configuration shown in fig. 1 does not constitute a limitation of the e-commerce platform and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1004, which is a kind of computer storage medium, may include therein an operating system, a data interface implementation program, and an e-commerce transaction information interaction program.
In the e-commerce platform shown in fig. 1, the processor may be a control chip in the e-commerce platform, and the processor may be configured to call the e-commerce transaction information interaction program stored in the memory, and perform the following operations:
acquiring transaction information on an e-commerce platform, wherein the transaction information comprises character information, images and position information corresponding to the images;
acquiring a convolution kernel corresponding to the image according to the position information;
extracting the features of the image by adopting the convolution kernel to acquire corresponding feature information;
matching the characteristic information with the character information;
and when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information, outputting the transaction information to a platform service center.
Further, the processor 1001 may call an e-commerce transaction information interaction program stored in the memory 1004 to obtain image information on the e-commerce platform, where the image information includes an image and position information corresponding to the image, and before the step of:
receiving images uploaded by a user side or a business side;
judging whether the image meets the set requirements or not;
if yes, storing the image in a set area;
if not, reminding the user terminal or the merchant terminal to input the image again.
Wherein the setting requirements include a requirement for image size and a requirement for sharpness.
Further, the processor 1001 may call an e-commerce transaction information interaction program stored in the memory 1004, where the convolution kernel includes a first convolution kernel and a second convolution kernel, where the second convolution kernel is larger than the first convolution kernel;
adopting the convolution kernel to extract the features of the image and obtain corresponding feature information:
performing first convolution neural network processing on the image by adopting a first convolution kernel so as to extract first characteristic information;
performing second convolution neural network processing on the image by adopting a second convolution kernel to extract second characteristic information;
judging whether the similarity of the first characteristic information and the second characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the second feature information as the feature information.
Further, the processor 1001 may call the e-commerce transaction information interaction program stored in the memory 1004, where the convolution kernel further includes a third convolution kernel, and the third convolution kernel is larger than the second convolution kernel;
after the step of determining whether the similarity between the first feature information and the second feature information is greater than a set feature similarity threshold, the method further includes:
if not, performing third convolution neural network processing on the image by adopting a third convolution kernel so as to extract third characteristic information;
judging whether the similarity of the second characteristic information and the third characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the third feature information as the feature information.
Further, the step of the processor 1001 may call the e-commerce transaction information interaction program stored in the memory 1004 to match the feature information with the text information, and then includes:
and when the matching degree of the two is smaller than a set value, sending a prompt message for inputting 'transaction information is wrong' to the user terminal or the merchant terminal.
The invention provides an e-commerce transaction information interaction method, and fig. 2 and 3 are embodiments of an operation method of an e-commerce platform provided by the invention.
Referring to fig. 2, in an embodiment of the present invention, the method for interacting e-commerce transaction information includes:
step S10, transaction information on the E-commerce platform is obtained, wherein the transaction information comprises character information, images and position information corresponding to the images; the transaction information may be product information uploaded by a merchant or evaluation information uploaded by a user, and the transaction information includes text information and an image, and it is obvious that generally, information transmitted by the image is matched with the text information, that is, the information is consistent in meaning, but because the merchant or the customer inputs are not standard or careful, problems that the image does not correspond to the text often exist.
Step S20, acquiring a convolution kernel corresponding to the image according to the position information; the position information corresponding to the image determines the requirement corresponding to the image and the basic product category, so that the e-commerce platform correspondingly stores a mapping relation table corresponding to the position information and the convolution kernel, and the corresponding convolution kernel can be found by inquiring the mapping relation table.
Step S30, extracting the features of the image by adopting the convolution kernel to acquire corresponding feature information; the convolution is adopted to check the image and carry out convolution neural network processing so as to extract the corresponding characteristic information, and thus, the characteristic information of the image can be extracted in an intelligent mode.
Step S40, matching the characteristic information with the character information;
step S50, when the matching degree of the two reaches a set value and the characteristic information and the character information contain abnormal information, the transaction information is output to a platform service center; when the characteristic information is matched with the text information, the input of the user or the merchant is correct, and then whether the characteristic information and the text information contain abnormal information or not is further judged, and if the characteristic information and the text information contain the abnormal information, the transaction information needs to be output to a platform service center and processed by the service center.
In the technical scheme of the invention, transaction information on an e-commerce platform is obtained, wherein the transaction information comprises character information, an image and position information corresponding to the image, a convolution kernel corresponding to the image is obtained according to the position information, the image is processed by adopting the convolution kernel to obtain corresponding characteristic information, the characteristic information is matched with the character information, and when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information, the transaction information is output to a platform service center. The image is subjected to feature extraction by adopting the convolutional neural network so as to automatically extract feature information, and the extracted feature information is matched with the character information, so that the efficiency can be greatly improved.
When the user or the merchant inputs the image, it is highly likely that the input image is not satisfactory, which causes a problem in the post-extraction feature, so in the embodiment of the present invention, step S10 is preceded by:
receiving images uploaded by a user side or a business side;
judging whether the image meets the set requirements or not;
if yes, storing the image in a set area;
if not, reminding the user terminal or the merchant terminal to input the image again.
Wherein the setting requirements include a requirement for image size and a requirement for sharpness.
Referring to fig. 3, fig. 3 is a diagram illustrating an embodiment of step S30 in fig. 2, where in step S30, the convolution kernel includes a first convolution kernel and a second convolution kernel, where the second convolution kernel is larger than the first convolution kernel;
step S30 includes:
step S31, performing first convolution neural network processing on the image by adopting a first convolution kernel to extract first characteristic information;
step S32, performing second convolution neural network processing on the image by adopting a second convolution kernel to extract second characteristic information;
step S33, judging whether the similarity between the first characteristic information and the second characteristic information is larger than a set characteristic similarity threshold value;
and step S34, if yes, using the second feature information as the feature information.
When the image is processed by the convolutional neural network algorithm, the larger the convolutional kernel is, the higher the corresponding information accuracy is, but at the same time, the larger the calculation amount is, the smaller the convolutional kernel is, the smaller the calculation amount is, but there is a problem of omission of the feature information, so in this embodiment, whether the adopted convolutional size is appropriate is determined according to the similarity (or difference) between feature information (i.e., first feature information and second feature information) obtained by the convolutional neural network algorithm processing 2 times before and after, when the similarity reaches a feature similarity threshold (e.g., 98%), that the difference between feature information obtained by the convolutional neural network algorithm processing twice is not large, that is, the meaning of obtaining the feature information by the convolutional neural network algorithm processing after further increasing the convolutional kernel is not large, that is, that the size of the preceding convolutional kernel is appropriate, and when the similarity does not reach the feature similarity threshold, that is, it means that the difference between the feature information obtained by the two times of convolutional neural network algorithm processing is large, that is, the first convolutional kernel and the second convolutional kernel are not suitable, further, in this embodiment, the convolutional kernel further includes a third convolutional kernel, where the third convolutional kernel is larger than the second convolutional kernel, and after the step S33, the method further includes:
step S35, if not, a third convolution is adopted to check the image and carry out third convolution neural network processing so as to extract third characteristic information;
step S36, judging whether the similarity between the second characteristic information and the third characteristic information is larger than a set characteristic similarity threshold value;
and step S37, if yes, using the third feature information as the feature information.
Thus, the accuracy of feature information extraction can be further improved.
In addition, in other embodiments of the present invention, after step S40, the method further includes: and when the matching degree of the two is smaller than a set value, sending a prompt message for inputting 'transaction information is wrong' to the user terminal or the merchant terminal. That is, at this time, the text information input by the surface user or the merchant does not match the image, and needs to be input again by the user or the merchant.
The invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores an e-commerce transaction information interaction program, and the e-commerce transaction information interaction program realizes the steps of the e-commerce transaction information interaction method according to any one of the above embodiments when being executed by a processor.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of software products, which are stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and include instructions for enabling a terminal device (such as a mobile phone, a computer, a server, a television, or a network device) to execute the methods according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. An e-commerce transaction information interaction method is characterized by comprising the following steps:
acquiring transaction information on an e-commerce platform, wherein the transaction information comprises character information, images and position information corresponding to the images;
acquiring a convolution kernel corresponding to the image according to the position information;
extracting the features of the image by adopting the convolution kernel to acquire corresponding feature information;
matching the characteristic information with the character information;
and when the matching degree of the characteristic information and the character information reaches a set value and the characteristic information and the character information contain abnormal information, outputting the transaction information to a platform service center.
2. The e-commerce transaction information interaction method of claim 1, wherein before the step of obtaining image information on the e-commerce platform, the image information including an image and position information corresponding to the image, the method further comprises:
receiving images uploaded by a user side or a business side;
judging whether the image meets the set requirements or not;
if yes, storing the image in a set area;
if not, reminding the user terminal or the merchant terminal to input the image again.
3. The e-commerce transaction information interaction method of claim 2, wherein the setting requirements include requirements for image size and requirements for definition.
4. The e-commerce transaction information interaction method of claim 1, wherein the convolution kernel comprises a first convolution kernel and a second convolution kernel, wherein the second convolution kernel is larger than the first convolution kernel;
adopting the convolution kernel to extract the features of the image and obtain corresponding feature information:
performing first convolution neural network processing on the image by adopting a first convolution kernel so as to extract first characteristic information;
performing second convolution neural network processing on the image by adopting a second convolution kernel to extract second characteristic information;
judging whether the similarity of the first characteristic information and the second characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the second feature information as the feature information.
5. The e-commerce transaction information interaction method of claim 4, wherein the convolution kernel further comprises a third convolution kernel, the third convolution kernel being larger than the second convolution kernel;
after the step of determining whether the similarity between the first feature information and the second feature information is greater than a set feature similarity threshold, the method further includes:
if not, performing third convolution neural network processing on the image by adopting a third convolution kernel so as to extract third characteristic information;
judging whether the similarity of the second characteristic information and the third characteristic information is greater than a set characteristic similarity threshold value or not;
and if so, taking the third feature information as the feature information.
6. The e-commerce transaction information interaction method of claim 1, wherein after the step of matching the characteristic information with the text information, further comprising:
and when the matching degree of the two is smaller than a set value, sending a prompt message for inputting 'transaction information is wrong' to the user terminal or the merchant terminal.
7. A computer-readable storage medium, wherein the computer-readable storage medium stores thereon an e-commerce transaction information interaction program, which when executed implements the steps of the e-commerce transaction information interaction method according to any one of claims 1 to 6.
8. An e-commerce platform comprising a memory, a processor and an e-commerce transaction information interaction program stored on the memory and executable on the processor, the e-commerce transaction information interaction program when executed implementing the steps of the e-commerce transaction information interaction method as claimed in any one of claims 1 to 6.
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| CN109409401A (en) * | 2018-08-30 | 2019-03-01 | 深圳市买买提信息科技有限公司 | A kind of information checking method, device and system |
| CN109767828A (en) * | 2019-01-23 | 2019-05-17 | 深圳市新产业眼科新技术有限公司 | Interactive inline diagnosis cloud platform and its operation method and readable storage medium storing program for executing |
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| CN114741254A (en) * | 2022-02-21 | 2022-07-12 | 驼驼数字科技(北京)有限公司 | Method, system, computing device and storage medium for monitoring payment success rate of cross-border e-commerce platform |
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