CN115809900A - Resource recommendation method, electronic device and storage medium - Google Patents
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Abstract
The application relates to the technical field of computers, and provides a resource recommendation method, which comprises the following steps: responding to the recommendation request, and determining a target industry chain corresponding to the target product; determining a target position of a target product in a target industry chain; determining a correlated product type from the target industry chain based on the target location; determining a target associated product corresponding to the target product from the products corresponding to the associated product types; generating enterprise recommendation information based on the target associated product; the method and the device can help solve the problem of poor resource recommendation effect, and the target associated product is determined based on the position information of the target product and the target product in the target industry chain, and then the enterprise recommendation information is generated based on the target associated product, so that the product can be used as a gripper, enterprise resources can be matched for the target enterprise based on the association relation between the products, corresponding enterprise resources can be effectively matched for the target enterprise, and the resource recommendation effect is improved. In addition, an electronic device and a storage medium are provided.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a resource recommendation method, an electronic device, and a storage medium.
Background
With the development of information technology and the advancement of science and technology, the construction of an industrial chain model is gradually automated and intelligentized, and how to realize supply and demand matching among enterprises based on the industrial chain is a key problem.
In the related technology, an enterprise-based industrial chain is constructed based on data of different enterprises in aspects of registered capital, enterprise scale, business range, transaction relationship and the like, and corresponding enterprise resources are matched for a target enterprise based on the pre-constructed industrial chain when the target enterprise has requirements.
However, the inventor finds that the requirement matching relationship in the related art is relatively fixed in the research process, and when a target enterprise has some special requirements, especially some new business requirements, corresponding enterprise resources cannot be effectively matched for the target enterprise, which may cause a problem of poor resource recommendation effect.
Disclosure of Invention
In order to help improve the problem of poor resource recommendation effect, the application provides a resource recommendation method, an electronic device and a storage medium.
In a first aspect, the present application provides a resource recommendation method, which adopts the following technical scheme:
a resource recommendation method is used in a resource recommendation system, and the method comprises the following steps:
responding to the recommendation request, and determining a target industry chain corresponding to the target product;
determining a target location of the target product in the target industry chain;
determining an associated product type from the target industry chain based on the target location;
determining a target associated product corresponding to the target product from the products corresponding to the associated product types;
and generating enterprise recommendation information based on the target associated product.
By adopting the technical scheme, the enterprise resources can be matched for the target enterprise by taking the products as the grippers based on the incidence relation among the products without depending on the supply-demand relation among the enterprises, so that the corresponding enterprise resources can be effectively matched for the target enterprise, and the resource recommendation effect is improved.
Optionally, the determining, by the processor, a target associated product corresponding to the target product from products corresponding to the associated product type includes:
and determining target downstream products from the downstream products based on the matching relationship between the product information of the target products and the supply demand information of the downstream products corresponding to the downstream product types.
By adopting the technical scheme, the matching degree of the determined target downstream product and the target product can be improved, so that the accuracy of the determined target downstream product can be improved, and the resource recommendation effect can be improved.
Optionally, the determining, by the processor, a target associated product corresponding to the target product from products corresponding to the associated product types includes:
and determining a target upstream product from each upstream product based on the matching relationship between the product information of each upstream product corresponding to the upstream product type and the supply demand information of the target product.
By adopting the technical scheme, the matching degree of the determined target upstream product and the target product can be improved, so that the accuracy of the determined target upstream product can be improved, and the resource recommendation effect is improved.
Optionally, the generating of the enterprise recommendation information based on the target associated product includes:
determining at least one target production enterprise based on the matching relation between the target associated product and each enterprise;
and generating target recommendation information based on the intelligence information of each target enterprise, wherein the intelligence information comprises patent intelligence information.
By adopting the technical scheme, the information comprises the patent information, and the research and development level and the strength of the enterprises can be analyzed and obtained based on the patent information, so that the recommendation order among different enterprises in the recommendation information can be determined, and the quality of the target recommendation information can be improved.
Optionally, after determining the target associated product corresponding to the target product from the products corresponding to the associated product types, the method further includes:
and taking the target associated product as a target product, returning and executing the steps of determining the target position of the target product, determining the type of the associated product based on the target position and determining the target associated product corresponding to the target product from the products corresponding to the type of the associated product.
By adopting the technical scheme, the product chain corresponding to the target product can be determined by taking the target product as the center, and the enterprise recommendation information corresponding to the product chain is obtained, so that the whole industry chain recommendation can be conveniently carried out based on the target product, and the resource recommendation effect can be improved.
Optionally, before the target associated product is taken as a target product, the method further includes:
outputting enterprise recommendation information;
responding to a recommendation information selection instruction, and executing a step of taking the target associated product as a target product for the target associated product indicated by the recommendation information selection instruction.
By adopting the technical scheme, the resource recommendation method and the resource recommendation system can further recommend according to the operation of the user, so that the accuracy of resource recommendation can be improved.
Optionally, the recommendation request includes requester identification information, and before determining the target industry chain corresponding to the target product, the method further includes:
determining a candidate product based on the requester identifying information;
under the condition that the number of the candidate products is more than two, outputting selection prompt information corresponding to each candidate product;
in response to a candidate product selection instruction, determining a candidate product indicated by the candidate product selection instruction as the target product.
By adopting the technical scheme, when the number of the determined candidate products is more than two, the target product is determined from each candidate product based on the candidate product selection instruction, so that the determined target product can be matched with the actual requirement of the user, and the accuracy of resource recommendation can be improved.
Optionally, the recommending request includes identification information of a requester, and the determining a target industry chain corresponding to the target product includes:
determining a candidate industry chain corresponding to the target product;
when the number of the candidate industry chains is two or more, the target industry chain is determined from each of the candidate industry chains based on the requester identification information.
By adopting the technical scheme, the manual intervention in the process of determining the target industrial chain can be reduced, so that the operation difficulty of the system can be reduced, and meanwhile, the accuracy of the determined target industrial chain can be improved, so that the accuracy of resource recommendation can be improved.
In a second aspect, the present application provides an electronic device, which adopts the following technical solutions:
an electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, the at least one application configured to: any of the resource recommendation methods provided in the first aspect is performed.
In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform any one of the resource recommendation methods provided in the first aspect.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the method can help solve the problem of poor resource recommendation effect caused by the fact that when enterprise resources are directly matched based on a pre-constructed industrial chain, the requirement matching relationship among enterprises is relatively fixed and corresponding enterprise resources cannot be effectively matched for target enterprises; because the products are used as the grippers, enterprise resources are matched for the target enterprise based on the incidence relation among the products, and the supply-demand relation among the enterprises is not required, corresponding enterprise resources can be effectively matched for the target enterprise, and the resource recommendation effect is improved;
2. the product chain corresponding to the target product can be determined by taking the target product as the center, and meanwhile, the enterprise recommendation information corresponding to the product chain is obtained, so that the whole industry chain recommendation can be conveniently carried out based on the target product, and therefore, the resource recommendation effect can be improved.
Drawings
Fig. 1 is a schematic flowchart of a resource recommendation method provided in an embodiment of the present application;
FIG. 2 is a flowchart illustrating another resource recommendation method provided in an embodiment of the present application;
FIG. 3 is a flowchart illustrating a further resource recommendation method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to fig. 1-4 and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
The embodiment of the application provides a resource recommendation method, which is used in a resource recommendation system. With particular reference to fig. 1, the resource recommendation method comprises the following steps:
Wherein, the product refers to: anything that can be used and consumed by a person and that can satisfy a need, including tangible items, intangible services, and/or combinations thereof; specifically, the tangible articles may be raw materials, parts, and the like, and the intangible services may be obstetrical and research services, raw material research and development services, product promotion services, product transportation services, and the like, and the embodiment does not limit the types of products.
The target industry chain is composed of at least two product nodes, and the target industry chain comprises product nodes corresponding to target products.
Optionally, the recommendation request may be automatically generated by the system, such as: the system generates a recommendation request under the condition that the browsing operation of the user is detected; or may be generated in response to a user's trigger operation, such as: the system generates the recommendation request when receiving a recommendation request operation of the user, which is not limited in the embodiment.
In one example, the recommending request includes requester identification information, and before determining a target industry chain corresponding to the target product, the recommending request further includes: the target product is determined based on the requester identification information.
The requester identification information may be information automatically obtained by the system when the recommendation request is generated, such as: user account information, etc.; or it may be information input by the user himself, such as: enterprise identification, etc., and the embodiment does not limit the manner of obtaining the user identification.
Correspondingly, in the case that the requester identification information includes user account information, determining the target product based on the requester identification information includes: determining a target product based on the historical query record corresponding to the account information and/or the corresponding subject information; in a case where the requester identification information is an enterprise identification, determining subject information based on the enterprise identification, and then determining a target product based on the subject information, which is not limited in this embodiment.
In one example, the subject information includes product type information, where the target product is determined based on the product type information of the business.
According to the technical scheme, the target product can be automatically determined based on the identification information of the requester without manual input, so that the requirement on a user in the recommendation process can be reduced, and the problem that errors are easy to occur in manual input is solved, so that the accuracy of resource recommendation can be improved.
Since the number of products corresponding to the requester identification information may be two or more, further, in an example, determining a target industry chain corresponding to the target product includes: determining a candidate product based on the requester identifying information; under the condition that the number of the candidate products is more than two, outputting selection prompt information corresponding to each candidate product, responding to a product selection instruction, and determining the candidate product indicated by the product selection instruction as a target product; in the case where there is one candidate product, the candidate product is determined as the target product.
The method for outputting the selection prompt information corresponding to the candidate product may be displaying the selection prompt information corresponding to each candidate product on an operation interface of the resource recommendation system, or may also be sending the selection prompt information to other systems through a data interface for output by other systems, and this embodiment does not limit the method for outputting the selection prompt information.
Correspondingly, the candidate product selection instruction may be generated when the user triggers the selection prompt information displayed on the operation interface of the resource recommendation system, or may also be sent to the system by other systems through the data interface, and the embodiment does not limit the manner of obtaining the candidate product selection instruction.
In the technical scheme, when the number of the determined candidate products is more than two, the target product is determined from each candidate product based on the candidate product selection instruction, so that the determined target product can be matched with the actual requirement of the user, and the accuracy of resource recommendation can be improved.
In another example, when there are more than two candidate products, the matching degree of each candidate product with the information corresponding to the requester identifier may be determined, and the candidate product with the highest matching degree with the information corresponding to the requester identifier may be determined as the target product.
In practical implementation, the target product may also be directly specified in the recommendation request, such as: the user specifies the target product when inputting the requester information, and the embodiment does not limit the determination method of the target product.
Optionally, determining a target industry chain corresponding to the target product includes: and determining the target industry chain from the template industry chains based on the product information of the target product.
In this embodiment, the product information means: information describing the nature of the product. Specifically, in the case where the product is a tangible article, the product information includes: information such as shape parameters, composition, generation process, functional parameters, working parameters and/or use scenes of the product; in the case where the product is an intangible service, the product information includes: research and development direction, research and development ability, popularization channel, popularization ability, transportation mode and/or transportation ability and other information, and the content of the product information is not limited in the embodiment.
The template industry chain is pre-constructed. In one example, the template industry chain is extracted from a large number of product transaction records, in other examples, the template industry may also be preset based on industry research and/or experience, and the embodiment does not limit the acquisition manner of the template industry chain.
Further, in an example, the recommendation request includes requester identification information, and determining a target industry chain corresponding to the target product includes: determining a candidate industry chain corresponding to a target product; determining a target industry chain from each candidate industry chain based on the requester identification information when the number of the candidate industry chains is more than two; if there is one candidate industry chain, the candidate industry chain is determined as the target industry chain.
Optionally, determining the target industry chain from at least one industry chain corresponding to the target product based on the requester identification information includes: inquiring transaction information corresponding to the requester based on the requester identification information; and determining a target industry chain from at least one industry chain corresponding to the target product based on the transaction information.
Such as: the target product is a lithium battery, the corresponding industrial chain corresponding to the lithium battery comprises an automobile industrial chain and a mobile phone industrial chain, and if a plurality of mobile phone manufacturers exist in the associated transaction party of the requester according to the identification information of the requester, the mobile phone industrial chain is determined as the target industrial chain.
In the above technical solution, when the number of the industry chains corresponding to the target product is more than two, the target industry chain can be selected from the industry chains corresponding to the target product by combining the requester identification information, so that manual intervention in the target industry chain determination process can be reduced, thereby reducing the operation difficulty of the system, and simultaneously improving the accuracy of the determined target industry chain, thereby improving the accuracy of resource recommendation.
In another example, when there are two or more candidate industry chains, selection prompt information corresponding to each candidate industry chain may be output, and the candidate industry chain indicated by the industry chain selection instruction may be determined as the target industry chain in response to the industry chain selection instruction.
And 102, determining a target position of the target product in the target industry chain.
The target position is represented by links in a target industry chain, and each link in the target industry chain at least comprises one product node.
Optionally, determining a target position of the target product in the target industry chain includes: determining the matching degree of the product information of the target product and the key information corresponding to each link of the target industrial chain; and determining the link with the highest matching degree of the key information and the product information of the target product in all links of the target industrial chain as the target position. Therefore, the target product can be accurately positioned in the target industry chain, and the accuracy of resource recommendation can be improved.
Wherein, the key information is preset. In one example, the key information is determined based on product information corresponding to product nodes contained in the link.
In one example, determining a matching degree of product information of a target product and key information corresponding to each link of a target industry chain includes: and for each link of the target industrial chain, determining the text similarity and/or semantic similarity between the product information of the target product and the key information corresponding to the link as the matching degree.
Wherein the associated product type comprises an upstream product type and/or a downstream product type. The upstream product type refers to a product of a link located before the target location in the target industry chain, and the downstream product type refers to a product of a link located after the target location in the target industry chain.
Such as: the industrial chain sequentially comprises three links of raw material production, raw material processing and product popularization, wherein the target position is a raw material processing link, the upstream product type is a product in the raw material production link, and the downstream product type is a product in the product popularization link.
Optionally, when the target location is located at the start end of the industry chain, the target location on the target industry chain does not include the upstream product type; in the case where the target location is at the end of the industry chain, the target industry chain does not include the downstream product type corresponding to the target location.
In actual implementation, the associated product types may also include other product types, such as: the competitive product type, the embodiment does not limit the related product type.
In one example, determining the associated product type from the target industry chain based on the target location includes: determining products of a link in the target industry chain prior to the target location as upstream product types.
In another example, determining the associated product type from the target industry chain based on the target location includes: determining a product of a link in the target industry chain after the target location as a downstream product type.
In the technical scheme, because the products on the target industry chain are divided into different associated product types based on the target position, the target associated product corresponding to the target product can be conveniently determined from the products corresponding to the associated product types, so that the determination efficiency of the target associated product can be improved, and the determination accuracy of the target associated product can also be improved.
And 104, determining a target associated product corresponding to the target product from the products corresponding to the associated product types.
Optionally, the target associated product includes, corresponding to the associated product type: a target downstream related product and/or a target upstream related product.
In one example, the associated product type includes a downstream product type, and the target associated product includes a target downstream product; determining a target associated product corresponding to the target product from products corresponding to the associated product types, including: and determining the target downstream product from the downstream products based on the matching relationship between the product information of the target product and the supply demand information of the downstream products corresponding to the types of the downstream products.
In this embodiment, the supply demand information refers to: product requirements for the nature of the upstream supply product. Specifically, in the case where the supply demand is a supply demand for an item, the supply information includes: information such as shape parameters, composition, generation process, functional parameters, working parameters and/or use scenes of the required product; in the case where the supply demand is a service supply demand, the supply information includes: information such as a required research and development direction, a required research and development capacity, a required popularization channel, a required popularization capacity, a required transportation mode, and/or a required transportation capacity, and the content of the supply demand information is not limited in this embodiment.
According to the technical scheme, the target downstream product can be determined from the downstream products based on the product information of the target product and the supply demand information of the downstream products, so that the matching degree of the determined target downstream product and the target product can be improved, the accuracy of the determined target downstream product can be improved, and the resource recommendation effect can be improved.
Optionally, determining the target downstream product from the downstream products based on the matching relationship between the product information of the target product and the supply demand information of the downstream products corresponding to the types of the downstream products, includes: for each downstream product corresponding to the downstream product type, determining whether the product information of the target product is matched with the supply demand information of the downstream product; and if so, determining the downstream product as the target downstream product.
Optionally, in order to facilitate matching of the product information with the supply demand information, the product information and the supply demand information are expressed in the same data format, so that the product information and the supply demand information can be conveniently compared, and the matching relationship between the product information and the supply demand information can be conveniently determined.
Further, in the case where there are a plurality of target downstream products, it is possible to base other information such as: determining an optimal target downstream product from a plurality of target downstream products according to a historical search record corresponding to the user account and main information corresponding to the enterprise identification, and then executing step 105; alternatively, step 105 may be directly performed, which is not limited in this embodiment.
In another example, the associated product type includes an upstream product type, and the target associated product includes a target upstream product; determining a target associated product corresponding to the target product from products corresponding to the associated product types, including: and determining the target upstream product from the upstream products based on the matching relation between the product information of the upstream products corresponding to the upstream product types and the supply demand information of the target product.
In this embodiment, the manner of determining the target upstream product is the same as the manner of determining the target downstream product, which is not limited in this embodiment.
Similarly, in the case where there are multiple target upstream products, the information may be based on other information such as: determining an optimal target upstream product from a plurality of target upstream products by using a historical search record corresponding to the user account and main information corresponding to the enterprise identification, and executing a step 105; alternatively, step 105 may be directly performed, which is not limited in this embodiment.
In the technical scheme, the target upstream product can be determined from the upstream product based on the supply demand information of the target product and the product information of the upstream product, so that the matching degree of the determined target upstream product and the target product can be improved, the accuracy of the determined target upstream product can be improved, and the resource recommendation effect can be improved.
In practical implementations, the target product may also include other types of products, such as: the target competitive product, the embodiment, is not limited to the type of the target product.
And 105, generating enterprise recommendation information based on the target associated product.
Optionally, generating the enterprise recommendation information based on the target associated product includes: determining at least one target enterprise based on the matching relation between the target associated product and each enterprise; and generating target recommendation information based on the intelligence information of each target enterprise.
Wherein the intelligence information is collected in advance, and the intelligence information comprises patent intelligence information. Specifically, the patent information may be various patent documents such as patent publications, patent specifications, and patent abstracts, and the research and development level and strength of an enterprise may be obtained by analysis based on the patent information, so that it may be helpful to determine the recommendation order among different enterprises in the recommendation information, and the quality of the target recommendation information may be improved. In actual implementation, the information may further include information such as business information, business risk information, and legal risk information, so as to further improve the quality of the target recommendation information.
Optionally, determining at least one target enterprise based on the matching relationship between the target associated product and each enterprise includes: and determining at least one target enterprise based on the matching relation between the product information of the target associated product and the product type information of each enterprise.
Wherein, the product type information of the enterprise is preset. Specifically, the product type information of the enterprise may be directly obtained based on the business registration information and/or the registration information of the enterprise, or may be determined based on other information of the enterprise, which may include: the information such as the transaction information, the bid and offer information, and/or the product promotion information is not limited in the embodiment.
Optionally, the product type information of the enterprise can be updated in real time, so that the accuracy of the resource recommendation result can be improved.
Optionally, generating the enterprise recommendation information based on the target associated product includes: and generating enterprise recommendation information based on the target associated products for each target associated product corresponding to the target product. Therefore, the target recommendation information corresponding to different target associated products can be conveniently and respectively displayed under the condition that the number of the target associated products is more than two.
In one example, generating target recommendation information based on intelligence information of each target enterprise includes: and for each target associated product corresponding to the target product, generating target recommendation information corresponding to the target associated product based on the information of each target enterprise corresponding to the target associated product.
In actual implementation, the target recommendation information corresponding to the target product may also be generated based on the information of the target enterprises corresponding to all target related products corresponding to the target product, so that the target recommendation result corresponding to the target product may be integrally displayed conveniently, and the generation manner of the target recommendation information is not limited in this embodiment.
The resource recommendation method provided by the embodiment is implemented according to the following principle: responding to the recommendation request, and determining a target industry chain corresponding to the target product; determining a target position of a target product in a target industry chain; determining a correlated product type from the target industry chain based on the target location; determining a target associated product corresponding to the target product from products corresponding to the associated product types; generating enterprise recommendation information based on the target associated product; the method can help solve the problem of poor resource recommendation effect caused by the fact that when enterprise resources are directly matched based on a pre-constructed industrial chain, the requirement matching relationship among enterprises is relatively fixed and corresponding enterprise resources cannot be effectively matched for target enterprises; because the target associated product is determined based on the target product and the position information of the target product in the target industrial chain, and then the enterprise recommendation information is generated based on the target associated product, the product can be used as a gripper, the enterprise resources can be matched for the target enterprise based on the association relationship among the products, the supply and demand relationship among the enterprises does not need to be relied on, so that the corresponding enterprise resources can be effectively matched for the target enterprise, and the resource recommendation effect is improved.
Based on the above technical solution, optionally, referring to fig. 2, after the step 104 determines the target associated product corresponding to the target product from the products corresponding to the associated product types, the method further includes the following steps:
According to the technical scheme, the related products of the target related products can be further determined based on the target related products, so that the product chain corresponding to the target products can be determined by taking the target products as the center, enterprise recommendation information corresponding to the product chain is obtained at the same time, whole industry chain recommendation can be conveniently carried out based on the target products, and therefore the resource recommendation effect can be improved.
Optionally, before step 201 returns the target associated product as the target product to execute step 102 to step 104, the method further includes the following steps:
and step 301, outputting enterprise recommendation information.
The method for outputting the enterprise recommendation information may be to display the enterprise recommendation information on an operation interface of the resource recommendation system, or may also be to send the enterprise recommendation information to other systems through a data interface for output by other systems.
The recommendation information selection instruction may be generated when the user triggers the enterprise recommendation information displayed on the resource recommendation system operation interface, or may also be sent to the system by another system through a data interface, and the method for obtaining the recommendation information selection instruction is not limited in this embodiment.
In one example, the recommendation information selection instruction includes a selected business identifier, and the target associated product can be determined through the business identifier. In actual implementation, the recommendation information selection instruction may also directly include the target related product, and the content of the recommendation information selection instruction is not limited in this embodiment.
In the technical scheme, because the associated product of the target associated product indicated by the recommendation information selection instruction can be further determined, further recommendation can be performed according to the operation of the user, and the accuracy of resource recommendation can be improved.
In actual implementation, whether to execute step 201 may also be determined in other ways, which is not limited in this embodiment.
An embodiment of the present application further provides an electronic device, as shown in fig. 4, the electronic device 400 shown in fig. 4 includes: a processor 401 and a memory 403. Wherein the processor 401 is coupled to the memory 403, such as via a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that the transceiver 404 is not limited to one in practical applications, and the structure of the electronic device 400 is not limited to the embodiment of the present application.
The Processor 401 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application specific integrated Circuit) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 401 may also be a combination of computing functions, e.g., comprising one or more microprocessors in combination, a DSP and a microprocessor in combination, or the like.
The Memory 403 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically erasable programmable Read Only Memory), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.
The memory 403 is used for storing application program codes for executing the scheme of the application, and the execution is controlled by the processor 401. Processor 401 is configured to execute application program code stored in memory 403 to implement the aspects illustrated in the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), etc., and fixed terminals such as digital TVs, desktop computers, etc. But also a server, etc. The electronic device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the use range of the embodiment of the present application.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed in a computer, the computer is caused to execute the resource recommendation method provided in the foregoing embodiment.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless otherwise indicated herein.
The foregoing is only a partial embodiment of the present application, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present application, and these modifications and decorations should also be regarded as the protection scope of the present application.
Claims (10)
1. A resource recommendation method is used in a resource recommendation system, and the method comprises the following steps:
responding to the recommendation request, and determining a target industry chain corresponding to the target product;
determining a target location of the target product in the target industry chain;
determining an associated product type from the target industry chain based on the target location;
determining a target associated product corresponding to the target product from the products corresponding to the associated product types;
and generating enterprise recommendation information based on the target associated product.
2. The method according to claim 1, wherein the associated product type includes a downstream product type, the target associated product includes a target downstream product, and the determining a target associated product corresponding to the target product from products corresponding to the associated product type includes:
and determining the target downstream product from each downstream product based on the matching relationship between the product information of the target product and the supply demand information of each downstream product corresponding to the downstream product type.
3. The method according to claim 1, wherein the associated product type includes an upstream product type, the target associated product includes a target upstream product, and the determining the target associated product corresponding to the target product from the products corresponding to the associated product type includes:
and determining the target upstream product from each upstream product based on the matching relationship between the product information of each upstream product corresponding to the upstream product type and the supply demand information of the target product.
4. The method of claim 1, wherein generating business recommendation information based on the target associated product comprises:
determining at least one target enterprise based on the matching relation between the target associated product and each enterprise;
and generating target recommendation information based on the intelligence information of each target enterprise, wherein the intelligence information comprises patent intelligence information.
5. The method according to claim 1, wherein after determining the target associated product corresponding to the target product from the products corresponding to the associated product types, the method further comprises:
and taking the target associated product as a target product, returning and executing the steps of determining the target position of the target product, determining the type of the associated product based on the target position and determining the target associated product corresponding to the target product from the products corresponding to the type of the associated product.
6. The method of claim 5, wherein before the target associated product is the target product, further comprising:
outputting enterprise recommendation information;
responding to a recommendation information selection instruction, and executing a step of taking the target associated product as a target product for the target associated product indicated by the recommendation information selection instruction.
7. The method of claim 1, wherein the recommendation request includes requester identification information, and before determining the target industry chain corresponding to the target product, the method further comprises:
determining a candidate product based on the requester identifying information;
under the condition that the number of the candidate products is more than two, outputting selection prompt information corresponding to each candidate product;
in response to a candidate product selection instruction, determining a candidate product indicated by the candidate product selection instruction as the target product.
8. The method of claim 1, wherein the recommendation request includes requester identification information, and wherein the determining the target industry chain corresponding to the target product comprises:
determining a candidate industry chain corresponding to the target product;
when the number of the candidate industry chains is two or more, the target industry chain is determined from each of the candidate industry chains based on the requester identification information.
9. An electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, the at least one application configured to: performing the resource recommendation method of any of claims 1 to 8.
10. A computer-readable storage medium on which a computer program is stored, which, when the computer program is executed in a computer, causes the computer to execute the resource recommendation method according to any one of claims 1 to 8.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211546469.6A CN115809900A (en) | 2022-12-05 | 2022-12-05 | Resource recommendation method, electronic device and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211546469.6A CN115809900A (en) | 2022-12-05 | 2022-12-05 | Resource recommendation method, electronic device and storage medium |
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| CN202211546469.6A Withdrawn CN115809900A (en) | 2022-12-05 | 2022-12-05 | Resource recommendation method, electronic device and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117435817A (en) * | 2023-12-20 | 2024-01-23 | 泰安北航科技园信息科技有限公司 | BI intelligent center system based on industry big data |
| CN117611191A (en) * | 2023-11-27 | 2024-02-27 | 哈尔滨工程大学三亚南海创新发展基地 | Method, system, computer equipment and storage medium for generating industrial chain |
-
2022
- 2022-12-05 CN CN202211546469.6A patent/CN115809900A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117611191A (en) * | 2023-11-27 | 2024-02-27 | 哈尔滨工程大学三亚南海创新发展基地 | Method, system, computer equipment and storage medium for generating industrial chain |
| CN117435817A (en) * | 2023-12-20 | 2024-01-23 | 泰安北航科技园信息科技有限公司 | BI intelligent center system based on industry big data |
| CN117435817B (en) * | 2023-12-20 | 2024-03-15 | 泰安北航科技园信息科技有限公司 | BI intelligent center system based on industry big data |
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