CN112906761A - E-commerce product classification method and system - Google Patents
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Abstract
The invention provides an e-commerce product classification method and system, and relates to the technical field of e-commerce. The E-commerce product classification method comprises the following steps: acquiring user demand information and demand information of an e-commerce channel on e-commerce products; collecting the information of the e-commerce products, extracting name keywords and actual effects, and adding labels to the e-commerce products to form a product pool; acquiring a classification request of the e-commerce product after the label is added, wherein the classification request comprises a request classification tree of the e-commerce product; and matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels. The method comprises the steps of analyzing an e-commerce channel, collecting information of e-commerce products and comparing the engagement degree of the products and the e-commerce channel. In addition, the invention also provides an e-commerce product classification system, which comprises: the device comprises an acquisition module, a tag adding module, a classification module and a matching module.
Description
Technical Field
The invention relates to the technical field of electronic commerce, in particular to a method and a system for classifying electronic commerce products.
Background
Electronic commerce, called e-commerce for short, refers to transaction activities and related service activities performed in an electronic transaction manner on the Internet (Internet), an Intranet (Intranet) and a Value Added Network (VAN), and is electronization and networking of each link of the traditional business activities. Electronic commerce includes electronic money exchange, supply chain management, electronic transaction marketing, network marketing, online transaction processing, electronic data Exchange (EDI), inventory management, and automated data collection systems. In this process, information technologies utilized include: internet, extranet, email, database, electronic directory and mobile phone.
The classification of electronic products and services has very important significance in products, so that both parties can quickly find out the concerned categories, and the service range of the platform can be very clearly positioned for an e-commerce channel; the service range is determined undoubtedly by class definition and display, and in most platforms, the class definition can be performed only by the platform, so that the platform standardizes a basic product data structure and has strong control capability on platform management. In defining the class, product, service related terms and scopes, such as SPU, SKU, specification, attribute, brand, inventory, are also defined synchronously; the definition of these basic terms ranges directly specifies and influences the range of services provided by the platform.
The existing e-commerce product classification methods generally form general names of the products or services, which generally belong to the scope of the products or services, according to the names of the products or services listed in the category titles. To determine the classification of each product or service, an alphabetical classification list is looked up. Often, the classification is too rigid, and the user cannot accurately find the product required by the user. And the category system of the E-commerce product sometimes does not accord with the actual use habit of the user, and the adjustment of the original category system relates to the maintenance of the data of the historical published product, so that the workload is extremely large. In addition, the habits of the merchant who releases the product and the buyer who purchases the product may be different, and one category system cannot simultaneously satisfy the use of different terminal users.
Disclosure of Invention
The invention aims to provide an e-commerce product classification method, which comprises the steps of analyzing an e-commerce channel, collecting information of e-commerce products, comparing the fit degree of the products with the e-commerce channel, classifying and pushing the e-commerce products, combining products with complementary effects, selling the combined products online and offline, classifying the e-commerce products through the e-commerce channel, the single or combined products, and selling the combined products online or offline to form an e-commerce product classification system, and meanwhile, the e-commerce product classification method is reasonable and effective.
Another object of the present invention is to provide an e-commerce product classification system capable of operating an e-commerce product classification method.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides an e-commerce product classification method, which includes acquiring user demand information and demand information of an e-commerce channel for e-commerce products; collecting the information of the e-commerce products, extracting name keywords and actual effects, and adding labels to the e-commerce products to form a product pool; acquiring a classification request of the e-commerce product after the label is added, wherein the classification request comprises a request classification tree of the e-commerce product; and matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels.
In some embodiments of the present invention, the acquiring the user requirement information and the requirement information of the e-commerce channel for the e-commerce product includes: and acquiring historical browsing records of the user, and acquiring the demand information of the user on different e-commerce platforms through the historical browsing records of the user provided by the e-commerce platform.
In some embodiments of the invention, the method further comprises analyzing the browsing product function utility and the reason of the user requirement according to the user historical browsing records.
In some embodiments of the present invention, the collecting the commercial product information and extracting the name keyword includes: and extracting keywords in the name of the E-commerce product required by the user based on the collected historical browsing records of the user.
In some embodiments of the invention, the extracted keyword information and the analyzed product function utility are stored in a database, so that comparison and classification of e-commerce products are facilitated.
In some embodiments of the present invention, the collecting the information of the electronic commerce product and extracting the name keyword and the actual efficacy to tag the electronic commerce product to form the product pool includes: and carrying out primary classification on the products through the keywords of the name of the electronic commerce product, integrating the primary classification result with the actual efficacy, and adding corresponding labels.
In some embodiments of the present invention, the acquiring of the merchant product information includes: and obtaining the statistical browsing amount, the collection amount, the download amount, the sales amount and the selection amount of the commercial products.
In some embodiments of the present invention, the obtaining of the tagged e-commerce product classification request includes a request classification tree of the e-commerce product, where the request classification tree includes: and acquiring the product quantity of each node in the corresponding request classification tree in the e-commerce platform, and if the quantity of the e-commerce products corresponding to all nodes of at least one section of tree branch of the request classification tree is greater than or equal to a preset quantity threshold value, establishing corresponding product classification for the e-commerce products in the e-commerce platform according to all nodes of at least one section of tree branch.
In a second aspect, an embodiment of the present application provides an e-commerce product classification system, which includes an obtaining module, configured to obtain user demand information and demand information of an e-commerce channel for e-commerce products; the label adding module is used for acquiring the information of the e-commerce products, extracting name keywords and actual effects and adding labels to the e-commerce products to form a product pool; the classification module is used for acquiring a classification request of the e-commerce product after the label is added, and the classification request comprises a request classification tree of the e-commerce product; and the matching module is used for matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels.
In some embodiments of the invention, the above includes: at least one memory for storing computer instructions; at least one processor in communication with the memory, wherein the at least one processor, when executing the computer instructions, causes the system to: the device comprises an acquisition module, a tag adding module, a classification module and a matching module.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
the method comprises the steps of analyzing an E-commerce channel, collecting information of E-commerce products, comparing the degree of fit of the products with the E-commerce channel, pushing the E-commerce products in a classified mode, combining the products with complementary effects, and selling the combined products online and offline.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic step diagram of an e-commerce product classification method according to an embodiment of the present invention;
fig. 2 is a detailed step diagram of an e-commerce product classification method according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of an e-commerce product classification system according to an embodiment of the present invention.
Icon: 10-an acquisition module; 20-adding a label module; 30-a classification module; 40-matching module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Example 1
Referring to fig. 1, fig. 1 is a schematic diagram illustrating steps of a classification method for electronic commerce products according to an embodiment of the present invention, which is shown as follows:
step S100, acquiring user demand information and demand information of an E-commerce channel on E-commerce products;
in some embodiments, historical browsing records of a user are collected, the historical browsing records of the user are collected through e-commerce channel supply and network investigation, the user needs e-commerce products in different e-commerce channels, browsing record keywords are extracted, and the keywords in the name of the e-commerce product needed by the user in the collected historical browsing records of the user are extracted for subsequent comparison; analyzing and browsing the functional utility of the product, and analyzing and knowing the functional utility of the product and the reason of user demand through product inquiry provided by an e-commerce channel; and establishing a database, and storing the extracted keyword information and the analyzed product function utility into the database, so that the e-commerce products can be conveniently compared and classified.
Step S110, collecting the information of the E-commerce products, extracting name keywords and actual effects, and adding labels to the E-commerce products to form a product pool;
in some embodiments, extracting keywords of the name of the e-commerce product, and performing primary classification on the e-commerce product by extracting the keywords in the name of the product, and meanwhile, preparing for subsequent comparison; analyzing the actual efficacy of the product, integrating the information provided by the merchant and the network query result marked by the e-commerce product, analyzing the actual efficacy of the product, adding a label to the e-commerce product according to the keyword and the actual efficacy, and then gathering all the e-commerce products added with the labels together to form a product pool.
Step S120, acquiring a classification request of the e-commerce product after the label is added, wherein the classification request comprises a request classification tree of the e-commerce product;
in some embodiments, in the e-commerce platform, the fabric category includes four sub-categories for clothing, apparel, home textiles, and industry. The curtain window screening under the e-commerce platform is numerous in products, and when sellers sell the curtain window screening on the e-commerce platform, the technical attributes, the material attributes and other attributes of the products cannot be highlighted quickly, and the sellers are difficult to find the products meeting the requirements of the sellers quickly. Thus, the buyer or e-commerce channel user sends a sort request in the fabric to the e-commerce platform.
The leaf nodes of the request classification tree include at least one of a process attribute of the target product and a material attribute of the target product, for example, a request classification tree for curtain window screening is provided in the classification request, the root node of the request classification tree is the curtain window screening, the leaf nodes include curtains, wherein the curtain category is further classified into a fabric curtain, a jacquard curtain, an embroidered curtain and the like.
And step S130, matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels.
In some embodiments, name keywords are compared, product keywords in the collected e-commerce product information are compared with products in a product pool in which the name keywords of the product required by the customer are stored in an e-commerce channel, and matching items are screened out; comparing the practical efficacy of the products, comparing the practical efficacy of the E-commerce products obtained by analysis with data in a database of practical efficacy of products required by customers in an E-commerce channel, and screening matching items; and integrating the two comparisons, integrating the matching items obtained by the two comparisons to obtain a final comparison result, and transmitting the final result to an e-commerce channel.
Example 2
Referring to fig. 2, fig. 2 is a detailed step diagram of an e-commerce product classification method according to an embodiment of the present invention, which is shown as follows:
and step S200, acquiring a user historical browsing record, and acquiring the requirement information of the user on different e-commerce platforms through the user historical browsing record provided by the e-commerce platform.
And step S210, analyzing the product function utility and the reason of the user requirement according to the historical browsing records of the user.
Step S220, extracting keywords in the name of the E-commerce product required by the user based on the collected historical browsing records of the user.
And step S230, storing the extracted keyword information and the analyzed product function utility into a database, and facilitating comparison and classification of the E-commerce products.
And S240, primarily classifying the products through the keywords of the e-commerce product names, integrating the results of the primary classification with the actual efficacy, and adding corresponding labels.
And step S250, obtaining the statistical browsing amount, the collection amount, the downloading amount, the sales amount and the selection amount of the commercial products.
Step S260, obtaining the product quantity of each node in the e-commerce platform corresponding to the request classification tree, and if the e-commerce product quantity corresponding to all nodes of at least one section of the tree branch of the request classification tree is greater than or equal to a preset quantity threshold, establishing a corresponding product classification for the e-commerce product in the e-commerce platform according to all nodes of at least one section of the tree branch.
In some embodiments, after receiving the classification request, the e-commerce platform may obtain the number of corresponding products in the e-commerce platform according to all nodes of the classification tree requested in the classification request, that is, the e-commerce platform may obtain the number of the products "curtains", and may also obtain the numbers of the products "cloth curtain", the products "jacquard curtain", and the products "embroidery curtain", so as to determine whether to further classify the "curtain window screening" according to the number of the corresponding products. The e-commerce platform can search in the e-commerce platform through the keywords, and the number of corresponding products is obtained according to the search result. Further, the keyword "cloth art" and "curtain" can be obtained for the product "cloth art curtain" in a Chinese processing manner, that is, the keyword "cloth art" and "curtain" are searched in the e-commerce platform, and the number of the product "cloth art curtain" is determined according to the search result.
And if the product quantity corresponding to all nodes of at least one section of tree branch of the request classification tree is larger than or equal to a preset quantity threshold value, establishing corresponding product classification for the target product in the e-commerce platform according to all nodes of at least one section of tree branch. Wherein at least one segment comprises a root node.
For example, the preset number threshold is 2000. If the number of the product curtain in the e-commerce platform is 5000, the number of the product cloth curtain is 2200, the number of the product jacquard curtain is 1000, and the number of the product embroidered curtain is 1500.
Since the number of the products curtain and the number of the products cloth curtain exceed 2000, the classified curtains are built under the curtain window screening in the e-commerce platform, and the classified cloth curtains are built under the classified curtains, and then sellers can sell their products under the classified curtains and the classified cloth curtains, and buyers can search for their needed products under the classified curtains and the classified cloth curtains.
In addition, the e-commerce platform may store the classification request. When the number of the jacquard curtains or embroidery curtains in the e-commerce platform is more than or equal to 2000, corresponding classification is established under the classification of the curtains.
In some embodiments, if the number of products corresponding to all nodes except the root node in the request classification tree is less than or equal to a preset number threshold, the request classification tree of the target product is saved.
In some embodiments, the preset number threshold is 2000. If the number of the product curtain in the e-commerce platform is 1800, the number of the product cloth curtain is 1000, the number of the product jacquard curtain is 200, and the number of the product embroidered curtain is 300. Because the number of the products of the curtain, the fabric curtain, the jacquard curtain and the embroidery curtain does not exceed the preset number threshold, the e-commerce platform does not establish classification under the curtain window screening at present, but stores the request classification tree. After protecting the requested classification tree, the e-commerce platform monitors the number of "curtains", "cloth curtains", "jacquard curtains" and "embroidered curtains" in the requested classification tree. Once the number of a certain node in the request classification tree exceeds 2000, a corresponding classification is established under the curtain window screening.
When the category embodiment of the e-commerce platform does not meet the requirements of users, a classification request of a target product is received, whether a new classification is established for the target product is determined according to the number of the products, and an existing category classification system does not need to be changed.
Example 3
Referring to fig. 3, fig. 3 is a schematic diagram of an e-commerce product classification system module according to an embodiment of the present invention, which is shown as follows:
the acquiring module 10 is used for acquiring user demand information and demand information of an e-commerce channel on e-commerce products;
the label adding module 20 is used for collecting the information of the e-commerce products, extracting name keywords and actual effects and adding labels to the e-commerce products to form a product pool;
the classification module 30 is configured to obtain a classification request of the e-commerce product after the tag is added, where the classification request includes a request classification tree of the e-commerce product;
and the matching module 40 is used for matching the e-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the e-commerce channels.
Also included are a memory, a processor, and a communication interface, which are electrically connected, directly or indirectly, to each other to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory may be used to store software programs and modules, and the processor may execute various functional applications and data processing by executing the software programs and modules stored in the memory. The communication interface may be used for communicating signaling or data with other node devices.
The Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), etc.; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and may include more or fewer components than shown in fig. 3, or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
To sum up, the method and the system for classifying e-commerce products provided by the embodiment of the application cover analysis of an e-commerce channel, information acquisition of the e-commerce products, comparison of fit degrees of the products and the e-commerce channel, classified pushing of the e-commerce products, combination of products with complementary effects, online and offline sales of the combined products, and independent or combined products through the e-commerce channel.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. An e-commerce product classification method, comprising:
acquiring user demand information and demand information of an e-commerce channel on e-commerce products;
collecting the information of the e-commerce products, extracting name keywords and actual effects, and adding labels to the e-commerce products to form a product pool;
acquiring a classification request of the e-commerce product after the label is added, wherein the classification request comprises a request classification tree of the e-commerce product;
and matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels.
2. The method for classifying E-commerce products according to claim 1, wherein the step of acquiring the user requirement information and the requirement information of the E-commerce channels for the E-commerce products comprises the steps of:
and acquiring historical browsing records of the user, and acquiring the demand information of the user on different e-commerce platforms through the historical browsing records of the user provided by the e-commerce platform.
3. The e-commerce product classification method of claim 2, further comprising:
and analyzing the functional utility of the browsed product and the reason of the user requirement according to the historical browsing records of the user.
4. The e-commerce product classification method of claim 1, wherein the collecting e-commerce product information and extracting name keywords comprises:
and extracting keywords in the name of the E-commerce product required by the user based on the collected historical browsing records of the user.
5. The e-commerce product classification method of claim 3 or claim 4, further comprising:
and storing the extracted keyword information and the analyzed product function utility into a database, so that the e-commerce products can be compared and classified conveniently.
6. The method for classifying E-commerce products according to claim 1, wherein the step of collecting E-commerce product information and extracting name keywords and actual power effects to label the E-commerce products to form a product pool comprises the steps of:
and carrying out primary classification on the products through the keywords of the name of the electronic commerce product, integrating the primary classification result with the actual efficacy, and adding corresponding labels.
7. The e-commerce product classification method of claim 1, wherein the collecting e-commerce product information comprises:
and obtaining the statistical browsing amount, the collection amount, the download amount, the sales amount and the selection amount of the commercial products.
8. The method for classifying electronic commerce products according to claim 1, wherein the step of obtaining the tagged electronic commerce product classification request comprises a request classification tree of electronic commerce products, and comprises:
and acquiring the product quantity of each node in the corresponding request classification tree in the e-commerce platform, and if the quantity of the e-commerce products corresponding to all nodes of at least one section of tree branch of the request classification tree is greater than or equal to a preset quantity threshold value, establishing corresponding product classification for the e-commerce products in the e-commerce platform according to all nodes of at least one section of tree branch.
9. An e-commerce product classification system, comprising:
the acquisition module is used for acquiring user demand information and demand information of an e-commerce channel on e-commerce products;
the label adding module is used for acquiring the information of the e-commerce products, extracting name keywords and actual effects and adding labels to the e-commerce products to form a product pool;
the classification module is used for acquiring a classification request of the e-commerce product after the label is added, and the classification request comprises a request classification tree of the e-commerce product;
and the matching module is used for matching the E-commerce products in the product pool to the root nodes corresponding to the classification trees based on the product labels and the requirement information of the users and the E-commerce channels.
10. The e-commerce product classification system of claim 9, comprising:
at least one memory for storing computer instructions;
at least one processor in communication with the memory, wherein the at least one processor, when executing the computer instructions, causes the system to perform: the device comprises an acquisition module, a tag adding module, a classification module and a matching module.
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