CN112650935A

CN112650935A - Intelligent information processing method applied to e-commerce cloud service environment and cloud server

Info

Publication number: CN112650935A
Application number: CN202110099664.8A
Authority: CN
Inventors: 梁志彬
Original assignee: 梁志彬
Current assignee: Nongfu shop Development Group Co.,Ltd.
Priority date: 2021-01-25
Filing date: 2021-01-25
Publication date: 2021-04-13
Anticipated expiration: 2041-01-25
Also published as: CN112650935B

Abstract

The invention discloses an intelligent information processing method applied to an e-commerce cloud service environment and a cloud server. In the method, firstly, the acquired to-be-processed e-commerce order information is analyzed and mined so as to accurately analyze and mine the content of current candidate transaction products and the content of current candidate transaction processes. And secondly, detecting the operation state of the e-commerce to ensure the real-time performance of the state of the online e-commerce in the operation process, and further ensure the high matching performance of the detection result of the operation state of the e-commerce and the detection result of the updated transaction record. Therefore, the hot e-commerce order can be accurately and quickly obtained, and information raw materials are further provided for subsequent user portrait analysis. In addition, when the hot e-commerce orders are screened by the method, the operation state of the e-commerce platform side and the transaction state of the e-commerce platform side and the user side can be taken into consideration, so that omission of partial e-commerce orders can be avoided, and the obtained hot e-commerce orders can cover more users as far as possible.

Description

Intelligent information processing method applied to e-commerce cloud service environment and cloud server

Technical Field

The disclosure relates to the technical field of online business and information processing, in particular to an intelligent information processing method and a cloud server applied to an online business cloud service environment.

Background

Online commerce generally refers to the realization of online shopping by customers, online transactions between merchants and online electronic payments, as well as various transaction activities, financial activities and related comprehensive service activities, in an open network environment of the internet, through browsers or servers, by buyers and sellers without conspiracy.

With the increasing popularity of online shopping, the demand of people for online shopping is higher and higher, which leads various e-commerce platforms to get great development opportunities, but the demand also promotes the rise of more e-commerce platforms to cause fierce competition, and under the large background of fierce competition of the e-commerce platforms, besides improving the product quality and reducing the commodity price, the consumption tendency of more consumers is needed to be known.

However, in the existing e-commerce cloud service environment, the scale and the quantity of the transaction order information are continuously enlarged, which is undoubtedly a great challenge for order analysis of the e-commerce platform, and it is very important to find useful order information from a large amount of transaction order information to realize subsequent user mining analysis.

Disclosure of Invention

In order to solve the technical problems in the related art, the intelligent information processing method and the cloud server applied to the e-commerce cloud service environment are provided.

In a first aspect, the present invention provides an intelligent information processing method applied to an e-commerce cloud service environment, where the method includes:

analyzing the obtained to-be-processed e-commerce order information to obtain the content of the current candidate transaction product and the content of the current candidate transaction process; obtaining an e-commerce operation state detection result and an updated transaction record detection result through the e-commerce order information to be processed, the current candidate transaction product content and the current candidate transaction process content;

and processing the E-commerce operation state detection result and the updated transaction record detection result by adopting a preset intelligent processing condition, and processing a candidate E-commerce order based on the updated transaction record detection result and the E-commerce operation state detection result which meet the preset intelligent processing condition to obtain a popular E-commerce order corresponding to the to-be-processed E-commerce order information.

In a second aspect, the present invention provides a cloud server, comprising a processor, a memory, and a bus; the processor and the memory are connected through the bus in a communication mode, and the processor is used for reading the computer program from the memory and executing the computer program to realize the method.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.

The method comprises the steps of firstly analyzing and mining the acquired to-be-processed e-commerce order information to accurately analyze and mine the content of current candidate transaction products and the content of current candidate transaction processes. And secondly, detecting the operation state of the e-commerce based on the order information of the e-commerce to be processed, the content of the current candidate transaction product and the content of the current candidate transaction process so as to ensure the real-time performance of the state of the online e-commerce in the operation process, and further ensure the high matching performance of the detection result of the operation state of the e-commerce and the detection result of the updated transaction record. On the basis, the preset intelligent processing conditions are adopted to analyze and process the detection result of the operation state of the e-commerce and the updated transaction record detection result so as to ensure that the preset intelligent processing conditions meet the conditions for processing the candidate e-commerce orders, and then when the preset intelligent processing conditions are met, the transaction record detection result and the detection result of the operation state of the e-commerce are updated to process the candidate e-commerce orders, so that hot e-commerce orders can be accurately and quickly obtained, and information raw materials are provided for subsequent user portrait analysis.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

Fig. 1 is a schematic view of a communication architecture of an intelligent information processing system applied to an e-commerce cloud service environment according to an embodiment of the present invention.

Fig. 2 is a flowchart of an intelligent information processing method applied to an e-commerce cloud service environment according to an embodiment of the present invention.

Fig. 3 is a block diagram of an intelligent information processing apparatus applied to an e-commerce cloud service environment according to an embodiment of the present invention.

Fig. 4 is a schematic diagram of a hardware structure of a cloud server according to an embodiment of the present invention.

Detailed Description

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 embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

The intelligent information processing method applied to the e-commerce cloud service environment can be applied to a communication system architecture shown in fig. 1. The cloud server 200 communicates with the service platform server 300 through a network. The cloud server 200 acquires the order information of the e-commerce to be processed, and determines the initial order state content of the order information of the e-commerce to be processed, wherein the initial order state content comprises initial transaction product content and initial transaction process content; the cloud server 200 selects current candidate transaction product contents from current candidate e-commerce orders corresponding to the e-commerce order information to be processed, and acquires corresponding current candidate transaction flow contents based on the e-commerce order information to be processed; the cloud server 200 detects the operation state of the e-commerce based on the content of the current candidate transaction product, the content of the current candidate transaction process and the content of the initial order state to obtain a detection result of the operation state of the e-commerce; selecting updated candidate transaction process contents from the current candidate e-commerce orders according to the e-commerce operation state detection result, and determining an updated transaction record detection result corresponding to the current candidate e-commerce orders according to the updated candidate transaction process contents and the current candidate transaction product contents; the cloud server 200 performs time sequence fusion on the updated candidate transaction process content and the current candidate transaction product content based on the detection result of the e-commerce operation state to obtain an initial fusion content, updates the current candidate transaction product content and the current candidate transaction process content according to the first information comparison result of the initial fusion content and the initial order state content, and returns to the step of the e-commerce operation state detection until a first intelligent processing condition is met; the cloud server 200 performs candidate e-commerce order processing based on the updated transaction record detection result and the e-commerce operation state detection result meeting the first intelligent processing condition to obtain a hot e-commerce order corresponding to the e-commerce order information to be processed, and the cloud server 200 may send the hot e-commerce order to the service platform server 300.

The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, big data and artificial intelligence platform. The cloud server 200 may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, and the like. The cloud server 200 and the service platform server 300 may be directly or indirectly connected through a wired or wireless communication manner, and the application is not limited herein.

On the basis of the above-mentioned architecture, please refer to fig. 2, the embodiment of the present invention can be summarized as follows:

step a, analyzing the acquired e-commerce order information to be processed to obtain the content of current candidate transaction products and the content of current candidate transaction processes; obtaining an e-commerce operation state detection result and an updated transaction record detection result through the e-commerce order information to be processed, the current candidate transaction product content and the current candidate transaction process content;

and b, processing the E-commerce operation state detection result and the updated transaction record detection result by adopting a preset intelligent processing condition, and performing candidate E-commerce order processing on the basis of the updated transaction record detection result and the E-commerce operation state detection result which meet the preset intelligent processing condition to obtain a popular E-commerce order corresponding to the to-be-processed E-commerce order information.

By executing the method described in step a and step b, the following beneficial technical effects can be achieved: firstly, analyzing and mining the acquired to-be-processed e-commerce order information so as to accurately analyze and mine the content of current candidate transaction products and the content of current candidate transaction processes. And secondly, detecting the operation state of the e-commerce based on the order information of the e-commerce to be processed, the content of the current candidate transaction product and the content of the current candidate transaction process so as to ensure the real-time performance of the state of the online e-commerce in the operation process, and further ensure the high matching performance of the detection result of the operation state of the e-commerce and the detection result of the updated transaction record. On the basis, the preset intelligent processing conditions are adopted to analyze and process the detection result of the operation state of the e-commerce and the detection result of the updated transaction record, so that when the preset intelligent processing conditions are met, candidate e-commerce order processing is carried out by updating the detection result of the transaction record and the detection result of the operation state of the e-commerce, thus hot e-commerce orders can be accurately and quickly obtained, and information raw materials are provided for subsequent user portrait analysis. In addition, when the hot e-commerce orders are screened by the method, the operation state of the e-commerce platform side and the transaction state of the e-commerce platform side and the user side can be taken into consideration, so that omission of partial e-commerce orders can be avoided, and the integrity of the obtained hot e-commerce orders can be ensured.

In an embodiment, an intelligent information processing method applied to an e-commerce cloud service environment is further provided, which is described by taking an example that the method is applied to the cloud server 200 in fig. 1, and in this embodiment, the method includes the following steps:

s202, acquiring the order information of the e-commerce to be processed, and determining the initial order state content of the order information of the e-commerce to be processed, wherein the initial order state content comprises initial transaction product content and initial transaction process content.

The to-be-processed e-commerce order information refers to information that needs to be subjected to candidate e-commerce order processing, and the e-commerce order information may be e-commerce order label information corresponding to a service label, for example, the service label may be a digital label or a letter label. The initial order state content is obtained by identifying e-commerce order interaction content in the e-commerce order information to be processed and is used as order state content during time sequence fusion. Including initial transaction product content and initial transaction flow content. The initial transaction product content refers to initial transaction product content record information in the identified e-commerce order. The initial transaction flow content refers to initial transaction flow content record information in the identified e-commerce order.

Specifically, the cloud server 200 may acquire the e-commerce order label through the e-commerce service user terminal, and acquire the to-be-processed e-commerce order information from the e-commerce order label, where the to-be-processed e-commerce order information may be dynamic information corresponding to the service label or static information corresponding to the service label. The cloud server 200 may also directly obtain the to-be-processed e-commerce order information, for example, the cloud server 200 may obtain the to-be-processed e-commerce order information stored in the memory, or obtain the corresponding to-be-processed e-commerce order information based on an e-commerce order label stored in the memory, or the cloud server 200 may obtain the to-be-processed e-commerce order information from the internet, for example, the to-be-processed e-commerce order information may be obtained from an e-commerce interaction network, a live broadcast delivery network, an offline transaction network, and the like. The cloud server 200 may further obtain the to-be-processed e-commerce order information from the service platform server 300. Then, the cloud server 200 determines initial order state content of the e-commerce order information to be processed by using an analysis policy corresponding to the e-commerce order interaction content, where the initial order state content includes initial transaction product content and initial transaction flow content. For example, the initial order state content of the to-be-processed e-commerce order information can be determined through the e-commerce order query policy and the e-commerce order matching policy. For example, the initial transaction flow content in the initial order state content obtained after the e-commerce order interaction content is determined is the transaction flow content of the e-commerce order in the current e-commerce operation state, and cannot be specified in advance on the processing model corresponding to the candidate e-commerce order. And the content except the content of the initial transaction flow can be bound in the processing model corresponding to the candidate e-commerce order. For example, a binding relationship is established between the content of the initial transaction product and the content of the corresponding candidate transaction product in the processing model corresponding to the candidate e-commerce order.

S204, selecting current candidate transaction product content from the current candidate e-commerce order corresponding to the e-commerce order information to be processed, and acquiring corresponding current candidate transaction process content based on the e-commerce order information to be processed.

The current candidate e-commerce order is a current candidate e-commerce order corresponding to the to-be-processed e-commerce order information obtained according to a processing model corresponding to a candidate e-commerce order used in advance. The processing model corresponding to the candidate e-commerce order used in advance refers to a preset candidate e-commerce order processing model. The current candidate trading product content refers to candidate content in the current candidate e-commerce order, wherein the candidate content is defined as the candidate content of the trading product, and the feature definition is preset for the feature definition of each candidate content by a processing model corresponding to the candidate e-commerce order used in advance. Namely, the processing models corresponding to the current candidate e-commerce order and the candidate e-commerce order used in advance are represented in the same representation mode, and the content with the same number represents the same order scene. The current candidate transaction flow content refers to candidate transaction flow content obtained according to the to-be-processed e-commerce order information.

Specifically, the cloud server 200 acquires a processing model corresponding to a candidate e-commerce order used in advance. And obtaining a current candidate e-commerce order corresponding to the to-be-processed e-commerce order information according to a processing model corresponding to a candidate e-commerce order used in advance, and then selecting the content of the current candidate transaction product according to the feature definition of each content in the current candidate e-commerce order. For example, the cloud server 200 may use a machine learning model (such as a deep neural network model) to obtain the current candidate e-commerce order. And then acquiring corresponding current candidate transaction flow contents according to whether the to-be-processed e-commerce order information is dynamic e-commerce order label information.

S206, carrying out E-commerce operation state detection based on the current candidate transaction product content, the current candidate transaction process content and the initial order state content to obtain an E-commerce operation state detection result.

The detection result of the e-commerce operation state refers to a corresponding detection result of the e-commerce operation state in the comparison process of the local fusion information. The detection of the e-commerce operation state refers to the detection of operation state results based on the time sequence fusion parameters. And the E-business operation state detection result is used for representing the E-business operation state of the E-business order.

Specifically, the cloud server 200 performs time sequence fusion analysis on the current candidate transaction product content and the current candidate transaction process content, and then detects the e-commerce operation state detection result in the local fusion information comparison process to obtain the e-commerce operation state detection result.

S208, selecting updated candidate transaction process contents from the current candidate e-commerce orders according to the e-commerce operation state detection result, and determining an updated transaction record detection result corresponding to the current candidate e-commerce orders according to the updated candidate transaction process contents and the current candidate transaction product contents.

And updating the candidate transaction flow contents refers to the candidate transaction flow contents obtained after the current candidate e-commerce order is converted according to the e-commerce operation state detection result. The updated transaction record detection result refers to a transaction record detection result obtained based on a processing model of the candidate e-commerce order transaction record according to the updated candidate transaction flow content and the current candidate transaction product content, the transaction record detection result is used for representing the authentication state of the e-commerce order, and the transaction record detection result comprises a payer detection result and a payee detection result. The payer detection result is a detection result indicating the e-commerce order payment information, and the payee detection result is a detection result indicating the e-commerce order payment information.

Specifically, the cloud server 200 performs e-commerce operation state conversion on the current candidate e-commerce order according to the e-commerce operation state detection result, selects candidate transaction flow content from the candidate e-commerce order after e-commerce operation state conversion as updated candidate transaction flow content, and then determines an updated transaction record detection result corresponding to the current candidate e-commerce order according to the updated candidate transaction flow content and the current candidate transaction product content based on the processing model of the candidate e-commerce order transaction record.

S210, performing time sequence fusion on the updated candidate transaction process content and the current candidate transaction product content based on the detection result of the e-commerce operation state to obtain initial fusion content, and updating the current candidate transaction product content and the current candidate transaction process content according to the first information comparison result of the initial fusion content and the initial order state content.

Here, time-series fusion can be understood as linear fusion. The first information comparison result refers to a content information comparison result between the initial fused content and the initial order state content.

Specifically, the cloud server 200 performs e-commerce operation state conversion on the updated candidate transaction process content and the current candidate transaction product content according to the e-commerce operation state detection result to obtain converted candidate content, performs initial transaction content recording corresponding to the time sequence fusion content on the converted candidate content to obtain initial fusion content, the initial fused content includes each initial fused transaction product content and each initial fused transaction process content, a content information comparison result between each initial fused transaction product content and each corresponding initial transaction product content in the initial order state content is determined, and determining content information comparison results between each initial fusion transaction process content and each corresponding initial transaction process content in the initial order state content, and determining the sum of the difference degrees of the content information comparison results to obtain a first information comparison result.

S212 judges whether or not the first intelligent processing condition is satisfied, and if the first intelligent processing condition is satisfied, S202 is executed, and if the first intelligent processing condition is not satisfied, the process returns to S206.

S214, carrying out candidate e-commerce order processing based on the updated transaction record detection result and the e-commerce operation state detection result which meet the first intelligent processing condition, and obtaining a popular e-commerce order corresponding to the e-commerce order information to be processed.

The first intelligent processing condition refers to a condition for processing the candidate e-commerce order, and includes that the difference degree corresponding to the first information comparison result is smaller than a preset threshold value, a preset iteration number is reached, or the updated transaction record detection result and the e-commerce operation state detection result are not obviously changed abnormally. The fact that the transaction record updating detection result and the e-commerce operation state detection result do not have obvious abnormal changes means that the difference degree between the transaction record updating detection result and the e-commerce operation state detection result obtained in the previous time and the transaction record updating detection result and the e-commerce operation state detection result obtained in the next time is smaller than a preset threshold value. The hot e-commerce order refers to a candidate e-commerce order obtained by processing the candidate e-commerce order by using the updated transaction record detection result and the e-commerce operation state detection result which meet the first intelligent processing condition.

Specifically, when the cloud server 200 determines whether the first intelligent processing condition is met, when the first intelligent processing condition is met, the candidate e-commerce order processing is performed based on the updated transaction record detection result meeting the first intelligent processing condition and the e-commerce operation state detection result, and when the first intelligent processing condition is not met, the process returns to S204, that is, the e-commerce operation state detection is performed based on the current candidate transaction product content, the current candidate transaction flow content and the initial order state content, so as to obtain the e-commerce operation state detection result. And continuously looping iteration until the first intelligent processing condition is met.

In the intelligent information processing method applied to the e-commerce cloud service environment, the initial order state content of the e-commerce order information to be processed is determined by acquiring the e-commerce order information to be processed, wherein the initial order state content comprises initial transaction product content and initial transaction process content; selecting current candidate transaction product content from a current candidate e-commerce order corresponding to the e-commerce order information to be processed, then carrying out e-commerce operation state detection according to the current candidate transaction product content, the current candidate transaction flow content and the initial order state content to obtain an e-commerce operation state detection result, selecting updated candidate transaction flow content from the current candidate e-commerce order by using the e-commerce operation state detection result, selecting the candidate transaction flow content by using the e-commerce operation state detection result in each iteration, so that more accurate candidate transaction flow content can be selected, then determining an updated transaction record detection result corresponding to the current candidate e-commerce order by using the updated candidate transaction flow content and the current candidate transaction product content, so that an updated transaction record detection result is determined by using the updated candidate transaction flow content and the current candidate transaction product content in each iteration, therefore, a more accurate updated transaction record detection result can be obtained, when the intelligent processing condition is met, the updated transaction record detection result and the e-commerce operation state detection result are used for candidate e-commerce order processing, and the candidate e-commerce order processing is carried out by using the updated transaction record detection result and the e-commerce operation state detection result, so that the problem of order processing omission generated when the e-commerce order is analyzed and processed is avoided, hot e-commerce orders can be accurately and quickly obtained, and further information raw materials are provided for subsequent user portrait analysis.

In one embodiment, the step of returning the detection of the e-commerce operation state until the first intelligent processing condition is met after the current candidate transaction product content and the current candidate transaction process content are updated according to the first information comparison result of the initial fusion content and the initial order state content comprises the following steps:

s302, a first information comparison result is determined and obtained based on the initial fusion content and the initial order state content, and when the first information comparison result does not accord with a first intelligent processing condition, the current candidate e-commerce order is updated based on the updated transaction record detection result, so that an updated candidate e-commerce order is obtained.

Wherein, the updating the transaction record detection result comprises updating a payer detection result and updating a payee detection result. Updating the candidate e-commerce order refers to updating the current candidate e-commerce order by using the updated transaction record detection result to obtain the candidate e-commerce order.

Specifically, the cloud server 200 determines the sum of the difference degrees corresponding to each initial fusion content and each corresponding initial order state content comparison result to obtain a first information comparison result, and updates the current candidate e-commerce order based on the updated payer detection result and the updated payee detection result to obtain an updated candidate e-commerce order when the difference degree corresponding to the first information comparison result is smaller than a preset first information comparison difference threshold.

S304, selecting updated candidate trading product content from the updated candidate e-commerce order to obtain updated current candidate trading product content, taking the updated candidate trading process content as the updated current candidate trading process content, and returning to the step of carrying out e-commerce operation state detection on the basis of the current candidate trading product content, the current candidate trading process content and the initial order state content to obtain an e-commerce operation state detection result until the first intelligent processing condition is met.

Wherein the updated current candidate trading product content refers to candidate trading product content determined from the candidate content characteristics in the updated candidate e-commerce order.

Specifically, the cloud server 200 selects updated candidate transaction product content from the updated candidate e-commerce order to obtain updated current candidate transaction product content, uses the updated candidate transaction process content as the updated current candidate transaction process content, and returns the steps of performing e-commerce operation state detection based on the current candidate transaction product content, the current candidate transaction process content and the initial order state content, and obtaining an e-commerce operation state detection result to perform iterative loop until the first intelligent processing condition is met.

In the above embodiment, by determining the first information comparison result, when the first information comparison result does not meet the first intelligent processing condition, selecting updated candidate transaction product content from the updated candidate e-commerce order to obtain updated current candidate transaction product content, taking the updated candidate transaction process content as the updated current candidate transaction process content, and returning to the step of performing e-commerce operation state detection based on the current candidate transaction product content, the current candidate transaction process content, and the initial order state content to obtain an e-commerce operation state detection result until the first intelligent processing condition is met, so that loop iteration can be performed continuously to obtain a more accurate e-commerce operation state detection result, and the accuracy and the reliability of the determined hot e-commerce order are higher.

In one embodiment, the to-be-processed e-commerce order information is dynamic e-commerce order label information, and the initial fused content includes initial fused transaction product content and initial fused transaction process content.

S302, determining to obtain a first information comparison result based on the initial fusion content and the initial order state content, and including:

determining to obtain a transaction product content comparison result based on the initial fusion transaction product content and the initial transaction product content, and determining to obtain a transaction process content comparison result based on the initial fusion transaction process content and the initial transaction process content; and obtaining a first information comparison result of the initial fusion content and the initial order state content based on the transaction flow content comparison result and the transaction product content comparison result.

The dynamic e-commerce order label information refers to information changed in the e-commerce order label, and the transaction product content comparison result refers to an information comparison result of transaction product content record information of the initial fusion transaction product content and the initial transaction product content. The transaction flow content comparison result refers to an information comparison result of the transaction flow content record information of the initial fusion transaction flow content and the initial transaction flow content.

Specifically, when detecting that the to-be-processed e-commerce order information is dynamic e-commerce order label information, the cloud server 200 determines a difference between type information of each initial fusion transaction product content corresponding to the dynamic e-commerce order label information and type information of each corresponding initial transaction product content to obtain a difference of each transaction product content, determines a sum of the differences of each transaction product content to obtain a transaction product content comparison result, determines a difference between the type information of each initial fusion transaction process content corresponding to the dynamic e-commerce order label information and the type information of each corresponding initial transaction process content to obtain a difference of each transaction process content, and determines a sum of the differences of each transaction process content to obtain a transaction process content comparison result. And then determining the sum of the comparison result of the transaction product content and the comparison result of the transaction process content to obtain a first information comparison result of the initial fusion content and the initial order state content.

In the embodiment, when the to-be-processed e-commerce order information is dynamic e-commerce order label information, the first information comparison result of the initial fusion content and the initial order state content is obtained directly by determining the transaction product content comparison result and the transaction process content comparison result, so that the efficiency of obtaining the first information comparison result is improved.

In one embodiment, the to-be-processed e-commerce order information is static e-commerce order label information, and the initial fusion content comprises initial fusion transaction product content and initial fusion transaction process content;

s402, determining to obtain a transaction product content comparison result based on the initial fusion transaction product content and the initial transaction product content, and determining to obtain a transaction process content comparison result based on the initial fusion transaction process content and the initial transaction process content.

Specifically, when the to-be-processed e-commerce order information is static e-commerce order label information, determining the difference degree between the type information of each initial fusion transaction product content corresponding to the static e-commerce order label information and the type information of each corresponding initial transaction product content to obtain the difference degree of each transaction product content, determining the sum of the difference degrees of each transaction product content to obtain a transaction product content comparison result, determining the difference degree between the type information of each initial fusion transaction process content corresponding to the static e-commerce order label information and the type information of each corresponding initial transaction process content to obtain the difference degree of each transaction process content, and determining the sum of the difference degrees of each transaction process content to obtain a transaction process content comparison result.

S402, obtaining a historical transaction record detection result corresponding to the historical e-commerce order label information of the static e-commerce order label information, wherein the historical transaction record detection result is a transaction record detection result used by the historical e-commerce order label information in candidate e-commerce order processing.

The historical e-commerce order label information refers to historical e-commerce order label information of static e-commerce order label information.

Specifically, the cloud server 200 stores the transaction record detection result and the e-commerce operation state detection result, which are used when candidate e-commerce order processing is performed, in the local memory each time the transaction record detection result and the e-commerce operation state detection result are obtained. When the cloud server 200 needs to be used, a historical transaction record detection result corresponding to the historical e-commerce order tag information of the static e-commerce order tag information can be obtained from the memory. The cloud server 200 may also store the transaction record detection result and the e-commerce operation state detection result used by the e-commerce order label information in candidate e-commerce order processing into the service platform server each time the transaction record detection result and the e-commerce operation state detection result are obtained, and obtain the historical transaction record detection result corresponding to the historical e-commerce order label information of the static e-commerce order label information from the service platform server when the transaction record detection result and the e-commerce operation state detection result are required to be used.

S402, determining a comparison result of the historical transaction record detection result and the transaction record information for updating the transaction record detection result, and obtaining a first information comparison result of the initial fusion content and the initial order state content based on the transaction process content comparison result, the transaction product content comparison result and the transaction record information comparison result.

The transaction record information comparison result refers to the difference degree of the transaction record detection result between the historical e-commerce order label information.

Specifically, the cloud server 200 determines a detection result deviation value between the historical transaction record detection result and the updated transaction record detection result, and takes the detection result deviation value as the transaction record information comparison result. Then, the cloud server 200 adds the difference degrees corresponding to the transaction flow content comparison result, the transaction product content comparison result, and the transaction record information comparison result to obtain a first information comparison result of the initial fusion content and the initial order state content.

In the embodiment, the first information comparison result of the initial fusion content and the initial order state content is obtained by determining the historical transaction record detection result and the transaction record information comparison result of the updated transaction record detection result and based on the transaction flow content comparison result, the transaction product content comparison result and the transaction record information comparison result, and the change of the transaction record detection result of the historical e-commerce order label information can be constrained to be in line with the actual service condition as much as possible, so that the problem that the transaction record detection result is not matched with the actual service condition is avoided, and the high service matching degree and the reliability of the determined hot e-commerce order are improved.

In one embodiment, the step S202 of determining the initial transaction product content and the initial transaction process content corresponding to the to-be-processed e-commerce order information includes:

s502, E-commerce order inquiry is carried out based on the E-commerce order information to be processed, and an E-commerce order inquiry result is obtained.

The e-commerce order inquiry refers to inquiring the state of the e-commerce order in the e-commerce order information to be processed. The E-commerce order inquiry result refers to an inquiry result formed by the state of the E-commerce order in the E-commerce order information to be processed.

Specifically, the cloud server 200 queries the state of the e-commerce order by using the e-commerce order query strategy on the to-be-processed e-commerce order information to obtain an e-commerce order query result. The e-commerce order query policy may be a template matching policy, for example, a self-adaptive enhanced classifier algorithm, a neural network algorithm such as a Convolutional Neural Network (CNN) algorithm, or a support vector machine algorithm, and the like. The e-commerce order inquiry strategy is used for inquiring an inquiry result in the e-commerce order information to be processed and performing two classification judgment on a finished delivery state of the e-commerce order and an unfinished delivery state of the e-commerce order.

S502, E-commerce order interaction content detection is carried out in E-commerce order query results, and E-commerce order interaction content corresponding to the E-commerce order information to be processed is obtained.

S502, determining initial transaction product content and initial transaction flow content from e-commerce order interaction content.

The e-commerce order interaction content refers to interaction record information in an e-commerce order, and comprises interaction contents of a payment mode, a distribution mode, order placing time, order number, an e-commerce order interaction process and the like. The initial transaction product content refers to the transaction product content in the e-commerce order of the e-commerce order information to be processed. The initial transaction flow content refers to the transaction flow content in the e-commerce order of the e-commerce order information to be processed. The number of e-commerce order interaction contents can be customized.

Specifically, the cloud server 200 uses the e-commerce order interactive content detection strategy to perform e-commerce order interactive content detection in the e-commerce order query result, so as to obtain e-commerce order interactive content corresponding to the e-commerce order information to be processed, and determine initial transaction product content and initial transaction flow content from the e-commerce order interactive content. The e-commerce order interaction content detection strategy includes, but is not limited to, deep learning based algorithm and the like. In one embodiment, the content of the e-commerce order interaction can be determined through a forward feedback neural network model, and then the content of the initial transaction product and the content of the initial transaction flow can be determined according to the content information of the e-commerce order interaction content.

In one embodiment, when the to-be-processed e-commerce order information is static e-commerce order label information, e-commerce order matching tracking is performed, and initial transaction product content and initial transaction flow content are determined.

In the embodiment, the content of the e-commerce order interaction is detected through the e-commerce order information to be processed, so that the content of the initial transaction product and the content of the initial transaction flow are determined, and subsequent use is facilitated.

In one embodiment, the to-be-processed e-commerce order information is dynamic e-commerce order label information;

s204, acquiring corresponding current candidate transaction process content based on the e-commerce order label information, wherein the process comprises the following steps:

s602, acquiring a target content popularity evaluation index, fusing the current candidate trading product content to an initial trading content record according to the target content popularity evaluation index to obtain a fused trading product content, and performing E-commerce operation state detection based on the fused trading product content and the initial trading product content to obtain a dynamic E-commerce operation state detection result.

The target content heat evaluation index is a content heat evaluation index determined by detecting the content heat evaluation index from each preset content heat evaluation index. The fused transaction product content refers to initial content obtained by fusing the content of the current candidate transaction product through time sequence. The initial content is the initial genre information and the candidate content is the candidate genre information. The dynamic e-commerce operation state detection result is an e-commerce operation state detection result obtained when the e-commerce order information to be processed is dynamic e-commerce order label information and the e-commerce operation state is detected by only using the candidate transaction product content.

Specifically, when the to-be-processed e-commerce order information is dynamic e-commerce order label information, the cloud server 200 acquires a target content popularity evaluation index, and fuses the current candidate transaction product content to the initial transaction content record through a time sequence according to the target content popularity evaluation index to obtain the fused transaction product content.

Then, when the cloud server 200 obtains the content of the converged transaction product, determining a detection result of the e-commerce operation state of the converged transaction product content and the initial transaction product content, where the local convergence difference degree is small, to obtain a detection result of the dynamic e-commerce operation state. The e-commerce operation state detection result may include a product advertisement detection result and a product sale detection result. The product sale detection result refers to a detection result of ordering product sale of the e-commerce, and can be represented by a data list. The product advertisement detection result refers to a detection result of the e-commerce order product advertisement and can be represented by a data list.

S604, selecting the current candidate transaction flow content corresponding to the label information of the dynamic e-commerce order from the content query result of the candidate e-commerce order transaction flow of the current candidate e-commerce order according to the detection result of the operation state of the dynamic e-commerce.

The content query result of the candidate e-commerce order transaction flow refers to a preset query result of the flow state of the candidate e-commerce order transaction flow content.

Specifically, the cloud server 200 selects a preset number of candidate transaction execution contents from the content query results of the candidate e-commerce order transaction flows of the current candidate e-commerce order, where the candidate transaction execution contents refer to contents for synchronously executing query contents in the content query results of the candidate e-commerce order transaction flows and transaction contents of the e-commerce user terminal transaction types. And then determining a secondary fusion information comparison result of the time sequence fusion of each candidate transaction execution content and the initial transaction flow content according to the dynamic e-commerce operation state detection result, and taking the candidate transaction execution content with the minimum difference value corresponding to the secondary fusion information comparison result as the current candidate transaction flow content corresponding to the dynamic e-commerce order label information.

In the embodiment, when the to-be-processed e-commerce order information is dynamic e-commerce order label information, current candidate transaction flow content corresponding to the dynamic e-commerce order label information is selected from content query results of candidate e-commerce order transaction flows of current candidate e-commerce orders according to dynamic e-commerce operation state detection results, so that more accurate current candidate transaction flow content can be obtained, and subsequent use is facilitated.

In one embodiment, S602, acquiring a target content popularity evaluation index includes:

s702, obtaining each preset content heat degree evaluation index, and selecting the current content heat degree evaluation index from each preset content heat degree evaluation index.

The preset content heat degree evaluation index refers to a preset content heat degree evaluation index value. The current content popularity evaluation index is a content popularity evaluation index used when determining the content popularity evaluation index.

Specifically, the cloud server 200 obtains each preset content heat evaluation index, where the cloud server 200 may determine an initial content heat evaluation index value, then obtain a preset evaluation mode, and then search in directions of increasing and decreasing the content heat evaluation index to obtain each preset content heat evaluation index.

S704, fusing the content of the current candidate trading product to the initial trading content record according to the current content heat evaluation index to obtain the fused trading product content corresponding to the content heat evaluation index, carrying out E-commerce operation state detection based on the fused trading product content corresponding to the content heat evaluation index and the initial trading product content to obtain an E-commerce operation state detection result corresponding to the content heat evaluation index, and selecting the candidate trading process content corresponding to the content heat evaluation index from the content query result of the candidate E-commerce order trading process of the current candidate E-commerce order according to the E-commerce operation state detection result corresponding to the content heat evaluation index.

The fusion transaction product content corresponding to the content popularity evaluation index is fusion transaction product content obtained when the current content popularity evaluation index is used for time sequence fusion. The detection result of the e-commerce operation state corresponding to the content popularity evaluation index is an e-commerce operation state detection result obtained by detecting the e-commerce operation state according to the fused transaction product content and the initial transaction product content corresponding to the content popularity evaluation index. The candidate transaction flow content corresponding to the content popularity evaluation index refers to the candidate transaction flow content selected by using the detection result of the e-commerce operation state corresponding to the content popularity evaluation index.

Specifically, the cloud server 200 fuses the current candidate transaction product content to the initial transaction content record according to the current content popularity evaluation index to obtain a fused transaction product content corresponding to the content popularity evaluation index, and then determines the e-commerce operation state detection result of the fused transaction product content corresponding to the content popularity evaluation index and the initial transaction product content in the local fusion information comparison process to obtain the e-commerce operation state detection result corresponding to the content popularity evaluation index. And then selecting candidate transaction execution contents from the content query results of the candidate e-commerce order transaction flows of the current candidate e-commerce order according to the e-commerce operation state detection results corresponding to the content popularity evaluation indexes, and determining the candidate transaction flow contents corresponding to the content popularity evaluation indexes from the candidate transaction execution contents.

S706, carrying out E-commerce operation state detection corresponding to the content heat evaluation index based on the candidate transaction process content, the current candidate transaction product content and the initial order state content corresponding to the content heat evaluation index to obtain an E-commerce operation state detection result corresponding to the content heat evaluation index.

The e-commerce operation state detection result corresponding to the content popularity evaluation index is an e-commerce operation state detection result corresponding to the content popularity evaluation index obtained by performing e-commerce operation state detection on candidate transaction process content corresponding to the content popularity evaluation index

Specifically, the cloud server 200 performs time sequence fusion on candidate transaction process content corresponding to the content popularity evaluation index and current candidate transaction product content into an initial transaction content record to obtain initial fusion content corresponding to the content popularity evaluation index, determines an e-commerce operation state detection result when the difference between the initial fusion content corresponding to the content popularity evaluation index and the initial order state content is minimized, and obtains an e-commerce operation state detection result corresponding to the content popularity evaluation index.

S708, selecting updated candidate transaction process content of the content popularity evaluation index from the content query result of the candidate e-commerce order transaction process according to the e-commerce operation state detection result corresponding to the content popularity evaluation index, and determining an updated transaction record detection result of the content popularity evaluation index corresponding to the current candidate e-commerce order according to the updated candidate transaction process content of the content popularity evaluation index and the current candidate transaction product content.

The candidate transaction process content updated according to the content popularity evaluation index refers to the candidate transaction process content selected according to the detection result of the e-commerce operation state corresponding to the content popularity evaluation index. The updated transaction record detection result of the content popularity evaluation index is an updated transaction record detection result determined according to the content of the updated candidate transaction flow of the content popularity evaluation index. The updated transaction record detection result of the content popularity evaluation index comprises an updated payee detection result of the content popularity evaluation index and a payer detection result corresponding to the updated payee detection result of the content popularity evaluation index.

Specifically, the cloud server 200 selects candidate transaction execution contents from the content query results of the candidate e-commerce order transaction flows, and then selects updated candidate transaction flow contents of the content popularity evaluation indexes from the candidate transaction execution contents according to the e-commerce operation state detection results corresponding to the content popularity evaluation indexes. And then determining an updated transaction record detection result of the content heat evaluation index corresponding to the current candidate e-commerce order according to the updated candidate transaction process content of the content heat evaluation index and the current candidate transaction product content.

And S710, performing time sequence fusion on the candidate transaction process content updated by the content heat evaluation index and the current candidate transaction product content based on the detection result of the e-commerce operation state corresponding to the content heat evaluation index to obtain an initial fusion content corresponding to the content heat evaluation index, and updating the candidate transaction process content and the current candidate transaction product content corresponding to the content heat evaluation index according to the second information comparison result of the initial fusion content corresponding to the content heat evaluation index and the initial order state content.

The initial fusion content corresponding to the content popularity evaluation index is obtained when the updated candidate transaction process content of the content popularity evaluation index and the current candidate transaction product content are subjected to time sequence fusion according to the detection result of the e-commerce operation state corresponding to the content popularity evaluation index. The second information comparison result is a content information comparison result between the initial fusion content and the initial order state content corresponding to the content popularity evaluation index.

Specifically, the cloud server 200 performs e-commerce operation state analysis on the updated candidate transaction process content of the content popularity evaluation index and the e-commerce operation state detection result corresponding to the content popularity evaluation index of the current candidate transaction product content.

And then performing time sequence fusion on the updated candidate transaction process content of the content heat evaluation index analyzed by the electric company operation state and the current candidate transaction product content to obtain initial fusion content corresponding to the content heat evaluation index, and then determining content information comparison of the initial fusion content corresponding to the content heat evaluation index and the initial order state content to obtain a second information comparison result. And updating candidate transaction process content and current candidate transaction product content corresponding to the content popularity evaluation index according to the second information comparison result.

S712 judges whether or not the second intelligent processing condition is satisfied, and if the second intelligent processing condition is satisfied, S714 is executed, and if the second intelligent processing condition is not satisfied, the process returns to S706 for execution.

And S714, obtaining a current second information comparison result corresponding to the current content heat degree evaluation index.

The second intelligent processing condition is an intelligent processing condition that the second information comparison result is a local information comparison result corresponding to the current content heat evaluation index. The method comprises the step of detecting the updated transaction record of the content heat degree evaluation index and the e-commerce operation state corresponding to the content heat degree evaluation index, wherein the updated transaction record of the content heat degree evaluation index and the e-commerce operation state corresponding to the content heat degree evaluation index are not obviously changed abnormally, namely, the updated transaction record of the content heat degree evaluation index and the e-commerce operation state corresponding to the content heat degree evaluation index are consistent in value obtained in the last iteration and the current iteration.

Specifically, when the preset iteration number is reached, that is, when the second intelligent processing condition is met, the cloud server 200 takes the second information comparison result meeting the second intelligent processing condition as the current second information comparison result corresponding to the current content heat evaluation index. And when the preset iteration times are not reached, namely the second intelligent processing condition is not met, returning to the step S706 to continue the iteration execution.

And S716, traversing each preset content heat evaluation index to obtain each current second information comparison result corresponding to each preset content heat evaluation index, comparing each current second information comparison result to obtain a target second information comparison result, and taking the preset content heat evaluation index corresponding to the target second information comparison result as the target content heat evaluation index.

The target second information comparison result refers to the current second information comparison result with the minimum difference degree in each current second information comparison result.

Specifically, the cloud server 200 traverses each preset content heat evaluation index, that is, returns to the step of selecting the current content heat evaluation index from each preset content heat evaluation index for execution, and the selected preset content heat evaluation index is not selected repeatedly. Until obtaining each current second information comparison result corresponding to each preset content heat degree evaluation index. And then comparing each current second information comparison result to obtain a target second information comparison result, and taking a preset content heat evaluation index corresponding to the target second information comparison result as a target content heat evaluation index. The minimum difference corresponding to each preset content heat evaluation index is determined, then the minimum difference is further selected from the minimum differences to serve as a target second information comparison result, and the preset content heat evaluation index corresponding to the target second information comparison result serves as the target content heat evaluation index. Then, the cloud server 200 specifies the target content popularity evaluation index, that is, the cloud server 200 directly uses the target content popularity evaluation index when performing candidate e-commerce order processing on subsequent e-commerce order tag information.

In the above embodiment, the current second information comparison result of each preset content heat evaluation index is determined, then the target second information comparison result is determined from the current second information comparison result, and the preset content heat evaluation index corresponding to the target second information comparison result is used as the target content heat evaluation index, so that the obtained target content heat evaluation index is more accurate.

In one embodiment, the step of updating candidate transaction process content and current candidate transaction product content corresponding to the content popularity evaluation index according to the second information comparison result of the initial fusion content and the initial order state content corresponding to the content popularity evaluation index and returning to the step of detecting the e-commerce operation state corresponding to the content popularity evaluation index until a second intelligent processing condition is met includes:

and when the second information comparison result does not accord with the second intelligent processing condition, updating the current candidate e-commerce order based on the updated transaction record detection result of the content heat degree evaluation index to obtain an updated candidate e-commerce order corresponding to the content heat degree evaluation index. Selecting updated candidate trading product content corresponding to the content heat evaluation index from the updated candidate e-commerce order corresponding to the content heat evaluation index, taking the updated candidate trading product content corresponding to the content heat evaluation index as current candidate trading product content, taking the updated candidate trading process content of the content heat evaluation index as candidate trading process content corresponding to the content heat evaluation index, returning to the step of carrying out e-commerce operation state detection based on the content heat evaluation index level based on the candidate trading process content corresponding to the content heat evaluation index, the current candidate trading product content and the initial order state content until a second intelligent processing condition is met.

The candidate updated e-commerce order corresponding to the content heat degree evaluation index is a candidate e-commerce order obtained by using an updated transaction record detection result of the content heat degree evaluation index. The updated candidate trading product content corresponding to the content popularity evaluation index is the candidate trading product content selected from the updated candidate e-commerce order corresponding to the content popularity evaluation index.

Specifically, when the difference degree corresponding to the second information comparison result is not less than the information comparison difference degree threshold of the preset content heat degree evaluation index, the cloud server 200 updates the current candidate e-commerce order according to the update transaction record detection result of the content heat degree evaluation index, so as to obtain an update candidate e-commerce order corresponding to the content heat degree evaluation index.

In the above embodiment, when the second information comparison result does not meet the second intelligent processing condition, the iterative execution is continuously performed, so that the obtained current second information comparison result is more accurate.

In one embodiment, S602, performing e-commerce operation status detection based on the fused transaction product content and the initial transaction product content to obtain a dynamic e-commerce operation status detection result, includes:

s802, a first initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information is obtained, and the current candidate transaction product content is fused to an initial transaction content record based on the first initial e-commerce operation state detection result to obtain a first dynamic fusion transaction product content.

The first initial e-commerce operation state detection result refers to a preset initialized e-commerce operation state detection result. The first dynamic fusion trading product content is fusion trading product content obtained by performing time sequence fusion on dynamic e-commerce order label information corresponding to current candidate trading product content.

Specifically, the cloud server 200 obtains a first initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information, performs e-commerce operation state analysis on each current candidate transaction product content according to the first initial e-commerce operation state detection result to obtain each current candidate transaction product content after the e-commerce operation state analysis, and performs time sequence fusion on each current candidate transaction product content after the e-commerce operation state analysis to the initial transaction content record to obtain each first dynamic fusion transaction product content.

S804, a third information comparison result is determined and obtained based on the first dynamic fusion transaction product content and the initial transaction product content.

The third information comparison result refers to a content information comparison result between the content of the first dynamic fusion transaction product and the content of the initial transaction product, and the content information comparison result may be represented by graph data or a list.

Specifically, the cloud server 200 determines an information comparison result of each first dynamic fusion transaction product content and the corresponding initial transaction product content, and then determines a sum of the difference degrees corresponding to the information comparison result to obtain a third information comparison result. In one embodiment, a corresponding weight may be set for each first dynamic fusion transaction product content, when it is determined that the information comparison result of each first dynamic fusion transaction product content is obtained, the corresponding weight is determined to obtain a weighted information comparison result, and then the sum of the difference degrees corresponding to the weighted information comparison result is determined to obtain a third information comparison result.

S806, judging whether the third intelligent processing condition is satisfied, executing S808a when the third intelligent processing condition is satisfied, executing S808b when the third intelligent processing condition is not satisfied, and returning to S802 for execution.

S808a, using the first initial e-commerce operation state detection result meeting the third intelligent processing condition as a dynamic e-commerce operation state detection result.

S808b, adjusting the first initial e-commerce operation state detection result according to the third information comparison result, and returning to the step of fusing the current candidate transaction product content to the initial transaction content record based on the first initial e-commerce operation state detection result to obtain the first dynamic fusion transaction product content until the third information comparison result meets the third intelligent processing condition.

Specifically, the cloud server 200 performs reverse iteration to optimize the first initial e-commerce operation state detection result according to the third information comparison result, obtains the adjusted first initial e-commerce operation state detection result, then returns to fuse the current candidate transaction product content to the initial transaction content record based on the first initial e-commerce operation state detection result, performs iteration execution in the step of obtaining the first dynamic fusion transaction product content until the third information comparison result meets the third intelligent processing condition, and takes the first initial e-commerce operation state detection result meeting the third intelligent processing condition as the dynamic e-commerce operation state detection result.

In the above embodiment, the first initial e-commerce operation state detection result is optimized through reverse iteration, and when the third intelligent processing condition is met, the first initial e-commerce operation state detection result meeting the third intelligent processing condition is used as the dynamic e-commerce operation state detection result, so that the obtained dynamic e-commerce operation state detection result is more accurate.

In one embodiment, the to-be-processed e-commerce order information is static e-commerce order label information; s204, acquiring corresponding current candidate transaction process content based on the to-be-processed e-commerce order information, wherein the process comprises the following steps:

and acquiring historical candidate transaction flow content corresponding to the historical e-commerce order label information of the static e-commerce order label information, wherein the historical candidate transaction flow content is the candidate transaction flow content in the candidate e-commerce order corresponding to the historical e-commerce order label information, and the historical candidate transaction flow content is taken as the current candidate transaction flow content.

Specifically, when the to-be-processed e-commerce order information is static e-commerce order label information, it is indicated that the to-be-processed e-commerce order information has historical e-commerce order label information, at this time, the cloud server 200 directly obtains historical candidate transaction flow content corresponding to the historical e-commerce order label information, and takes the historical candidate transaction flow content as current candidate transaction flow content corresponding to the to-be-processed e-commerce order information. In the embodiment, the historical candidate transaction flow contents are directly used as the current candidate transaction flow contents corresponding to the to-be-processed e-commerce order information, so that the candidate transaction flow contents can be shared, and the processed popular e-commerce orders can meet the synchronous use requirements of as many service providers as possible.

s206, carrying out E-commerce operation state detection based on the current candidate transaction product content, the current candidate transaction process content and the initial order state content to obtain an E-commerce operation state detection result, wherein the detection result comprises the following steps:

s902, acquiring a second initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information, and fusing the current candidate transaction product content and the current candidate transaction process content to an initial transaction content record based on the second initial e-commerce operation state detection result to obtain dynamic initial fusion content.

And the second initial e-commerce operation state detection result refers to an initialized e-commerce operation state detection result corresponding to the dynamic e-commerce order label information. The detection result of the e-commerce operation state comprises a product sale detection result and a product advertisement detection result. The second initial e-commerce operation state detection result may be the same as or different from the first initial e-commerce operation state detection result.

Specifically, the cloud server 200 obtains a second initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information, performs e-commerce operation state detection on the current candidate transaction product content and the current candidate transaction process content according to the second initial e-commerce operation state detection result, namely performs product sale analysis on the current candidate transaction product content and the current candidate transaction process content according to a product sale detection result in the second initial e-commerce operation state detection result, performs product advertisement analysis on the current candidate transaction product content and the current candidate transaction process content after the product sale analysis according to a product advertisement detection result in the second initial detection result to obtain an e-commerce operation state analysis result, and then fuses the e-commerce operation state analysis result to the initial transaction content record through a time sequence to obtain a dynamic initial fusion content, the dynamic initial fusion content includes the initial fusion content corresponding to the current candidate trading product content and the initial fusion content corresponding to the current candidate trading process content.

And S904, determining to obtain a fourth information comparison result based on the dynamic initial fusion content and the initial order state content.

The fourth information comparison result refers to a content information comparison result of the dynamic initial fusion content and the initial order state content.

Specifically, the cloud server 200 determines content information comparison between the dynamic initial fusion content and the initial order state content to obtain a fourth information comparison result, the cloud server 200 determines content difference between the transaction product content in the dynamic initial fusion content and the transaction product content in the corresponding initial order state content, then determines content difference between the transaction process content in the dynamic initial fusion content and the transaction process content in the corresponding initial order state content, and then determines the sum of the content differences to obtain the fourth information comparison result.

S906 judges whether or not the fourth information comparison result satisfies the fourth intelligent processing condition, and if so, executes S908a, and if not, executes S908b and returns to S902.

S908b, adjusting the second initial carrier operation status detection result according to the fourth information comparison result.

S908a, using the second initial e-commerce operation state detection result meeting the fourth intelligent processing condition as the e-commerce operation state detection result corresponding to the dynamic e-commerce order label information.

The fourth intelligent processing condition means that the difference degree corresponding to the fourth information comparison result is smaller than a preset threshold value. The fourth intelligent processing condition may be that a preset number of iterations is reached. The fourth intelligent processing condition may also be that the second initial provider operation state detection result obtained in the current iteration and the second initial provider operation state detection result obtained in the previous iteration do not have obvious abnormal changes.

Specifically, the cloud server 200 determines whether the fourth information comparison result meets a fourth intelligent processing condition, performs reverse iterative optimization according to the fourth information comparison result when the fourth information comparison result does not meet the fourth intelligent processing condition, thereby adjusting the second initial provider operation state detection result, and returns to S902 to continue iterative execution. And when the fourth intelligent processing condition is met, taking the second initial e-commerce operation state detection result meeting the fourth intelligent processing condition as the e-commerce operation state detection result corresponding to the dynamic e-commerce order label information.

In the above embodiment, the detection result of the e-commerce operation state is initialized, then the initialized detection result of the e-commerce operation state is continuously adjusted in a loop iteration manner, and when the fourth intelligent processing condition is met, the detection result of the second initial e-commerce operation state meeting the fourth intelligent processing condition is used as the detection result of the e-commerce operation state corresponding to the dynamic e-commerce order label information, so that the obtained detection result of the e-commerce operation state is more accurate.

In one embodiment, the to-be-processed e-commerce order information is static e-commerce order label information;

s1002, acquiring a third initial e-commerce operation state detection result corresponding to static e-commerce order label information, and fusing the current candidate transaction product content and the current candidate transaction process content to an initial transaction content record according to the third initial e-commerce operation state detection result to obtain static initial fusion content.

And the third initial e-commerce operation state detection result refers to an initialized e-commerce operation state detection result corresponding to the static e-commerce order label information. The static initial fusion content refers to initial fusion content obtained by fusion according to the detection result of the operation state of the third initial e-commerce.

Specifically, the cloud server 200 obtains a third initial e-commerce operation state detection result corresponding to the static e-commerce order label information, performing product sale analysis on the current candidate transaction product content and the current candidate transaction process content according to the product sale detection result in the third initial e-commerce operation state detection result, then according to the product advertisement detection result in the third initial E-business operation state detection result, the current candidate transaction product content and the current candidate transaction flow content are subjected to product advertisement analysis to obtain the current candidate transaction product content and the current candidate transaction flow content after the E-business operation state analysis, the current candidate transaction product content and the current candidate transaction flow content after the E-business operation state analysis are fused into the initial transaction content record to obtain static initial fusion content, the static initial fused content includes initial fused transaction product content and initial fused transaction flow content.

And S1004, determining to obtain a fifth information comparison result based on the static initial fusion content and the initial order state content, and obtaining a historical e-commerce operation state detection result corresponding to the historical e-commerce order tag information of the static e-commerce order tag information, wherein the historical e-commerce operation state detection result is an e-commerce operation state detection result of a candidate e-commerce order corresponding to the historical e-commerce order tag information.

The fifth information comparison result refers to a content information comparison result between the static initial fusion content and the initial order state content.

Specifically, the cloud server 200 determines content information comparison results of all initial fusion transaction product contents in the static initial fusion content and initial transaction product contents in the corresponding initial order state content to obtain content information comparison results of all transaction product contents, then determines content information comparison results of all initial fusion transaction process contents in the static initial fusion content and initial transaction process contents in the corresponding initial order state content to obtain content information comparison results of all transaction process contents, and then determines the sum of the content information comparison results of all transaction product contents and the difference degrees of the content information comparison results of all transaction process contents to obtain a fifth information comparison result. At this time, the cloud server 200 obtains a historical e-commerce operation state detection result corresponding to the historical e-commerce order tag information of the static e-commerce order tag information, where the historical e-commerce operation state detection result is an e-commerce operation state detection result of a candidate e-commerce order corresponding to the historical e-commerce order tag information.

And S1006, determining an e-commerce operation state information comparison result of the historical e-commerce operation state detection result and the third initial e-commerce operation state detection result, and obtaining a target fifth information comparison result according to the fifth information comparison result and the e-commerce operation state information comparison result.

The e-commerce operation state information comparison result refers to an information comparison result between the historical e-commerce operation state detection result and the third initial e-commerce operation state detection result. The e-commerce operation state information comparison result may include a product sale information comparison result and a product advertisement information comparison result. The product sale information comparison result is the product sale detection result in the detection result of the operation state of the e-commerce, and the product advertisement information comparison result is the product advertisement detection result in the detection result of the operation state of the e-commerce

Specifically, the cloud server 200 determines a product sales information comparison result between a product sales detection result in the historical e-commerce operation state detection result and a product sales detection result in the third initial e-commerce operation state detection result, then determines a product advertisement information comparison result between a product advertisement detection result in the historical e-commerce operation state detection result and a product advertisement detection result in the third initial e-commerce operation state detection result, and then determines the sum of the difference degrees of the product sales information comparison result and the product advertisement information comparison result to obtain an e-commerce operation state information comparison result. And then, the sum of the difference degrees of the fifth information comparison result and the e-commerce operation state information comparison result is determined to obtain a target fifth information comparison result. In one embodiment, corresponding weights may be set for the fifth information comparison result and the e-commerce operation state information comparison result, and the information comparison result after weighting may be determined.

And S1008, judging whether the fifth intelligent processing condition is met, executing S1010a when the fifth intelligent processing condition is met, executing S1010b when the fifth intelligent processing condition is not met, and returning to the step S1002 for execution.

S1010b, adjusting a third initial e-commerce operation state detection result corresponding to the static e-commerce order label information according to the target fifth information comparison result, and returning to the step of fusing the current candidate transaction product content and the current candidate transaction process content to the initial transaction content record according to the third initial e-commerce operation state detection result to obtain the static initial fused content.

S1010a, taking the third initial e-commerce operation state detection result meeting the fifth intelligent processing condition as an e-commerce operation state detection result corresponding to the static e-commerce order label information.

The fifth intelligent processing condition means that the difference degree corresponding to the target fifth information comparison result is smaller than a preset threshold, the fifth intelligent processing condition may also be that a preset iteration number is reached, or the fifth intelligent processing condition may also be that a third initial power company operation state detection result obtained by the current iteration and a third initial power company operation state detection result obtained by the previous iteration do not have an obvious abnormal change.

Specifically, the server continuously performs loop iteration according to a fifth intelligent processing condition to adjust a third initial e-commerce operation state detection result, and when the fifth intelligent processing condition is met, the third initial e-commerce operation state detection result meeting the fifth intelligent processing condition is used as an e-commerce operation state detection result corresponding to the static e-commerce order label information.

In the above embodiment, the third initial e-commerce operation state detection result meeting the fifth intelligent processing condition can be found as the e-commerce operation state detection result corresponding to the static e-commerce order label information by continuously adjusting the third initial e-commerce operation state detection result, so that the accuracy of obtaining the e-commerce operation state detection result corresponding to the static e-commerce order label information is improved.

In one embodiment, S208, selecting and updating candidate transaction flow contents from the current candidate e-commerce order according to the e-commerce operation status detection result, includes:

and S1102, acquiring preset number of transaction process configuration files in the content query result of the candidate e-commerce order transaction process of the current candidate e-commerce order.

The content query result of the candidate e-commerce order transaction flow refers to a content query result corresponding to the preset candidate e-commerce order transaction flow content.

Specifically, the cloud server 200 obtains preset number of transaction process configuration files in content query results of candidate e-commerce order transaction processes of the current candidate e-commerce order.

And S1104, acquiring transaction type identification information, and selecting corresponding candidate transaction execution contents from the preset number of transaction process configuration files according to the transaction type identification information.

The candidate transaction execution content refers to the content of synchronous execution of the query content in the content query result of the candidate e-commerce order transaction flow and the transaction content of the e-commerce user terminal transaction type. The transaction type identification information refers to a transaction type corresponding to the e-commerce service user terminal, namely, identification information corresponding to the e-commerce service user terminal when the e-commerce service user terminal conducts transaction within a preset time period.

Specifically, the cloud server 200 acquires the transaction type identification information, and then selects the content with the most matched transaction content from the preset number of transaction process configuration files according to the transaction type identification information as each candidate transaction execution content with the preset number corresponding to the preset number of transaction process configuration files. And determining corresponding candidate transaction execution contents from each transaction flow configuration file.

And S1106, fusing the candidate transaction execution contents to the initial transaction content record according to the detection result of the e-commerce operation state to obtain the transaction execution fusion contents.

The transaction execution fusion content is initial fusion content obtained by fusing candidate transaction execution content to the initial transaction content record through a time sequence.

Specifically, the cloud server 200 performs product sale analysis on each candidate transaction execution content according to a product sale detection result in the e-commerce operation state detection result, then performs product advertisement analysis according to a product advertisement detection result in the e-commerce operation state detection result to obtain each candidate transaction execution content after the e-commerce operation state analysis, and then fuses each candidate transaction execution content after the e-commerce operation state analysis to the initial transaction content record through a time sequence to obtain each transaction execution fusion content.

And S1108, determining to obtain a sixth information comparison result based on each transaction execution fusion content and the initial transaction process content, comparing the sixth information comparison result corresponding to each transaction execution fusion content to obtain a target sixth information comparison result, and taking the candidate transaction execution content corresponding to the target sixth information comparison result as the updated candidate transaction process content corresponding to the initial transaction process content.

The sixth information comparison result is a content information comparison result between the transaction execution fusion content and the initial transaction flow content. The target sixth information comparison result refers to a difference minimum information comparison result in sixth information comparison results corresponding to each transaction execution fusion content.

Specifically, current initial transaction process content is determined from each initial transaction process content, sixth information comparison results of each transaction execution fusion content and the current initial transaction process content are determined, a sixth information comparison result with the minimum difference degree is determined from the sixth information comparison results, and candidate transaction execution content corresponding to the sixth information comparison result with the minimum difference degree is used as updated candidate transaction process content corresponding to the current initial transaction process content. And determining candidate transaction execution contents corresponding to the initial transaction process contents as updated candidate transaction process contents corresponding to each initial transaction process content. For example, there are 20 groups in the initial transaction flow content and 40 groups in the candidate transaction execution content. Randomly selecting an initial transaction flow content from the initial transaction flow content, then determining the content information comparison result of the 40 groups of candidate transaction execution contents and the initial transaction flow content to obtain 40 groups of content information comparison results, determining the content information comparison result with the minimum difference degree from the 40 groups of candidate transaction execution contents, then taking the corresponding candidate transaction execution contents as the updated candidate transaction flow contents of the selected initial transaction flow content, and sequentially selecting the corresponding updated candidate transaction flow contents from the candidate transaction execution contents for each initial transaction flow content.

In the embodiment, the candidate transaction execution content is determined from the content query result of the candidate e-commerce order transaction flow of the current candidate e-commerce order, and then the updated candidate transaction flow content is determined from the candidate transaction execution content based on the e-commerce operation state detection result, so that the updated candidate transaction flow content consistent with the initial transaction flow content and the characteristic definition can be obtained, and the accuracy of the obtained updated candidate transaction flow content is ensured.

In one embodiment, the step S1104 of obtaining the transaction type identification information, and selecting corresponding candidate transaction execution contents from the preset number of transaction process configuration files according to the transaction type identification information includes:

s1502, determining a current transaction process configuration file from a preset number of transaction process configuration files, selecting an initial candidate content from the current transaction process configuration file, and determining transaction chain identification information of the initial candidate content.

The current transaction process configuration file refers to a transaction process configuration file which needs to be determined to correspondingly update the transaction process content at present. The initial candidate content is a candidate content arbitrarily selected by the current transaction flow configuration file. The trade chain identification information of the initial candidate content is obtained according to the trade chain configuration file of the initial candidate content. The trade chain profile of the initial candidate content is the profile that best matches the associated trade chain profile of all the profiles in which it resides.

Specifically, the cloud server 200 determines a current transaction flow configuration file from a preset number of transaction flow configuration files, selects an initial candidate content from the current transaction flow configuration file, and then determines to obtain transaction chain identification information of the initial candidate content.

And S1502, acquiring transaction type identification information, and performing content clustering operation according to the transaction chain identification information and the transaction type identification information to obtain transaction content clustering information.

And S1502, when the transaction content clustering information does not accord with the preset transaction content clustering condition, returning to the step of selecting the initial candidate content from the current transaction process configuration file, and when the transaction content clustering information accords with the preset transaction content clustering condition, taking the initial candidate content which accords with the preset transaction content clustering condition as the candidate transaction execution content corresponding to the current transaction process configuration file.

The transaction content clustering information refers to the transaction content clustering distribution weight of the correlation detection result of the transaction chain configuration file of the initial candidate content and the transaction type of the e-commerce business user terminal. The preset transaction content clustering condition means that the transaction content clustering distribution weight of the correlation detection result of the transaction chain configuration file of the initial candidate content and the transaction type of the e-commerce business user terminal is less than the preset transaction content clustering distribution weight, namely the preset transaction content clustering distribution weight is closest to 1. Specifically, the cloud server 200 obtains the transaction type identification information, and performs content clustering operation according to the transaction chain identification information and the transaction type identification information to obtain transaction content clustering information.

And then when the transaction content clustering information does not accord with the preset transaction content clustering condition, returning to the step of selecting initial candidate content from the current transaction process configuration file, and when the transaction content clustering information accords with the preset transaction content clustering condition, taking the initial candidate content which accords with the preset transaction content clustering condition as candidate transaction execution content corresponding to the current transaction process configuration file. And sequentially selecting candidate transaction execution contents corresponding to the preset number of transaction process configuration files.

In the embodiment, the content, in the candidate content, of which the transaction chain configuration file and the transaction type of the e-commerce user terminal are closest to the preset reference type is used as the candidate transaction execution content, so that the accuracy and the real-time performance of the obtained candidate transaction execution content are improved.

In one embodiment, updating the transaction record detection result includes updating a payer detection result and updating a payee detection result;

s214, performing candidate e-commerce order processing based on the updated transaction record detection result and the e-commerce operation state detection result meeting the first intelligent processing condition, to obtain a popular e-commerce order corresponding to the e-commerce order information to be processed, including:

s1602, acquiring a processing model of the candidate e-commerce order transaction record, and inputting the updated payer detection result and the updated payee detection result which meet the first intelligent processing condition into the processing model of the candidate e-commerce order transaction record to obtain the candidate e-commerce order of the transaction record.

S1602, carrying out E-commerce operation state analysis on the candidate transaction record E-commerce order based on the E-commerce operation state detection result meeting the first intelligent processing condition to obtain a popular E-commerce order.

The processing model corresponding to the candidate e-commerce order is a set of contents of the N candidate e-commerce orders, namely the candidate e-commerce orders are very dense business cloud data. The candidate transaction record e-commerce order refers to a processing model corresponding to the obtained candidate e-commerce order with the updated transaction record detection result. The hot e-commerce order refers to a candidate e-commerce order which is analyzed and processed and corresponds to the e-commerce order in the e-commerce order information to be processed.

Specifically, the processing model for obtaining the candidate e-commerce order transaction record inputs the updated payer detection result and the updated payee detection result which meet the first intelligent processing condition into the processing model for the candidate e-commerce order transaction record to be determined, so as to obtain the candidate e-commerce order, wherein the e-commerce operation state detection result comprises an updated product sale detection result and an updated product advertisement detection result. And analyzing the e-commerce operation state of the candidate transaction record e-commerce order based on the e-commerce operation state detection result meeting the first intelligent processing condition to obtain a hot e-commerce order.

In the embodiment, the candidate e-commerce order is processed by using the updated transaction record detection result and the e-commerce operation state detection result which meet the first intelligent processing condition, so that the obtained hot e-commerce order has high instantaneity, service matching performance and reliability.

In a specific embodiment, an intelligent information processing method applied to an e-commerce cloud service environment is provided, specifically:

and acquiring the e-commerce order information to be processed, and judging whether the e-commerce order information to be processed is dynamic e-commerce order label information.

When the to-be-processed e-commerce order information is dynamic e-commerce order label information, determining initial order state content of the to-be-processed e-commerce order information, and selecting current candidate transaction product content from current candidate e-commerce orders corresponding to the to-be-processed e-commerce order information.

Obtaining each preset content heat degree evaluation index, selecting a current content heat degree evaluation index from each preset content heat degree evaluation index, fusing the current candidate transaction product content to an initial transaction content record according to the current content heat degree evaluation index to obtain a fused transaction product content corresponding to the content heat degree evaluation index, and carrying out E-commerce operation state detection based on the fused transaction product content corresponding to the content heat degree evaluation index and the initial transaction product content to obtain an E-commerce operation state detection result corresponding to the content heat degree evaluation index.

Selecting candidate transaction process content corresponding to the content heat evaluation index from content query results of candidate e-commerce order transaction processes of a current candidate e-commerce order according to e-commerce operation state detection results corresponding to the content heat evaluation index, performing e-commerce operation state detection corresponding to the content heat evaluation index based on the candidate transaction process content corresponding to the content heat evaluation index, the current candidate transaction product content and the initial order state content to obtain e-commerce operation state detection results corresponding to the content heat evaluation index, selecting updated candidate transaction process content of the content heat evaluation index from the content query results of the candidate e-commerce order transaction processes according to the e-commerce operation state detection results corresponding to the content heat evaluation index, and determining updated transaction record detection results of the content heat evaluation index corresponding to the current candidate e-commerce order according to the updated candidate transaction process content of the content heat evaluation index and the current candidate transaction product content.

And performing time sequence fusion on the updated candidate transaction process content of the content heat evaluation index and the current candidate transaction product content based on the electric company operation state detection result corresponding to the content heat evaluation index to obtain initial fusion content corresponding to the content heat evaluation index, updating the candidate transaction process content and the current candidate transaction product content corresponding to the content heat evaluation index according to the second information comparison result of the initial fusion content and the initial order state content corresponding to the content heat evaluation index, and returning to the step of electric company operation state detection corresponding to the content heat evaluation index until a second intelligent processing condition is met to obtain a current second information comparison result corresponding to the current content heat evaluation index.

Traversing each preset content heat evaluation index to obtain each current second information comparison result corresponding to each preset content heat evaluation index, comparing each current second information comparison result to obtain a target second information comparison result, and taking the preset content heat evaluation index corresponding to the target second information comparison result as the target content heat evaluation index.

And fusing the content of the current candidate transaction product to the initial transaction content record according to the target content heat evaluation index to obtain the content of the fused transaction product, and detecting the operation state of the e-commerce based on the content of the fused transaction product and the content of the initial transaction product to obtain a dynamic e-commerce operation state detection result.

And selecting current candidate transaction flow contents corresponding to the to-be-processed e-commerce order information from the content query results of the candidate e-commerce order transaction flows of the current candidate e-commerce order according to the dynamic e-commerce operation state detection result. And acquiring a second initial e-commerce operation state detection result corresponding to the e-commerce order information to be processed, and fusing the current candidate transaction product content and the current candidate transaction process content to the initial transaction content record based on the second initial e-commerce operation state detection result to obtain dynamic initial fusion content.

Determining to obtain a fourth information comparison result based on the dynamic initial fusion content and the initial order state content; adjusting a second initial e-commerce operation state detection result according to the fourth information comparison result, and returning to a step of fusing the current candidate transaction product content and the current candidate transaction process content into an initial transaction content record based on the second initial e-commerce operation state detection result to obtain dynamic initial fusion content until the fourth information comparison result meets a fourth intelligent processing condition; and taking the second initial e-commerce operation state detection result meeting the fourth intelligent processing condition as an e-commerce operation state detection result corresponding to the e-commerce order information to be processed.

Acquiring preset number of transaction process configuration files in a content query result of a candidate e-commerce order transaction process of a current candidate e-commerce order, determining the current transaction process configuration file from the preset number of transaction process configuration files, selecting initial candidate content from the current transaction process configuration file, and determining transaction chain identification information of the initial candidate content; acquiring transaction type identification information, and performing content clustering operation according to the transaction chain identification information and the transaction type identification information to obtain transaction content clustering information; and when the transaction content clustering information does not accord with the preset transaction content clustering condition, returning to the step of selecting initial candidate content from the current transaction process configuration file, and when the transaction content clustering information accords with the preset transaction content clustering condition, taking the initial candidate content which accords with the preset transaction content clustering condition as candidate transaction execution content corresponding to the current transaction process configuration file.

And fusing each candidate transaction execution content to the initial transaction content record according to the detection result of the e-commerce operation state to obtain each transaction execution fusion content, determining to obtain a sixth information comparison result based on each transaction execution fusion content and the initial transaction process content, comparing the sixth information comparison result corresponding to each transaction execution fusion content to obtain a target sixth information comparison result, and taking the candidate transaction execution content corresponding to the target sixth information comparison result as the updated candidate transaction process content corresponding to the initial transaction process content.

Determining an updated transaction record detection result corresponding to the current candidate e-commerce order according to the updated candidate transaction process content and the current candidate transaction product content, performing time sequence fusion on the updated candidate transaction process content and the current candidate transaction product content based on the e-commerce operation state detection result to obtain an initial fusion content, determining a transaction product content comparison result based on the initial fusion transaction product content and the initial transaction product content, and determining to obtain a transaction process content comparison result based on the initial fusion transaction process content and the initial transaction process content; and when the first information comparison result does not accord with the first intelligent processing condition, updating the current candidate e-commerce order based on the updated transaction record detection result to obtain an updated candidate e-commerce order.

And selecting updated candidate trading product content from the updated candidate e-commerce order to obtain updated current candidate trading product content, taking the updated candidate trading process content as the updated current candidate trading process content, and returning to the step of detecting the e-commerce operation state based on the current candidate trading product content, the current candidate trading process content and the initial order state content to obtain an e-commerce operation state detection result until a first intelligent processing condition is met.

And processing the candidate e-commerce order based on the updated transaction record detection result and the e-commerce operation state detection result which meet the first intelligent processing condition to obtain a popular e-commerce order corresponding to the e-commerce order information to be processed.

When the to-be-processed e-commerce order information is static e-commerce order label information, e-commerce order matching tracking is conducted on the to-be-processed e-commerce order information to obtain initial order state content, and current candidate transaction product content is selected from current candidate e-commerce orders corresponding to the to-be-processed e-commerce order information.

Acquiring a third initial e-commerce operation state detection result and a target content heat evaluation index corresponding to the e-commerce order information to be processed, fusing the current candidate transaction product content and the current candidate transaction flow content to an initial transaction content record according to the third initial e-commerce operation state detection result and the target content heat evaluation index to obtain static initial fusion content, determining to obtain a fifth information comparison result based on the static initial fusion content and the initial order state content, acquiring a historical e-commerce operation state detection result corresponding to historical e-commerce order label information of the e-commerce order information to be processed, wherein the historical e-commerce operation state detection result is the e-commerce operation state detection result of the candidate e-commerce order corresponding to the historical e-commerce order label information, and determining the e-commerce operation state information comparison result of the historical e-commerce operation state detection result and the third initial e-commerce operation state detection result, and obtaining a target fifth information comparison result according to the fifth information comparison result and the e-commerce operation state information comparison result.

And adjusting a third initial e-commerce operation state detection result corresponding to the e-commerce order information to be processed according to the target fifth information comparison result, returning to the step of fusing the current candidate transaction product content and the current candidate transaction process content into the initial transaction content record according to the third initial e-commerce operation state detection result and the target content heat evaluation index to obtain static initial fusion content until the target fifth information comparison result meets a fifth intelligent processing condition, and taking the third initial e-commerce operation state detection result meeting the fifth intelligent processing condition as the e-commerce operation state detection result corresponding to the e-commerce order information to be processed.

Acquiring preset number of transaction process configuration files in a content query result of a candidate e-commerce order transaction process of a current candidate e-commerce order, determining the current transaction process configuration file from the preset number of transaction process configuration files, selecting initial candidate content from the current transaction process configuration file, and determining transaction chain identification information of the initial candidate content; acquiring transaction type identification information, and performing content clustering operation according to the transaction chain identification information and the transaction type identification information to obtain transaction content clustering information; when the transaction content clustering information does not accord with the preset transaction content clustering condition, returning to the step of selecting initial candidate content from the current transaction process configuration file, and when the transaction content clustering information accords with the preset transaction content clustering condition, taking the initial candidate content which accords with the preset transaction content clustering condition as candidate transaction execution content corresponding to the current transaction process configuration file; fusing each candidate transaction execution content to the initial transaction content record according to the detection result of the e-commerce operation state to obtain each transaction execution fusion content; and determining to obtain a sixth information comparison result based on each transaction execution fusion content and the initial transaction process content, comparing the sixth information comparison result corresponding to each transaction execution fusion content to obtain a target sixth information comparison result, taking the candidate transaction execution content corresponding to the target sixth information comparison result as the updated candidate transaction process content corresponding to the initial transaction process content, and determining the updated transaction record detection result corresponding to the current candidate e-commerce order according to the updated candidate transaction process content and the current candidate transaction product content.

Performing time sequence fusion on the updated candidate transaction process content and the current candidate transaction product content based on the detection result of the e-commerce operation state and the target content heat evaluation index to obtain initial fusion content, determining to obtain a transaction product content comparison result based on the initial fusion transaction product content and the initial transaction product content, and determining to obtain a transaction process content comparison result based on the initial fusion transaction process content and the initial transaction process content; acquiring a historical transaction record detection result corresponding to historical e-commerce order label information of the e-commerce order information to be processed, wherein the historical transaction record detection result is a transaction record detection result used by the historical e-commerce order label information when candidate e-commerce orders are processed; determining a transaction record information comparison result of the historical transaction record detection result and the updated transaction record detection result, obtaining a first information comparison result of the initial fusion content and the initial order state content based on the transaction process content comparison result, the transaction product content comparison result and the transaction record information comparison result, and updating the current candidate e-commerce order based on the updated transaction record detection result to obtain an updated candidate e-commerce order when the first information comparison result does not accord with a first intelligent processing condition.

Based on the same inventive concept, the invention also provides a block diagram of an intelligent information processing device 40 applied to an e-commerce cloud service environment, and the device comprises the following functional modules.

The e-commerce order information analysis module 41 is configured to analyze the obtained to-be-processed e-commerce order information to obtain current candidate transaction product content and current candidate transaction flow content; and obtaining the detection result of the e-commerce operation state and the updated transaction record detection result through the e-commerce order information to be processed, the current candidate transaction product content and the current candidate transaction process content.

And the hot e-commerce order determining module 42 is configured to process the e-commerce operation state detection result and the updated transaction record detection result by using a preset intelligent processing condition, and perform candidate e-commerce order processing based on the updated transaction record detection result and the e-commerce operation state detection result meeting the preset intelligent processing condition to obtain a hot e-commerce order corresponding to the e-commerce order information to be processed.

On the basis, please refer to fig. 4 in combination, which provides a cloud server 200, including a processor 210, a memory 220 connected to the processor 210, and a bus 230; wherein, the processor 210 and the memory 220 complete communication with each other through the bus 230; the processor 210 is used to call the program instructions in the memory 220 to execute the above-mentioned method.

Further, a readable storage medium is provided, on which a program is stored, which when executed by a processor implements the method described above.

It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims

1. An intelligent information processing method applied to an e-commerce cloud service environment is characterized by comprising the following steps:

2. The method according to claim 1, characterized in that the obtained to-be-processed e-commerce order information is analyzed to obtain current candidate transaction product content and current candidate transaction flow content; obtaining the detection result of the e-commerce operation state and the detection result of the updated transaction record through the to-be-processed e-commerce order information, the current candidate transaction product content and the current candidate transaction process content, wherein the steps of the method comprise:

acquiring the order information of the e-commerce to be processed, and determining the initial order state content of the order information of the e-commerce to be processed; wherein the initial order state content comprises initial trading product content and initial trading process content;

selecting current candidate transaction product content from the current candidate e-commerce order corresponding to the to-be-processed e-commerce order information, and acquiring corresponding current candidate transaction flow content based on the to-be-processed e-commerce order information;

carrying out E-commerce operation state detection based on the current candidate transaction product content, the current candidate transaction process content and the initial order state content to obtain an E-commerce operation state detection result;

selecting updated candidate transaction process contents from the current candidate e-commerce order according to the e-commerce operation state detection result, and determining an updated transaction record detection result corresponding to the current candidate e-commerce order according to the updated candidate transaction process contents and the current candidate transaction product contents;

processing the E-commerce operation state detection result and the updated transaction record detection result by adopting preset intelligent processing conditions, and processing candidate E-commerce orders based on the updated transaction record detection result and the E-commerce operation state detection result which meet the preset intelligent processing conditions to obtain hot E-commerce orders corresponding to the to-be-processed E-commerce order information:

performing time sequence fusion on the updated candidate transaction process content and the current candidate transaction product content based on the detection result of the electric company operation state to obtain initial fusion content, updating the current candidate transaction product content and the current candidate transaction process content according to a first information comparison result of the initial fusion content and the initial order state content, and returning to the step of detecting the electric company operation state until a first intelligent processing condition is met;

and processing candidate e-commerce orders based on the updated transaction record detection result and the e-commerce operation state detection result which meet the first intelligent processing condition to obtain popular e-commerce orders corresponding to the e-commerce order information to be processed.

3. The method according to claim 2, wherein the step of returning to the e-commerce operation status detection until a first intelligent processing condition is met after updating the current candidate transaction product content and the current candidate transaction flow content according to the first information comparison result of the initial fusion content and the initial order status content comprises:

determining to obtain a first information comparison result based on the initial fusion content and the initial order state content, and updating the current candidate e-commerce order based on the updated transaction record detection result to obtain an updated candidate e-commerce order when the first information comparison result does not accord with a first intelligent processing condition;

and selecting updated candidate trading product content from the updated candidate e-commerce order to obtain updated current candidate trading product content, taking the updated candidate trading process content as the updated current candidate trading process content, and returning to the step of carrying out e-commerce operation state detection on the basis of the current candidate trading product content, the current candidate trading process content and the initial order state content to obtain an e-commerce operation state detection result until a first intelligent processing condition is met.

4. The method according to claim 3, wherein the to-be-processed e-commerce order information is dynamic e-commerce order tag information, and the initial fused content comprises initial fused transaction product content and initial fused transaction flow content; determining to obtain a first information comparison result based on the initial fusion content and the initial order state content, including:

determining to obtain a transaction product content comparison result based on the initial fusion transaction product content and the initial transaction product content, and determining to obtain a transaction process content comparison result based on the initial fusion transaction process content and the initial transaction process content;

and obtaining a first information comparison result of the initial fusion content and the initial order state content based on the transaction flow content comparison result and the transaction product content comparison result.

5. The method according to claim 3, wherein the to-be-processed e-commerce order information is static e-commerce order label information, and the initial fused content comprises initial fused transaction product content and initial fused transaction flow content; determining to obtain a first information comparison result based on the initial fusion content and the initial order state content, including:

acquiring a historical transaction record detection result corresponding to the historical e-commerce order label information of the static e-commerce order label information; the historical transaction record detection result is a transaction record detection result used by the historical e-commerce order label information in candidate e-commerce order processing;

and determining a transaction record information comparison result of the historical transaction record detection result and the updated transaction record detection result, and obtaining a first information comparison result of the initial fusion content and the initial order state content based on the transaction process content comparison result, the transaction product content comparison result and the transaction record information comparison result.

6. The method according to claim 2, wherein the determining of the initial transaction product content and the initial transaction flow content corresponding to the pending e-commerce order information comprises:

e-commerce order inquiry is carried out based on the to-be-processed E-commerce order information to obtain an E-commerce order inquiry result;

e-commerce order interaction content detection is carried out in the E-commerce order query result to obtain E-commerce order interaction content corresponding to the E-commerce order information to be processed;

and determining initial transaction product content and initial transaction flow content from the e-commerce order interaction content.

7. The method of claim 2, wherein the pending e-commerce order information is dynamic e-commerce order tag information; the step of obtaining corresponding current candidate transaction flow contents based on the e-commerce order label information comprises the following steps:

acquiring a target content popularity evaluation index, fusing the current candidate transaction product content to an initial transaction content record according to the target content popularity evaluation index to obtain a fused transaction product content, and performing E-commerce operation state detection based on the fused transaction product content and the initial transaction product content to obtain a dynamic E-commerce operation state detection result;

selecting current candidate transaction flow contents corresponding to the dynamic e-commerce order label information from content query results of candidate e-commerce order transaction flows of the current candidate e-commerce order according to the dynamic e-commerce operation state detection result;

the obtaining of the target content popularity evaluation index includes:

acquiring each preset content heat degree evaluation index, and selecting a current content heat degree evaluation index from each preset content heat degree evaluation index;

fusing the content of the current candidate transaction product to an initial transaction content record according to the current content heat evaluation index to obtain fused transaction product content corresponding to the content heat evaluation index, and carrying out E-commerce operation state detection based on the fused transaction product content corresponding to the content heat evaluation index and the initial transaction product content to obtain an E-commerce operation state detection result corresponding to the content heat evaluation index;

selecting candidate transaction process contents corresponding to the content heat evaluation indexes from the content query results of the candidate e-commerce order transaction processes of the current candidate e-commerce order according to the e-commerce operation state detection results corresponding to the content heat evaluation indexes;

carrying out E-commerce operation state detection corresponding to the content heat evaluation index based on the candidate transaction process content corresponding to the content heat evaluation index, the current candidate transaction product content and the initial order state content to obtain an E-commerce operation state detection result corresponding to the content heat evaluation index;

selecting updated candidate transaction process contents of the content popularity evaluation indexes from the content query results of the candidate e-commerce order transaction processes according to the e-commerce operation state detection results corresponding to the content popularity evaluation indexes;

determining an updated transaction record detection result of the content heat evaluation index corresponding to the current candidate e-commerce order according to the updated candidate transaction process content of the content heat evaluation index and the current candidate transaction product content;

performing time sequence fusion on the updated candidate transaction process content of the content heat evaluation index and the current candidate transaction product content based on the e-commerce operation state detection result corresponding to the content heat evaluation index to obtain initial fusion content corresponding to the content heat evaluation index, updating the candidate transaction process content and the current candidate transaction product content corresponding to the content heat evaluation index according to the initial fusion content corresponding to the content heat evaluation index and the second information comparison result of the initial order state content, returning to the e-commerce operation state detection step corresponding to the content heat evaluation index until a second intelligent processing condition is met, and obtaining a current second information comparison result corresponding to the current content heat evaluation index;

traversing each preset content heat evaluation index to obtain each current second information comparison result corresponding to each preset content heat evaluation index, comparing each current second information comparison result to obtain a target second information comparison result, and taking the preset content heat evaluation index corresponding to the target second information comparison result as the target content heat evaluation index;

wherein, the step of updating the candidate transaction process content and the current candidate transaction product content corresponding to the content heat evaluation index according to the second information comparison result of the initial fusion content corresponding to the content heat evaluation index and the initial order state content, and returning to the step of detecting the e-commerce operation state corresponding to the content heat evaluation index until a second intelligent processing condition is met comprises the following steps:

when the second information comparison result does not accord with a second intelligent processing condition, updating the current candidate e-commerce order based on the updated transaction record detection result of the content heat evaluation index to obtain an updated candidate e-commerce order corresponding to the content heat evaluation index;

and selecting the updated candidate trading product content corresponding to the content heat evaluation index from the updated candidate e-commerce order corresponding to the content heat evaluation index, taking the updated candidate trading product content corresponding to the content heat evaluation index as the current candidate trading product content, taking the updated candidate trading process content of the content heat evaluation index as the candidate trading process content corresponding to the content heat evaluation index, and returning to the step of carrying out content heat evaluation index-level-based e-commerce operation state detection on the basis of the candidate trading process content corresponding to the content heat evaluation index, the current candidate trading product content and the initial order state content to obtain an e-commerce operation state detection result corresponding to the content heat evaluation index until a second intelligent processing condition is met.

8. The method of claim 7, wherein performing e-commerce operation status detection based on the fused transaction product content and the initial transaction product content to obtain a dynamic e-commerce operation status detection result comprises:

acquiring a first initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information, and fusing the current candidate transaction product content to an initial transaction content record based on the first initial e-commerce operation state detection result to obtain a first dynamic fusion transaction product content;

determining to obtain a third information comparison result based on the first dynamic fusion transaction product content and the initial transaction product content;

adjusting the first initial e-commerce operation state detection result according to the third information comparison result, and returning to the step of fusing the current candidate transaction product content to an initial transaction content record based on the first initial e-commerce operation state detection result to obtain a first dynamic fusion transaction product content until the third information comparison result meets a third intelligent processing condition;

and taking the first initial e-commerce operation state detection result meeting the third intelligent processing condition as the dynamic e-commerce operation state detection result.

9. The method of claim 1, wherein the pending e-commerce order information is static e-commerce order label information; the step of acquiring corresponding current candidate transaction flow contents based on the to-be-processed e-commerce order information comprises the following steps:

acquiring historical candidate transaction flow content corresponding to historical e-commerce order label information of the static e-commerce order label information; the historical candidate transaction flow content is candidate transaction flow content in a candidate e-commerce order corresponding to the historical e-commerce order label information;

taking the historical candidate transaction flow contents as the current candidate transaction flow contents;

alternatively, the first and second electrodes may be,

the to-be-processed e-commerce order information is dynamic e-commerce order label information; the detecting the operation state of the e-commerce based on the content of the current candidate transaction product, the content of the current candidate transaction process and the content of the initial order state to obtain a detection result of the operation state of the e-commerce comprises the following steps:

acquiring a second initial e-commerce operation state detection result corresponding to the dynamic e-commerce order label information, and fusing the current candidate transaction product content and the current candidate transaction process content to an initial transaction content record based on the second initial e-commerce operation state detection result to obtain dynamic initial fusion content;

determining to obtain a fourth information comparison result based on the dynamic initial fusion content and the initial order state content;

adjusting the second initial e-commerce operation state detection result according to the fourth information comparison result, and returning to the step of fusing the current candidate transaction product content and the current candidate transaction process content into an initial transaction content record based on the second initial e-commerce operation state detection result to obtain dynamic initial fusion content until the fourth information comparison result meets a fourth intelligent processing condition;

and taking the second initial e-commerce operation state detection result meeting the fourth intelligent processing condition as the e-commerce operation state detection result corresponding to the dynamic e-commerce order label information.

10. A cloud server comprising a processor, a memory, and a bus; the processor and the memory are communicatively connected through the bus, and the processor is used for reading the computer program from the memory and executing the computer program to realize the method of any one of the above claims 1 to 9.