CN117575655A - Product information transmission method, device, equipment and storage medium - Google Patents

Product information transmission method, device, equipment and storage medium Download PDF

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CN117575655A
CN117575655A CN202311595273.0A CN202311595273A CN117575655A CN 117575655 A CN117575655 A CN 117575655A CN 202311595273 A CN202311595273 A CN 202311595273A CN 117575655 A CN117575655 A CN 117575655A
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product
user
clients
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client
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白源
李泽鹏
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Agricultural Bank of China
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

The invention discloses a method, a device, equipment and a storage medium for transmitting product information, which comprise the following steps: obtaining product records to be analyzed of at least two clients, wherein the at least two clients comprise a target client and at least one client to be selected; determining the user similarity between the clients according to at least two product records to be analyzed; and transmitting product information to the target client and the client to be selected corresponding to the target client according to the user similarity among the clients. According to the technical scheme, the accuracy of product information transmission is improved, the personalized product requirements of the user are met, the user time is saved, and the use experience of the user is optimized.

Description

Product information transmission method, device, equipment and storage medium
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method, an apparatus, a device, and a storage medium for transmitting product information.
Background
With the explosive growth of global information, it has become increasingly important how to obtain effective information from a large amount of information. Commercial banks are constantly dedicated to providing high-quality services for a large number of clients, and when the clients invest, the clients can have poor investment experience due to the difficulty in selecting the banking investment products due to the various investment products, and meanwhile, the commercial banks consume a large amount of manpower, material resources and financial resources.
The product information transmission method adopted by commercial banks at present is single, product information of certain products is transmitted to all clients indiscriminately, personalized product information transmission is lacked, the transmission accuracy of the product information transmission is low, personalized requirements of clients cannot be met, and further poor experience of the clients is caused.
Disclosure of Invention
The invention provides a product pushing method, a device, equipment and a storage medium, which improve the accuracy of product information transmission, meet the personalized product requirements of users, save the time of the users and optimize the use experience of the users.
In a first aspect, an embodiment of the present disclosure provides a method for transmitting product information, including:
obtaining product records to be analyzed of at least two clients, wherein the at least two clients comprise a target client and at least one client to be selected;
determining the user similarity between the clients according to at least two product records to be analyzed;
and transmitting product information to the target client and the client to be selected corresponding to the target client according to the user similarity among the clients.
In a second aspect, an embodiment of the present disclosure provides a product information transmission apparatus, including:
the system comprises a product record acquisition module, a storage module and a storage module, wherein the product record acquisition module is used for acquiring product records to be analyzed of at least two clients, and the at least two clients comprise a target client and at least one client to be selected;
the similarity determining module is used for determining the user similarity between the clients according to at least two product records to be analyzed;
and the product information transmission module is used for transmitting product information to the target client and the to-be-selected client corresponding to the target client according to the user similarity among the clients.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the product information transmission method provided by the embodiment of the first aspect described above.
In a fourth aspect, embodiments of the present disclosure provide a computer readable storage medium storing computer instructions for causing a processor to execute the product information transmission method provided in the first aspect.
The method, the device, the equipment and the storage medium for transmitting the product information are characterized in that the product records to be analyzed of at least two clients are obtained, and the at least two clients comprise a target client and at least one client to be selected; determining the user similarity between the clients according to at least two product records to be analyzed; and transmitting product information to the target client and the client to be selected corresponding to the target client according to the user similarity among the clients. According to the technical scheme, the accuracy of product information transmission is improved, the personalized product requirements of the user are met, the user time is saved, and the use experience of the user is optimized.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for transmitting product information according to a first embodiment of the present invention;
fig. 2 is a flowchart of a method for transmitting product information according to a second embodiment of the present invention;
fig. 3 is a two-part diagram of a user product involved in a product information transmission method according to a second embodiment of the present invention;
fig. 4 is a consistency difference chart related to a product information transmission method according to a second embodiment of the present invention;
fig. 5 is a user relationship diagram involved in a product information transmission method according to a second embodiment of the present invention;
fig. 6 is a schematic structural diagram of a product information transmission device according to a third embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and "object" in the description of the present invention and the claims and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a product information transmission method according to an embodiment of the present invention, where the method may be applied to a situation where personalized product pushing is performed by a product information transmission device, and the product information transmission device may be implemented in a form of hardware and/or software.
As shown in fig. 1, the method includes:
s101, obtaining product records to be analyzed of at least two clients, wherein the at least two clients comprise a target client and at least one client to be selected.
In this embodiment, the client may be understood as a handheld terminal of the user. The product record to be analyzed may be understood as a product that the user has purchased, such as a financial product or an investment product, and includes product information to be analyzed and product scores to be analyzed. The information of the product to be analyzed can be understood as information such as the name, the type and the number of the product to be analyzed. The product score to be analyzed may be understood as a satisfaction score given by the user of the client after purchasing the product. The method and the device can be used for acquiring, storing, using and processing the data such as the product record to be analyzed in the technical scheme of the application, and all meet the requirements of related laws and regulations. The target client may be understood as a client for implementing the precision push. The candidate client may be understood as other clients using the software.
Specifically, the client selects related products through related software such as a mobile phone bank, namely related product selection records exist, the related product selection records are recorded as product records to be analyzed, and each client purchasing the related products is provided with the corresponding product records to be analyzed. And obtaining product information to be analyzed and product scores to be analyzed of a plurality of clients through a compliance technical means.
S102, determining the user similarity between the clients according to at least two product records to be analyzed.
In this embodiment, the user similarity may be understood as the similarity degree of the user corresponding to each client to the product requirement and preference.
Specifically, a corresponding user product bipartite graph is constructed according to at least two product records to be analyzed and corresponding clients thereof, product scoring consistency processing analysis is carried out on the user product bipartite graph, single-mode projection is carried out on user nodes based on consistency results so as to determine interaction among users corresponding to the clients, namely user similarity among the clients.
S103, according to the user similarity among the clients, product information is transmitted to the target client and the to-be-selected client corresponding to the target client.
In this embodiment, the product information may be understood as related information of the product, such as a product number, an investment type, aging information, or related article introduction, etc.
Specifically, according to the user similarity among the clients, a plurality of clients with similar product requirements and preferences can be determined, the originally determined product information which needs to be pushed towards the target client is pushed to the target client and simultaneously is also pushed to the to-be-selected client with similar product requirements and preferences of the target client, and the product information is transmitted to the clients through corresponding software.
According to the product information transmission method provided by the embodiment of the invention, the product records to be analyzed of at least two clients are obtained, and the at least two clients comprise a target client and at least one client to be selected; determining the user similarity between the clients according to at least two product records to be analyzed; and transmitting product information to the target client and the to-be-selected client corresponding to the target client according to the user similarity among the clients. According to the technical scheme, the accuracy of product information transmission is improved, the personalized product requirements of the user are met, the user time is saved, and the use experience of the user is optimized.
Example two
Fig. 2 is a flowchart of a product information transmission method according to a second embodiment of the present invention, where any of the foregoing embodiments is further optimized, and the method may be applicable to a situation where personalized product pushing is performed by a product information transmission device, and the product information transmission device may be implemented in a form of hardware and/or software.
As shown in fig. 2, the method includes:
s201, obtaining product records to be analyzed of at least two clients, wherein the at least two clients comprise a target client and at least one client to be selected.
S202, constructing a user product bipartite graph according to at least two clients and product records to be analyzed of the at least two clients.
In this embodiment, the two-part graph of the user product includes two vertex sets, and two vertices of each edge in the graph are respectively located in the two vertex sets, and no edge in each vertex set is connected. In the two-part graph of the user product, one vertex set is the vertex set of the user node, one vertex set is the vertex set of the product node, and two vertex sets are adopted
Specifically, the client is used as a user node, corresponding product nodes and connection relations between the product nodes and the user nodes are determined according to the product records to be analyzed of at least two clients, and a user product bipartite graph representing the relation between a user and a product is constructed.
Optionally, fig. 3 is a two-part diagram of a user product related to a product information transmission method according to a second embodiment of the present invention, as shown in fig. 3, the two-part diagram of the user product is constructed according to at least two clients and to-be-analyzed product records of the at least two clients, including:
s2021, constructing the user node according to at least two clients.
In this embodiment, a user node may be understood as a node representing a user to which a client corresponds.
Specifically, each client is used as a user node, and the user product bipartite graph comprises a plurality of user nodes. In fig. 3, each y characterizes a client as a user node, which does not intersect.
S2022, constructing a product node according to the product information to be analyzed of at least two clients.
In this embodiment, the product information to be analyzed is content in a record of the product to be analyzed, including information such as a name and a number of the product to be analyzed, and is used to characterize the product to be analyzed itself. The product node may be understood as a product purchased by a client corresponding to the user node.
Specifically, according to each piece of product information to be analyzed, the corresponding product to be analyzed is used as a product node, and the user product bipartite graph comprises a plurality of product nodes. In fig. 3, each x characterizes the purchased products of several clients as one product node, which does not intersect. It will be appreciated that since there may be a plurality of corresponding products to be analyzed at one client, the number of product nodes and the number of user nodes may not be identical, the number of product nodes being greater than or equal to the number of user nodes.
S2023, connecting the user node and the product node corresponding to the user node.
In this embodiment, according to the correspondence between the user node and the product node, that is, which product has been purchased by the client corresponding to the user node, the product node of the product is connected to the corresponding user node, and each user node is connected to at least one product node.
Illustratively, the client corresponding to the user node y1 purchased the products to be analyzed corresponding to the two product nodes x1 and x4, and thus, the user node y1 is connected to the product nodes x1 and x4, respectively.
S2024, assigning a value for the connection relation between the user node and the product node according to the product scores to be analyzed of at least two clients.
In this embodiment, the product score to be analyzed may be understood as the content in the record of the product to be analyzed, and represents the evaluation of the purchased product by the user on the client, which is used to represent the favorites or satisfaction degree of the user on the product.
Specifically, each client is assigned with a score of a product to be analyzed of the product and a connection relation between a corresponding user node of the client and a corresponding product node.
Illustratively, the user node y1 scores 0.7 for the product to be analyzed of the product node x1, 0.4 for the product to be analyzed of the product node x4, 0.7 is assigned to the connection relationship between y1 and x1, and 0.4 is assigned to the connection relationship between y1 and x 4.
S203, determining the user consistency between every two clients according to the user product bipartite graph.
In this embodiment, the user consistency may be understood as the degree of similarity of the requirements or favorites of two clients for a certain product class.
Specifically, scoring consistency calculation is performed according to user nodes corresponding to any two clients in the two-part graph of the product user, product nodes connected with the two user nodes, and connection relations between the two user nodes and the corresponding product nodes, so as to obtain a consistency value between the two user nodes, namely, obtain user consistency between the two clients.
Optionally, fig. 4 is a consistency difference diagram related to a product information transmission method according to a second embodiment of the present invention, as shown in fig. 4, determining, according to a user product bipartite diagram, user consistency between every two clients, including:
s2031, determining the user consistency between every two clients according to the connection attribute values between every two user nodes and the corresponding number of product nodes in the user product bipartite graph and the connection quantity value of each user node connected with the product nodes.
In this embodiment, the connection attribute value may be understood as a value of the product to be analyzed, i.e. a satisfaction degree score value of the product, where the connection attribute value is a value assigned to the connection relationship between the user node and the product node in step S2024. The connection quantity value can be understood as the number of product nodes connected by the user node, i.e. the number of products purchased by the client corresponding to the user node.
Specifically, each user node has a corresponding number of product nodes, and according to the two user nodes, the connection attribute value between the two product nodes corresponding to the two user nodes, and the connection quantity value of the product node connected to each user node, the consistency value between the two user nodes is calculated through a given formula, and the user consistency between the corresponding clients of the two user nodes is determined.
Exemplary, as shown in FIG. 4, u and v respectively represent two user nodes, p1, p2 and p3 are products purchased by the clients corresponding to the u node and the v node, the connection attribute value of the client corresponding to the u node to the p1 product is 0.6, the connection attribute value of the client corresponding to the v node to the p1 product is 0.7, and the user consistency Con of the clients u and v to the p1 product p1 (u, v) is 0.9, i.e., (1- |0.6-0.7|); the connection attribute value of the client corresponding to the u node to the p2 product is 0.4, the connection attribute value of the client corresponding to the v node to the p2 product is 0.3, and the user consistency Con of the client u and the client v to the p2 product p2 (u, v) is 0.9, i.e., (1- |0.4-0.3|); the connection attribute value of the client corresponding to the u node to the p3 product is 0.8, the connection attribute value of the client corresponding to the v node to the p3 product is 0.2, and the user consistency Con of the client u and the client v to the p3 product p3 (u, v) is 0.4, i.e., (1- |0.8-0.2|); according toAnd determining the consistency Con (u, v) between the user node u and the user node b, wherein deg (u) is the number of product nodes connected with the u node, and deg (v) is the number of product nodes connected with the v node, and is 3. It can be seen that user consistency between u node and v node +.>
S204, determining the user similarity between every two clients according to the user consistency between every two clients.
In this embodiment, a single-mode projection is performed on a user node-oriented graph of a user product by using user consistency between every two clients to obtain a relationship graph between the clients, then user similarity between the clients is determined by using a cosine similarity algorithm of collaborative filtering, and the interaction between the clients is determined according to the relationship graph amplitude of the user similarity as the clients.
Optionally, fig. 5 is a diagram of a user relationship involved in a product information transmission method according to a second embodiment of the present invention, as shown in fig. 5, determining a user similarity between each two clients according to a user consistency between each two clients, including:
s2041, according to the user consistency between every two clients, performing single-mode projection on the user product bipartite graph to each user node, and obtaining the association relation between the user nodes.
In this embodiment, the association relationship between the user nodes is that after the single-mode projection of the two-part graph of the user product, the user nodes can be connected into the same relationship graph. For example, three user nodes are all connected to the same product node, and these three user nodes may be connected to the same relationship graph.
Specifically, in the user product bipartite graph, the user relationship graph facing the user nodes as shown in fig. 5 is obtained by compressing two node sets (the nodes of the user nodes and the node set of the product nodes) of the bipartite graph to only one node set (the node set of the user nodes). Wherein two nodes in one set have at least one common neighbor node in the other set.
Illustratively, after a single-mode projection is performed on the user product bipartite graph for the user node, several user relationship graphs, such as a user relationship graph between y1, y2 and y4, and a user relationship graph between y3, y5 and y6, are obtained.
S2042, carrying out collaborative filtering according to the association relation among the user nodes, and determining the similarity between every two clients.
In this embodiment, cosine values between vector angles of every two user nodes in the user relationship graph are cooperatively filtered by a cosine similarity algorithm, so as to obtain a similarity value between the two user nodes. Wherein collaborative filtering is to recommend information of interest to a user using preferences of a community of interest to a person who has a common experience. After the similarity value between the two user nodes is calculated, the connection relation of the two user nodes in the user relation graph is assigned to be the weight of the corresponding connection relation.
S205, according to the similarity between the clients, determining the to-be-selected clients, of which the similarity with the target client meets the preset association pushing condition, through a preset classification algorithm.
In this embodiment, the preset classification algorithm may be understood as a preset algorithm for determining a candidate client similar to the target client, for example, may be a K-nearest neighbor algorithm, or may be another algorithm, which is not limited in this embodiment. The preset association pushing condition may be understood as a preset condition for determining a to-be-selected client associated with the target client from a large number of to-be-selected clients, for example, a condition that a similarity value reaches a preset threshold value, which indicates that product selection preferences of the to-be-selected client and the target client are relatively similar.
Specifically, according to the similarity between the clients, that is, the weight of the connection relationship between the user nodes in the user relationship graph, calculating K clients most similar to the target client through a similarity algorithm, and determining the candidate clients whose values (for example, the weight of the connection relationship between the user nodes) corresponding to the similarity between the target clients meet the preset similarity threshold. The determined clients to be selected are the clients to be selected which are the closest to the product requirements and the preference of the target client. It will be appreciated that the similarity threshold is determined according to actual requirements, and this embodiment is not limited thereto.
S206, the product information of the predetermined target-oriented client is transmitted to the target client in an associated mode, and the client to be selected meets the preset associated pushing condition.
In this embodiment, after determining a to-be-selected client similar to the product requirement and preference of the target client, the product information originally determined to be pushed towards the target client is pushed to the target client and also to the to-be-selected client similar to the product requirement and preference of the target client, and the product information is transmitted to each client through corresponding software.
In this embodiment, by acquiring product records to be analyzed of at least two clients, the at least two clients include a target client and at least one client to be selected; constructing a user product bipartite graph according to at least two clients and the product records to be analyzed of the at least two clients; determining the user consistency between every two clients according to the two-part diagram of the user product; determining the user similarity between every two clients according to the user consistency between every two clients; according to the similarity between the clients, determining a to-be-selected client, the similarity between the to-be-selected client and the target client of which meets the preset association pushing condition, through a preset classification algorithm; and transmitting the predetermined product information facing the target client to the target client in a correlated manner, and enabling the target client to meet the preset correlated pushing condition. Compared with the original similarity calculation method, the method for calculating the projection of the two-part graph of the user product can more accurately find the clients similar to the target clients, so that the accuracy of recommendation is increased; the consideration factors of the consistency are added into the similarity algorithm, so that the consistency calculation accuracy among users is greatly improved; for different target clients, favorite products can be pushed to the target clients instead of directly pushing hot spot products, so that personalized requirements of the clients are met, and the experience of the clients is improved. According to the technical scheme, the accuracy of product information transmission is improved, the personalized product requirements of the user are met, the user time is saved, and the use experience of the user is optimized.
Example III
Fig. 6 is a schematic structural diagram of a product information transmission device according to a third embodiment of the present invention. As shown in fig. 6, the apparatus includes:
a product record obtaining module 31, configured to obtain product records to be analyzed of at least two clients, where the at least two clients include a target client and at least one client to be selected;
a similarity determining module 32, configured to determine a user similarity between the clients according to at least two product records to be analyzed;
and the product information transmission module 33 is configured to transmit product information to the target client and the candidate client corresponding to the target client according to the user similarity between the clients.
According to the product information transmission device adopted by the technical scheme, the accuracy of product information transmission is improved, the personalized product requirements of users are met, the user time is saved, and the use experience of the users is optimized.
Optionally, the product record to be analyzed includes product information to be analyzed and product scores to be analyzed.
Optionally, the similarity determining module 32 includes:
the bipartite graph construction unit is used for constructing a user product bipartite graph according to at least two clients and the product records to be analyzed of the at least two clients;
the consistency determining unit is used for determining the user consistency between every two clients according to the user product bipartite graph;
and the similarity determining unit is used for determining the user similarity between every two clients according to the user consistency between every two clients.
Optionally, the bipartite graph construction unit is specifically configured to:
constructing a user node according to at least two clients;
constructing a product node according to the product information to be analyzed of at least two clients;
connecting the user node and a product node corresponding to the user node;
and assigning a value for the connection relation between the user node and the product node according to the product scores to be analyzed of at least two clients.
Optionally, the consistency determining unit is specifically configured to:
and determining the user consistency between every two clients according to the connection attribute values between every two user nodes and the corresponding number of product nodes in the user product bipartite graph and the connection quantity value of each user node connected with the product nodes.
Optionally, the consistency determining unit is specifically configured to:
according to the user consistency between every two clients, carrying out single-mode projection on the two graphs of the user product to each user node to obtain the association relation between the user nodes;
and collaborative filtering is carried out according to the association relation between the user nodes, and the similarity between every two clients is determined.
Optionally, the product information transmission module 33 is specifically configured to:
according to the similarity between the clients, determining the to-be-selected clients, of which the similarity with the target client meets the preset association pushing condition, through a preset classification algorithm;
and transmitting the predetermined product information facing the target client to the target client in a correlated manner, and transmitting the product information to the client to be selected meeting the preset correlated pushing condition.
The product information transmission device provided by the embodiment of the invention can execute the product information transmission method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 7 shows a schematic diagram of an electronic device 40 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 7, the electronic device 40 includes at least one processor 41, and a memory communicatively connected to the at least one processor 41, such as a Read Only Memory (ROM) 42, a Random Access Memory (RAM) 43, etc., in which the memory stores a computer program executable by the at least one processor, and the processor 41 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 42 or the computer program loaded from the storage unit 48 into the Random Access Memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 may also be stored. The processor 41, the ROM 42 and the RAM 43 are connected to each other via a bus 44. An input/output (I/O) interface 45 is also connected to bus 44.
Various components in electronic device 40 are connected to I/O interface 45, including: an input unit 46 such as a keyboard, a mouse, etc.; an output unit 47 such as various types of displays, speakers, and the like; a storage unit 48 such as a magnetic disk, an optical disk, or the like; and a communication unit 49 such as a network card, modem, wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 41 may be various general and/or special purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 41 performs the respective methods and processes described above, such as the product information transmission method.
In some embodiments, the product information transmission method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 48. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 40 via the ROM 42 and/or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the product information transmission method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the product information transmission method in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. A product information transmission method, characterized by comprising:
obtaining product records to be analyzed of at least two clients, wherein the at least two clients comprise a target client and at least one client to be selected;
determining the user similarity between the clients according to at least two product records to be analyzed;
and transmitting product information to the target client and the client to be selected corresponding to the target client according to the user similarity among the clients.
2. The method of claim 1, wherein the product record to be analyzed comprises product information to be analyzed and product scores to be analyzed.
3. The method of claim 2, wherein said determining user similarity between each of said clients based on at least two of said product records to be analyzed comprises:
constructing a user product bipartite graph according to at least two clients and the product records to be analyzed of the at least two clients;
determining the user consistency between every two clients according to the user product bipartite graph;
and determining the similarity of the users between every two clients according to the consistency of the users between every two clients.
4. A method according to claim 3, wherein said constructing a user product bipartite graph from at least two clients and to-be-analyzed product records of at least two clients comprises:
constructing a user node according to at least two clients;
constructing a product node according to the product information to be analyzed of at least two clients;
connecting the user node and a product node corresponding to the user node;
and assigning a value for the connection relation between the user node and the product node according to the product scores to be analyzed of at least two clients.
5. A method according to claim 3, wherein said determining user consistency between each two clients from said user product bipartite graph comprises:
and determining the user consistency between every two clients according to the connection attribute values between every two user nodes and the corresponding number of product nodes in the user product bipartite graph and the connection quantity value of each user node connected with the product nodes.
6. A method according to claim 3, wherein said determining the user similarity between each two clients based on the user consistency between each two clients comprises:
according to the user consistency between every two clients, carrying out single-mode projection on the two graphs of the user product to each user node to obtain the association relation between the user nodes;
and collaborative filtering is carried out according to the association relation between the user nodes, and the similarity between every two clients is determined.
7. The method according to claim 1, wherein said transmitting product information to the target client and the candidate clients corresponding to the target client according to the user similarity between the clients includes:
according to the similarity between the clients, determining the to-be-selected clients, of which the similarity with the target client meets the preset association pushing condition, through a preset classification algorithm;
and transmitting the predetermined product information facing the target client to the target client in a correlated manner, and transmitting the product information to the client to be selected meeting the preset correlated pushing condition.
8. A product information transmission apparatus, characterized by comprising:
the system comprises a product record acquisition module, a storage module and a storage module, wherein the product record acquisition module is used for acquiring product records to be analyzed of at least two clients, and the at least two clients comprise a target client and at least one client to be selected;
the similarity determining module is used for determining the user similarity between the clients according to at least two product records to be analyzed;
and the product information transmission module is used for transmitting product information to the target client and the to-be-selected client corresponding to the target client according to the user similarity among the clients.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform a product information transmission method according to any one of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a processor to perform a product information transmission method according to any one of claims 1-7.
CN202311595273.0A 2023-11-27 2023-11-27 Product information transmission method, device, equipment and storage medium Pending CN117575655A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311595273.0A CN117575655A (en) 2023-11-27 2023-11-27 Product information transmission method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311595273.0A CN117575655A (en) 2023-11-27 2023-11-27 Product information transmission method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN117575655A true CN117575655A (en) 2024-02-20

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Application Number Title Priority Date Filing Date
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Country Status (1)

Country Link
CN (1) CN117575655A (en)

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