CN113129099B - Social electronic commerce retail processing method and system based on blockchain communication - Google Patents
Social electronic commerce retail processing method and system based on blockchain communication Download PDFInfo
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9536—Search customisation based on social or collaborative filtering
Abstract
The application relates to the technical field of social electronic commerce, in particular to a social electronic commerce retail processing method and system based on blockchain communication, and the method and the system improve the accurate evaluation of the sales capacity of target social users by acquiring higher authenticity of original data from a blockchain network based on blockchain communication, select the target social users which are more matched with commodities to be sold as social salesmen, help to improve sales volume, and improve the viscosity of consumers by means of the target social users.
Description
Technical Field
The application relates to the technical field of social electronic commerce, in particular to a social electronic commerce retail processing method and system based on blockchain communication.
Background
Social electronic commerce is to realize buying and selling transactions through social communication between people, and concretely refers to business activities of selling goods or services by utilizing an internet social tool based on an interpersonal relationship network. The social electronic commerce retail is mainly based on 'people', surrounds 'people, goods and fields', and has shopping guiding function, social elements and social propagation multi-level rebate mechanism.
Wherein, a social salesman (such as a traffic blog) playing a role of "shopping guide" in social electronic commerce transaction activities is at the end of network sales, and the transaction activities are directly carried out through a social platform or a social tool. But ultimately the e-commerce operator who provides goods or services to the consumer. And the E-commerce operator cooperates with the social salesman to finally realize the acquisition and retail.
Currently, more electronic commerce operators conduct targeted commodity recommendation by social salesmen through acquiring social behavior data of consumers and through interest preference of the consumers.
In view of the above-mentioned related art, the inventor considers that there is a disadvantage that the e-commerce operator lacks knowledge about social salesmen, and may relate to the viscosity of consumers, thereby affecting sales of commodities.
Disclosure of Invention
In order to further improve sales volume and consumer viscosity, the application provides a social electronic commerce retail processing method, a system and a device based on blockchain communication.
In a first aspect, the social electronic commerce retail processing method based on blockchain communication provided by the application adopts the following technical scheme:
a social electronic commerce retail processing method based on blockchain communication comprises the following steps:
acquiring original data of a target social user in a blockchain network; the raw data includes social traffic data;
preprocessing the obtained original data to obtain a classification label of the target social user; the classification tags include social type tags;
comparing the classification labels with preset commodity identifications to form matching degree;
selecting target social users meeting preset conditions according to the matching degree;
and establishing a link with the target social user through the node.
By adopting the technical scheme, the blockchain is a shared database, and the data or information stored in the shared database has the advantages of 'non-falsifiability', 'whole-course mark remaining', 'disclosure transparency', 'collective maintenance', and the like. And the pass certificate is a negotiable encrypted digital rights voucher of the blockchain. The reality of the original data obtained from the blockchain network based on the blockchain pass is higher, the sales capability of an e-commerce operator to the target social users according to the original data can be improved, so that the target social users which are more matched with the commodities to be sold can be conveniently selected, the sales amount is improved, and the viscosity of the consumers to the commodities is improved by means of the target social users.
Optionally, the social traffic data includes a number of user nodes focusing on the target social user and a period of focus of the user nodes focusing on the target social user.
By adopting the technical scheme, the network people number of the target social users can be judged through the node number, so that the electronic commerce operator can calculate the possible radiation range of the commodity to be sold; the attention period of the node can be used for judging the vein viscosity of the target social user, so that the E-commerce operator can estimate the sales volume of the commodity.
Optionally, the original data further includes first browsed data of the historical recommended commodity of the target social user and processing behaviors of other nodes associated with the target social user on the historical recommended commodity; including but not limited to, bartering, ordering, forwarding, collecting, browsing, or screening.
By adopting the technical scheme, if the e-commerce operator establishes a link with the target social user through the node, the target social user is added into the commodity sales chain, so that the target social user is formed, and other nodes associated with the target social user become potential consumers of the commodity. Therefore, the historical record of the processed recommended commodity of the target social user, namely the first browsed data of the historical recommended commodity of the target social user and the processing behavior of other nodes associated with the target social user on the historical recommended commodity, is analyzed, so that the consumption habit of the potential consumer and the shopping guide capacity of the target social user on the potential consumer can be known.
Optionally, the method further comprises:
acquiring original data of at least two target social users; the target social user recommends historical recommended commodities matched with preset commodity identifications;
acquiring processing behaviors of simultaneously paying attention to historical recommended goods of at least two target social users respectively by user nodes of the target social users; the processing actions include, but are not limited to, bartering, ordering, forwarding, collecting, browsing, or screening;
giving different scores to the target social users according to the processing behaviors; the achievement, ordering, forwarding, collecting, browsing or shielding are sequentially given with scores from high to low;
weighting and calculating scores corresponding to different target social users within a preset time period to form sales capability parameters corresponding to the target social users;
and determining preset conditions according to the sales capability parameters.
By adopting the technical scheme, the target social users with the same potential consumers are compared, and the sales capacity of each target social user is judged, so that the E-commerce operator can select the target social users which are more matched with the commodities to be sold.
Optionally, preprocessing the obtained raw data to obtain a classification tag of the target social user, including:
establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises the target social user and other nodes focusing on the target social user; the relationship chain forming the relationship network diagram is the association between the target social user and other nodes;
determining the associated weight of the target social user in the relation network diagram according to the social information transfer model;
calculating expected values of influence of the target social users on other node propagation information and propagation information types through the relation network graph and the association weights;
and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
By adopting the technical scheme, the expected value of the influence on the information type and the corresponding propagation information of the target social contact in the relationship network can be analyzed through the relationship network diagram, and then the classification label of the target social contact user is formed, so that the classification label is more detailed, the comparison with the commodity identification of the commodity to be sold is facilitated, and the comparison precision is improved.
Optionally, the method further comprises the step of updating the original data of the target social user regularly and updating the classification label.
By adopting the technical scheme, the social network is updated and changed in real time, and the original data of the target users at different time points can be different, so that the requirement of the latest potential consumers associated with the target social users can be met by updating the original data regularly.
In a second aspect, the social electronic commerce retail processing system based on blockchain communication provided by the application adopts the following technical scheme:
a blockchain-based social electronic commerce retail processing system comprising:
the acquisition module is used for acquiring the original data of the target social user in the blockchain network; the raw data includes social traffic data;
the processing module is used for completing the following steps:
preprocessing the obtained original data to obtain a classification label of the target social user; the classification tags include social type tags;
comparing the classification labels with preset commodity identifications to form matching degree;
selecting target social users meeting preset conditions according to the matching degree;
and establishing a link with the target social user through the node.
By adopting the technical scheme, transaction data or associated data formed by each node in the blockchain network are left with trace and have traceability, so that the original data which is acquired by the acquisition module and is associated with the target social user and broadcast in the blockchain network has higher authenticity, and the situation that a platform or a third party carries out secondary modification or color rendering on the original data can be reduced. And the original data acquired by the acquisition module is preprocessed and compared through the processing module, and a target social user meeting preset conditions is determined and used for improving the accuracy of recommending the commodity to be sold to the consumer.
Optionally, the processing module further includes a classification sub-module; the classification submodule is used for:
establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises the target social user and other nodes focusing on the target social user; the relationship chain forming the relationship network diagram is the association between the target social user and other nodes;
determining the associated weight of the target social user in the relation network diagram according to the social information transfer model;
calculating expected values of influence of the target social users on other node propagation information and propagation information types through the relation network graph and the association weights;
and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
Through the technical scheme, the expected value of the influence on the information type and the corresponding propagation information of the target social contact in the relation network can be analyzed through the relation network diagram, and then the classification label of the target social contact user is formed, so that the classification label is more detailed, the comparison with the commodity identification of the commodity to be sold is facilitated, the recommendation accuracy degree to potential consumers is improved, and the sales volume is further improved.
In a third aspect, the present application provides a computer apparatus, which adopts the following technical scheme:
computer apparatus comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor implementing the social e-commerce retail processing method when executing the computer program.
By adopting the technical scheme, the computer device capable of executing the social electronic commerce retail processing method based on blockchain communication is provided.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium storing a computer program; the computer program when executed by a processor implements the social e-commerce retail processing method. Alternatively to this, the method may comprise,
by adopting the technical scheme, the carrier of the computer program of the social electronic commerce retail processing method based on the blockchain through certificate is provided.
In summary, the application has at least the following beneficial technical effects:
1. acquiring original data of a target social user with higher authenticity, and improving accurate evaluation of sales capacity of the target social user;
2. and selecting a target social user which is more matched with the commodity to be sold as a social sales person, so that sales volume and consumer viscosity are improved.
Drawings
FIG. 1 is a block flow diagram of the process of the present application;
FIG. 2 is a flowchart showing a specific process of step S020 of the present application;
fig. 3 is a block diagram showing a processing flow of the preset condition in step S040 according to the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings 1-3 and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application discloses a social electronic commerce retail processing method based on blockchain communication.
Referring to fig. 1, a social electronic commerce retail processing method based on blockchain communication includes:
s010: acquiring original data of a target social user in a blockchain network; the raw data includes social traffic data.
The blockchain network includes a number of nodes, which may include, but are not limited to, target social users, e-commerce operators, and other user nodes that establish associations with target social users through a social platform. The user node may be concerned with the target social user, may have performed an e-commerce transaction with the target social user, etc. The social traffic data includes the number of the user nodes and the associated data.
In particular, in one embodiment, the social traffic data may be a number of user nodes that are further targeted social users and a period of interest of the user nodes to the targeted social users. The number of the aggregated people in the social network of the target social user can be judged through the number of the user nodes, so that the electronic commerce operator is facilitated to calculate the possible radiation range of the commodity to be sold; the attention period of the node can be used for judging the vein viscosity of the target social user, so that the E-commerce operator can estimate the sales volume of the commodity.
In another embodiment, the original data in step S010 may further include the first browsed data of the historical recommended commodity of the target social user and the processing behavior of other nodes associated with the target social user on the historical recommended commodity; processing actions include, but are not limited to, bartering, ordering, forwarding, collecting, browsing, or screening. For target social users with histories such as shopping guide or commodity recommendation through a social platform, expected values reflecting sales capacity of the target social users can be formed according to data such as the initial browsing data of the histories recommended commodities and the like, and the expected values are used as one of the original data, so that a more suitable target social user can be selected as a social salesperson by an e-commerce operator.
S020: preprocessing the obtained original data to obtain a classification label of the target social user; the category labels include social type labels.
The social type labels can be specifically classified into makeup, delicacies, clothing, toys, shoe bags, travel, books, leisure service or decoration articles and the like according to the types of commodities recommended by the target social users in history; the social behavior of the target social user in the social platform can be specifically classified into a baby dao, a student, a full-time blogger, a retirement person, commodity experience, a sports fan, a knowledgeable person or a game player; professional identities broadcast in the blockchain network may also be based on the targeted social users.
Referring to fig. 2, in one embodiment, step S020 is to preprocess the obtained raw data to obtain a classification tag of the target social user, including the following steps:
s021: establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises a target social user and other nodes focusing on the target social user; the relationship chain constituting the relationship network graph is the association of the target social user with other nodes.
The relationship network graph can be used for knowing the irradiation condition of the vein centering on the target social user, the relationship between the target social user and other nodes associated with the target social user can be stored in the block, and the relationship chain between the target social user and other nodes is the graph edge of the relationship network graph.
S022: and determining the associated weight of the target social user in the relation network diagram according to the social information transfer model.
The information transfer model is essentially a dynamic incomplete information countermeasure and at least comprises a sending node and a receiving node; the receiving node may also evolve into a new sending node, delivering information to other nodes, thereby constituting a delivery model. The social information transfer model is based on a blockchain network and depends on a certification technology, and the transferred information has security and distortion prevention and can be encrypted. And determining the weight of the target social user through the distribution of the information transmission path, the sending node and the receiving node.
S023: and calculating expected values of the influence of the target social user on other node propagation information and the propagated information types through the relation network graph and the association weight.
And classifying, counting and superposing according to the relation between the target social user and other nodes associated with the target social user, so that the relation network graph forms the influence of the propagation information of the target social user.
S024: and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
Different information types may form different propagation influence, and the different social type labels may be projected by associating the different information types with the corresponding information types and the influence expected values.
Such as posting information about a comment article or video related to make-up, wherein the information type of the information can include make-up; the information has larger propagation quantity (which can be counted through actions such as forwarding, collecting, reading or clicking) meeting the radiation requirement, namely the expected value of the influence of the propagation information; thus, a social type tag that the target social user has "make-up" can be obtained.
Therefore, by establishing the relation network diagram, the social type labels of the target social users can be analyzed and acquired.
Referring to fig. 1, S030: and comparing the classification labels with preset commodity identifications to form matching degree.
The method comprises the steps that commodity identifications can be preset for commodities to be sold according to aspects such as materials, application scenes, use objects, use frequency or selling price levels, and one or more commodity identifications can be preset for each commodity to be sold; in the sales process, the commodity identification can also be changed or added according to feedback of the consumers.
Specifically, a correlation list can be established between the commodity identifications and the social type labels in advance, and each commodity identification in the correlation list and each social type label can respectively form a matching value in one-to-one correspondence. And comparing each commodity identification of the commodity to be sold with the social type label of each target social user, wherein the commodity identification has at least one matching value. The degree of matching may also be formed by subjecting the matching values to, for example, direct use, screening or weighted calculation processes.
S040: and selecting target social users meeting preset conditions according to the matching degree.
The matching degree is determined through matching values of the commodity identifications and the social type labels in one-to-one correspondence. And the target social users with proper matching degree can also have the problems of different sales capacities, improper time and the like, so that the target social users can be further screened according to preset conditions.
Referring to fig. 3, in order to further improve understanding and evaluation of sales capability of a target social user, the social e-commerce retail processing method based on blockchain communication of the present application may further include:
b010: acquiring original data of at least two target social users; the target social user recommends historical recommended goods matched with the preset goods identification.
B020: acquiring processing behaviors of user nodes which pay attention to at least two target social users simultaneously on historical recommended commodities of the target social users respectively; processing actions include, but are not limited to, bartering, ordering, forwarding, collecting, browsing, or screening.
B030: giving different scores to the target social users according to the processing behaviors; the transactions, orders, forwarding, collection, browsing or screening are given a top-to-bottom score in turn.
Wherein, according to the processing actions such as the transaction, the order, the forwarding, the collection, the browsing or the shielding, the possible reactions of the potential consumers to the commodity to be sold can be presumed.
B040: and (3) weighting and calculating scores corresponding to different target social users within a preset time period to form sales capability parameters corresponding to the target social users.
The weighting calculation may be to reject scores corresponding to historical recommended commodities with smaller sales, or may be to adjust and increase or decrease scores of different target social users with different time lengths.
B050: and determining preset conditions according to the sales capability parameters.
The preset condition may be a target social user whose sales capability parameter is located before a preset ranking, and the preset ranking may be set by the e-commerce operator according to the requirement. And preferably selecting target social users with good sales capacity, and improving sales of commodities to be sold.
Target social users with the same potential consumers are compared, and the sales capacity of each target social user is judged, so that the E-commerce operator can select target social users which are more matched with the commodities to be sold.
Referring to fig. 1, S050: and establishing a link with the target social user through the node.
Through data acquisition, preprocessing and comparison, target social users matched with the commodities to be sold and meeting preset conditions are screened out, and the target social users are added into a sales network of the commodities to be sold, so that sales of the commodities and viscosity of consumers to the commodities are improved by means of influence, information types and the like of the veins and the propagation information of the target social users.
In order to keep monitoring the sales capacity of the target social users, the social electronic commerce retail processing method based on blockchain communication can further comprise the following steps: and updating the original data of the target social user at regular time, and updating the classification label.
The social network is updated and changed in real time, and the original data of the target user at different time points can be different, so that the requirement of the latest potential consumers associated with the target social user can be met by updating the original data regularly.
Based on the same design concept, the embodiment also discloses a social electronic commerce retail processing system based on blockchain communication.
The social electronic commerce retail processing system based on the blockchain communication comprises an acquisition module and a processing module.
The acquisition module is used for acquiring original data of a target social user in the blockchain network; the raw data includes social traffic data.
The processing module is used for completing the following steps:
preprocessing the obtained original data to obtain a classification label of the target social user; the category labels include social type labels;
comparing the classification labels with preset commodity identifications to form matching degree;
selecting target social users meeting preset conditions according to the matching degree;
and establishing a link with the target social user through the node.
Transaction data or associated data formed by each node in the blockchain network is left with trace and has traceability, so that original data which is acquired by the acquisition module and is associated with the target social user and broadcasted in the blockchain network has higher authenticity, and the situation that a platform or a third party carries out secondary modification or color rendering on the original data can be reduced. And the original data acquired by the acquisition module is preprocessed and compared through the processing module, and a target social user meeting preset conditions is determined and used for improving the accuracy of recommending the commodity to be sold to the consumer.
Specifically, the processing module further comprises a classification sub-module; the classification submodule is used for completing:
establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises a target social user and other nodes focusing on the target social user; the relationship chain forming the relationship network diagram is the association between the target social user and other nodes;
determining the associated weight of the target social user in the relation network diagram according to the social information transfer model;
calculating expected values of influence of the target social users on other node propagation information and propagation information types through the relation network graph and the association weights;
and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
And processing expected values reflecting the information types and the corresponding propagation information influences of the target social users in the relation network by utilizing the classification sub-module to form classification labels of the target social users, so that the classification labels are more detailed, the comparison with the commodity identifications of the commodities to be sold is facilitated, and the recommendation accuracy degree to potential consumers is improved.
The present application also provides a computer readable storage medium storing instructions capable of implementing steps in the flow of fig. 1 to 3 when loaded and executed by a processor.
The computer-readable storage medium includes, for example: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Based on the same inventive concept, an embodiment of the present application provides a computer apparatus, including a memory and a processor, where the memory stores a computer program capable of being loaded by the processor and executing a social e-commerce retail processing method based on blockchain communication as in any of fig. 1 to 3.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
The foregoing embodiments are only used to describe the technical scheme of the present application in detail, but the descriptions of the foregoing embodiments are only used to help understand the method and the core idea of the present application, and should not be construed as limiting the present application. Variations or alternatives, which are easily conceivable by those skilled in the art, are included in the scope of the present application.
Claims (6)
1. The social electronic commerce retail processing method based on blockchain communication is characterized by comprising the following steps of:
acquiring original data of a target social user in a blockchain network; the raw data includes social traffic data;
preprocessing the obtained original data to obtain a classification label of the target social user; the classification tags include social type tags;
comparing the classification labels with preset commodity identifications to form matching degree;
selecting target social users meeting preset conditions according to the matching degree;
establishing a link with a target social user through a node;
the social flow data comprises the number of user nodes focusing on the target social user and the focusing period of the user nodes focusing on the target social user;
the original data also comprises the first browsed data of the historical recommended commodity of the target social user and the processing behaviors of other nodes associated with the target social user on the historical recommended commodity; the processing behavior comprises transaction, ordering, forwarding, collection, browsing or shielding;
preprocessing the obtained original data to obtain a classification label of the target social user, wherein the preprocessing comprises the following steps:
establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises the target social user and other nodes focusing on the target social user; the relationship chain forming the relationship network diagram is the association between the target social user and other nodes;
determining the associated weight of the target social user in the relation network diagram according to the social information transfer model;
calculating expected values of influence of the target social users on other node propagation information and propagation information types through the relation network graph and the association weights;
and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
2. The blockchain-based social e-commerce retail processing method of claim 1, further comprising:
acquiring original data of at least two target social users; the target social user recommends historical recommended commodities matched with preset commodity identifications;
acquiring processing behaviors of simultaneously paying attention to historical recommended goods of at least two target social users respectively by user nodes of the target social users; the processing behavior comprises transaction, ordering, forwarding, collection, browsing or shielding;
giving different scores to the target social users according to the processing behaviors; the achievement, ordering, forwarding, collecting, browsing or shielding are sequentially given with scores from high to low;
weighting and calculating scores corresponding to different target social users within a preset time period to form sales capability parameters corresponding to the target social users;
and determining preset conditions according to the sales capability parameters.
3. The blockchain-based social electronic commerce retail processing method of claim 1, wherein: and the method also comprises the step of updating the original data of the target social user at regular time and updating the classification label.
4. Social electronic commerce retail processing system based on blockchain through certificate, characterized by comprising:
the acquisition module is used for acquiring the original data of the target social user in the blockchain network; the original data comprises social flow data, initial browsed data of historical recommended commodities of the target social user and processing behaviors of other nodes associated with the target social user on the historical recommended commodities; the social flow data comprises the number of user nodes focusing on the target social user and the focusing period of the user nodes focusing on the target social user; the processing behavior comprises transaction, ordering, forwarding, collection, browsing or shielding;
the processing module is used for completing the following steps:
preprocessing the obtained original data to obtain a classification label of the target social user; the classification tags include social type tags;
comparing the classification labels with preset commodity identifications to form matching degree;
selecting target social users meeting preset conditions according to the matching degree;
establishing a link with a target social user through a node;
the processing module further comprises a classification sub-module; the classification submodule is used for:
establishing a relationship network diagram according to the social traffic data; the relationship network diagram comprises the target social user and other nodes focusing on the target social user; the relationship chain forming the relationship network diagram is the association between the target social user and other nodes;
determining the associated weight of the target social user in the relation network diagram according to the social information transfer model;
calculating expected values of influence of the target social users on other node propagation information and propagation information types through the relation network graph and the association weights;
and obtaining the classification labels of the target social users according to the expected values and the information types of the influence of the propagation information.
5. Computer device, characterized in that it comprises a processor, a memory and a computer program stored in said memory and executable on said processor, said processor implementing the social e-commerce retail processing method according to any one of claims 1-3 when executing said computer program.
6. A computer-readable storage medium, wherein the computer storage medium stores a computer program; the computer program, when executed by a processor, implements a social e-commerce retail processing method as claimed in any one of claims 1 to 3.
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| CN202110387446.4A CN113129099B (en) | 2021-04-10 | 2021-04-10 | Social electronic commerce retail processing method and system based on blockchain communication |
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| CN202110387446.4A CN113129099B (en) | 2021-04-10 | 2021-04-10 | Social electronic commerce retail processing method and system based on blockchain communication |
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