CN111192112A - Multi-platform interaction method and device - Google Patents
Multi-platform interaction method and device Download PDFInfo
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- CN111192112A CN111192112A CN201911389461.1A CN201911389461A CN111192112A CN 111192112 A CN111192112 A CN 111192112A CN 201911389461 A CN201911389461 A CN 201911389461A CN 111192112 A CN111192112 A CN 111192112A
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Abstract
The invention provides a multi-platform interaction method and a multi-platform interaction device, which relate to the technical field of data processing, and are characterized in that first member information of a first shop is obtained, wherein the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; and determining the first recommended commodity and the first recommendation frequency of the first shop according to the first preference information and the first preference rate, so that the technical effects of multi-platform interaction, omnibearing optimization of preference information of users and improvement of accuracy and purchase rate of recommended commodities are achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a multi-platform interaction method and device.
Background
The e-commerce platform is a platform for providing online transaction negotiation for enterprises or individuals. The enterprise electronic commerce platform is a management environment which establishes a virtual network space for carrying out business activities on the Internet and ensures the smooth operation of business; the system is an important place for coordinating and integrating information flow, material flow and fund flow in order, relevance and high-efficiency flow. Enterprises and merchants can make full use of shared resources such as network infrastructure, payment platform, security platform, management platform and the like provided by the electronic commerce platform to effectively develop own commercial activities at low cost. At present, the electronic commerce platform and other application platforms are operated interactively, so that a multi-platform win-win situation can be achieved, users are expanded for the electronic commerce platform, and benefits are increased for the other application platforms.
However, the applicant of the present invention finds that the prior art has at least the following technical problems:
the shops of the existing e-commerce platform recommend commodities to users according to shopping preferences of the users, so that the collected user information is one-sided, the preferences of the users cannot be completely mastered, the accuracy rate of recommending the commodities is low, and the commodity conversion rate is reduced.
Disclosure of Invention
The embodiment of the invention provides a multi-platform interaction method and device, solves the technical problems that in the prior art, commodities are recommended to a user by shops of an e-commerce platform according to shopping preferences of the user, so that the collected user information is one-sided, the preferences of the user cannot be completely mastered, the commodity recommending accuracy is low, and the commodity conversion rate is reduced, achieves multi-platform interaction, comprehensively optimizes the preference information of the user, improves the commodity recommending accuracy and purchasing rate, and improves the experience of the user.
In view of the foregoing, embodiments of the present application are provided to provide a multi-platform interaction method and apparatus.
In a first aspect, the present invention provides a multi-platform interaction method, where the method includes: obtaining first member information of a first store, wherein the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information of the first member; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; and determining a first recommended commodity and a first recommended frequency of the first shop according to the first preference information and the first preference rate.
Preferably, the method comprises:
obtaining second commodity information of a second shop purchased by the first member, wherein the second shop is from a first online platform; obtaining a first purchasing activity of the first member for purchasing the second commodity; judging whether the first purchasing activity exceeds a first preset threshold value or not; when the first purchasing activity exceeds a first preset threshold value, determining a first commodity category of the first commodity and a second commodity category of the second commodity; judging whether the first commodity category and the second commodity category have a first relevance; determining a second recommendation frequency with which the first store recommends the first item to the first member when the first item category has a first association with the second item category.
Preferably, the method comprises:
obtaining first evaluation information of the first member; obtaining third commodity information according to the first evaluation information, wherein the third commodity is a commodity sold by the second shop; determining second preference information according to the third commodity information and the first identity information; determining a second preference rate of the first member to the first shop according to the second preference information; and determining a second recommended commodity and a second recommended frequency of the first shop according to the second preference information and the second preference rate.
Preferably, the method comprises:
obtaining first browsing commodity information of the first member; determining first potential purchase demand information of the first member according to the first browsed commodity information; determining whether the first potential purchase demand information has a second association with the first store; when the first potential purchase demand information has a second relevance with the first shop, determining a third recommended commodity and a third recommendation frequency of the first shop according to the first potential purchase demand information.
Preferably, the method comprises:
obtaining a fourth commodity purchased by the first member, wherein the fourth commodity is a commodity sold by the second store; judging whether the fourth commodity has third relevance with the first identity information; determining third preference information of the first member according to the fourth commodity when the fourth commodity has a third association with the first identity information; determining a third preference rate of the first member to the first shop according to the third preference information; judging whether the third preference rate is higher than the first preference rate; and when the third preference rate is higher than the first preference rate, determining a fourth recommended commodity and a fourth recommended frequency of the first shop according to the third preference information and the third preference rate.
In a second aspect, the present invention provides a multi-platform interactive apparatus, comprising:
the system comprises a first obtaining unit, a second obtaining unit and a third obtaining unit, wherein the first obtaining unit is used for obtaining first member information of a first store, the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member;
a second obtaining unit configured to obtain first commodity information of the first store purchased by the first member;
the first operation unit is used for logging in a second online platform according to the telephone information or the mailbox information of the first member;
a third obtaining unit configured to obtain first identity information of the first member according to the second online platform;
a fourth obtaining unit, configured to obtain first preference information of the first member according to the first identity information and the first commodity information;
a first determining unit, configured to determine a first preference rate of the first member for the first store according to the first preference information;
a second determining unit configured to determine a first recommended item and a first recommended frequency of the first store according to the first preference information and the first preference rate.
Preferably, the apparatus comprises:
a fifth obtaining unit, configured to obtain second commodity information of a second store purchased by the first member, where the second store is from a first online platform;
a sixth obtaining unit, configured to obtain a first purchasing activity of the first member to purchase the second commodity;
a first judging unit, configured to judge whether the first purchasing activity exceeds a first preset threshold;
a third determination unit configured to determine a first item category of the first item and a second item category of the second item when the first purchase activity exceeds a first preset threshold;
a second determination unit configured to determine whether the first item category and the second item category have a first correlation;
a fourth determination unit configured to determine a second recommendation frequency with which the first shop recommends the first item to the first member when the first item category and the second item category have a first association.
Preferably, the apparatus comprises:
a seventh obtaining unit configured to obtain first evaluation information of the first member;
an eighth obtaining unit configured to obtain third item information according to the first evaluation information, wherein the third item is an item sold by the second store;
a fifth determining unit configured to determine second preference information based on the third commodity information and the first identity information;
a sixth determining unit, configured to determine a second liking rate of the first member to the first store according to the second liking information;
a seventh determining unit configured to determine a second recommended item and a second recommended frequency of the first store according to the second taste information and the second taste rate.
Preferably, the apparatus comprises:
a ninth obtaining unit configured to obtain first viewed commodity information of the first member;
an eighth determining unit configured to determine first potential purchase demand information of the first member based on the first viewed commodity information;
a third determination unit configured to determine whether the first potential purchase demand information has a second association with the first store;
a ninth determining unit configured to determine a third recommended item and a third recommended frequency of the first store according to the first potential purchase demand information when the first potential purchase demand information has a second association with the first store.
Preferably, the apparatus comprises:
a tenth obtaining unit configured to obtain a fourth commodity purchased by the first member, wherein the fourth commodity is a commodity sold by the second store;
a fourth judging unit, configured to judge whether the fourth commodity has a third association with the first identity information;
a tenth determining unit configured to determine third preference information of the first member based on the fourth article when the fourth article has a third association with the first identification information;
an eleventh determining unit, configured to determine a third preference rate of the first member for the first store according to the third preference information;
a fifth judging unit, configured to judge whether the third preference rate is higher than the first preference rate;
a twelfth determining unit, configured to determine a fourth recommended item and a fourth recommended frequency of the first store according to the third preference information and the third preference ratio when the third preference ratio is higher than the first preference ratio.
In a third aspect, the present invention provides a multi-platform interactive device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the above methods when executing the program.
In a fourth aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods described above.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
according to the multi-platform interaction method and device provided by the embodiment of the invention, first member information of a first shop is obtained, wherein the first shop is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information of the first member; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; the first recommended commodity and the first recommendation frequency of the first shop are determined according to the first preference information and the first preference rate, so that the technical problems that in the prior art, commodities are recommended to users by shops of an e-commerce platform according to shopping preferences of the users, collected user information is one-sided, the preferences of the users cannot be completely mastered, the accuracy of recommended commodities is low, and the commodity conversion rate is reduced are solved, multi-platform interaction is achieved, preference information of the users is comprehensively optimized, the accuracy and the purchase rate of the recommended commodities are improved, and the technical effect of user experience is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
FIG. 1 is a flowchart illustrating a multi-platform interaction method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an interactive apparatus with multiple platforms according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another multi-platform interactive device according to an embodiment of the present invention.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first operating unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a first determining unit 16, a second determining unit 17, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the invention provides a multi-platform interaction method and device, and aims to solve the technical problems that in the prior art, commodities are recommended to a user by shops of an e-commerce platform according to shopping preferences of the user, so that collected user information is one-sidedness, the preferences of the user cannot be completely mastered, the accuracy of recommended commodities is low, and the commodity conversion rate is reduced.
The technical scheme provided by the invention has the following general idea: obtaining first member information of a first store, wherein the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information of the first member; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; and determining a first recommended commodity and a first recommendation frequency of the first shop according to the first preference information and the first preference rate, so that multi-platform interaction is achieved, preference information of a user is optimized in an all-round manner, accuracy and purchase rate of recommended commodities are improved, and experience of the user is improved.
The technical solutions of the present invention are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present invention are described in detail in the technical solutions of the present application, and are not limited to the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Example one
Fig. 1 is a flowchart illustrating a multi-platform interaction method according to an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides a multi-platform interaction method, where the method includes:
step 110: the method comprises the steps of obtaining first member information of a first store, wherein the first store comes from a first online platform, and the first member information comprises telephone information or mailbox information of a first member.
Step 120: first commodity information of the first shop purchased by the first member is obtained.
Specifically, the first store is a business that is operating on a first online platform. The first member information is personal data information registered by the first member in the first shop, and includes name, gender, birthday, telephone number, mailbox information, purchase order information, point information and the like of the first member. The embodiment of the application can also adopt an encryption mode to encrypt all member information of the first online platform, so as to prevent the member information from being leaked or stolen by a third party. And implementing interactive cooperation through the first online platform and the second online platform, wherein the login mode of the second online platform is to verify login by adopting a telephone number or mailbox information, so as to obtain member data information of the first shop of the first online platform, namely the first member information, and extracting the telephone number or mailbox information of the first member from the first member information. The method comprises the steps of obtaining all commodity information purchased by a first member in a first shop through historical order information of the first member, and determining first commodity information according to the commodity information purchased by the first member, wherein the first commodity information is a commodity which is purchased by the first member in the first shop for the most times, and the first commodity information comprises information such as commodity attribute, price, picture, material and the like of the first commodity.
Step 130: and logging in a second online platform according to the telephone information or the mailbox information of the first member.
Step 140: first identity information of the first member is obtained according to the second online platform.
Specifically, according to first member information of a first shop obtained from a first online platform and further phone information or mailbox information of a first member extracted from the first member information, a second online platform is logged in according to the phone information or mailbox information of the first member to enter account information of the first member. The first identity information of the first member can be obtained according to the condition that the first member uses the second online platform, for example, the second online platform is QQ music, the music label of the first member in the collection list on the QQ music is 90 th turn and balladry, the first identity information of the first member is Zhongqing year, the character is quite quiet, the preference of the first member is biased to elegance and texture, and the preference of the first member for individually popular goods is low.
Step 150: and obtaining first preference information of the first member according to the first identity information and the first commodity information.
Step 160: and determining a first preference rate of the first member to the first shop according to the first preference information.
Specifically, according to multi-platform interaction, preference information of a user can be comprehensively optimized, namely first preference information of a first member is obtained according to first identity information of the first member and first commodity information purchased by the first member. If the first identity information of the first member is 90 years later, the characters converge inwards; the first commodity purchased by the first member is baby diaper, so that the first favorite information of the first member can be obtained from the first identity information and the first commodity information, and the first favorite information is household articles and infant articles with good texture and simple appearance. Obtaining all the types of commodities operated by the first store, and matching the first preference information of the first member with the commodities of the first store to obtain a first preference rate of the first member to the first store, wherein if the matching rate of the first preference information and the commodities of the first store is 80%, the first preference rate is 80%.
Step 170: and determining a first recommended commodity and a first recommended frequency of the first shop according to the first preference information and the first preference rate.
Specifically, the first recommended commodity of the first store can be obtained according to the first preference information of the first member, and the first recommended frequency of the first store for sending the marketing information to the first member can be obtained according to the first preference rate of the first member to the first store. The higher the first preference rate, the higher the first recommendation frequency. For example, if the first favorite information of the first member is household articles and infant articles with good texture and simple appearance, the first recommended commodity of the first store is cotton clothes of the infant in the current season; and if the first preference rate of the first member to the first shop reaches 80%, the first shop sends the marketing information of the first shop to the first member on the new commodities, holidays, weekday anniversaries, shopping mall activity days and the like, and recommends the commodity of the first shop to be sent to the first member in a daily sending mode on the multi-activity days.
Therefore, by the multi-platform interaction method in the embodiment, aiming at the first member information of the first store and the first commodity information of the first store purchased by the first member, the second online platform is logged in according to the telephone information or the mailbox information in the first member information, the first identity information of the first member is obtained according to the second online platform, the first preference information of the first member and the first preference rate of the first member to the first store are obtained by combining the first identity information with the first commodity information, the first recommended commodity and the first recommendation frequency of the first store are determined through the first preference information and the first preference rate, the multi-platform interaction is achieved, the preference information of the user is optimized in an all-round manner, the accuracy and the purchase rate of the recommended commodity are improved, the technical effect of the experience of the user is improved, and the problem that in the prior art, the shop of the e-commerce platform recommends the commodity for the user according to the shopping preference of the user is solved, the collected user information is one-sidedness, the user preference cannot be completely mastered, the accuracy of recommending commodities is low, and the commodity conversion rate is reduced.
Furthermore, the data fusion method in this embodiment may also be implemented by combining an Artificial Intelligence technology, wherein Artificial Intelligence (AI) is also called machine Intelligence, which is a subject for researching a computer to simulate some thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, and the like) of a human, and mainly includes a principle that the computer realizes Intelligence, and a computer similar to human brain Intelligence is manufactured, so that the computer can realize higher-level application. The method comprises the following specific steps: obtaining a photo of first member information of a first shop; inputting a picture of first member information of the first shop into a model, wherein the model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: first member information of the first store, first identification information for identifying a first item of the first store purchased by the first member, and second identification information for identifying first identification information of the first member on the second online platform; acquiring output information of the model, wherein the output information is a first recommended commodity and a first recommended frequency of a first shop; the output information of the model is to obtain first preference information of the first member and a first preference rate of the first member to the first store by using the first commodity in the first identification information and the first identification information in the second identification information, and determine a first recommended commodity and a first recommendation frequency of the first store according to the first preference information and the first preference rate.
Further, the training model in this embodiment is obtained by using machine learning training with multiple sets of data, where machine learning is a way to implement artificial intelligence, and has a certain similarity with data mining, and is also a multi-domain cross subject, and relates to multiple subjects such as probability theory, statistics, approximation theory, convex analysis, and computation complexity theory. Compared with the method for finding mutual characteristics among big data by data mining, the machine learning focuses on the design of an algorithm, so that a computer can learn rules from the data in a whitish manner, and unknown data can be predicted by using the rules.
Further, the method further comprises: obtaining second commodity information of a second shop purchased by the first member, wherein the second shop is from a first online platform; obtaining a first purchasing activity of the first member for purchasing the second commodity; judging whether the first purchasing activity exceeds a first preset threshold value or not; when the first purchasing activity exceeds a first preset threshold value, determining a first commodity category of the first commodity and a second commodity category of the second commodity; judging whether the first commodity category and the second commodity category have a first relevance; determining a second recommendation frequency with which the first store recommends the first item to the first member when the first item category has a first association with the second item category.
Specifically, second commodity information purchased by the first member at a second shop of the first online platform is obtained, and a first purchasing activity of the first member for purchasing the second commodity is obtained, wherein the first purchasing activity is determined by the frequency of purchasing the second commodity by the first member in a specified time. A first predetermined threshold of the first purchase activity is set, such as setting the first predetermined threshold to 50%. And judging whether the first purchasing activity exceeds a first preset threshold value, and determining a first commodity category of the first commodity and a second commodity category of the second commodity when the first purchasing activity exceeds the first preset threshold value. For example, the second commodity purchased by the first member in the second store is baby rice flour, the first purchasing activity reaches 65% and exceeds the first preset threshold value of 50%, the first commodity is baby diaper, the first commodity category is baby living goods, and the second commodity category is baby food. And judging whether the first commodity category and the second commodity category have a first relevance according to the first commodity category and the second commodity category, wherein the first relevance is obtained by analyzing and judging the commodity categories in a semantic analysis mode, and the first relevance represents that the first commodity category and the second commodity category belong to the same commodity or an audience group has the relevance. When the first commodity category and the second commodity category have a first correlation, a second recommendation frequency of the first shop for recommending the first commodity to the first member is determined, namely, the first shop can increase the recommendation frequency of the commodity to the first member.
Further, the method further comprises: obtaining first evaluation information of the first member; obtaining third commodity information according to the first evaluation information, wherein the third commodity is a commodity sold by the second shop; determining second preference information according to the third commodity information and the first identity information; determining a second preference rate of the first member to the first shop according to the second preference information; and determining a second recommended commodity and a second recommended frequency of the first shop according to the second preference information and the second preference rate.
Specifically, first evaluation information of the first member on the first online platform is obtained, and a third commodity of the second store is obtained according to the first evaluation information, wherein the first evaluation information is good evaluation information about the third commodity, namely, the first member has good physical and experience feeling for the third commodity and accords with the preference of the first member. And determining second preference information according to the third commodity purchased by the first member and the first identity information of the first member. And obtaining all commodities of the first store, matching the second preference information with the commodities of the first store, and determining the second preference rate of the first member to the first store. And determining a second recommendation frequency of the first shop recommending the second recommended commodity to the first member according to a second preference rate, wherein the higher the second preference rate, the higher the second recommendation frequency.
Further, the method further comprises: obtaining first browsing commodity information of the first member; determining first potential purchase demand information of the first member according to the first browsed commodity information; determining whether the first potential purchase demand information has a second association with the first store; when the first potential purchase demand information has a second relevance with the first shop, determining a third recommended commodity and a third recommendation frequency of the first shop according to the first potential purchase demand information.
Specifically, first browsing commodity information of commodities browsed by a first member on a first online platform is obtained, and first potential purchase demand information of the first member is determined according to the commodities browsed by the first member most frequently, the commodities browsed for the longest time and the commodities browsed by the same type of commodities in the first browsing commodity information, wherein the first potential purchase demand information is demand information of the first member for a certain commodity. It is determined whether the first potential purchase demand information has a second association with the first store, that is, whether the first potential purchase demand information of the first member has an association with the merchandise of the first store. The second relevance is that the item potentially demanded by the first member belongs to the same category of items as the item of the first store or the item of the first store can replace the item potentially demanded by the first member. When the first potential purchase demand information has a second relevance with the first shop, the purchase demand degree of the first member is determined according to the first potential purchase demand information, and the third recommended commodity and the third recommendation frequency of the first shop are determined according to the purchase demand degree.
Further, the method further comprises: obtaining a fourth commodity purchased by the first member, wherein the fourth commodity is a commodity sold by the second store; judging whether the fourth commodity has third relevance with the first identity information; determining third preference information of the first member according to the fourth commodity when the fourth commodity has a third association with the first identity information; determining a third preference rate of the first member to the first shop according to the third preference information; judging whether the third preference rate is higher than the first preference rate; and when the third preference rate is higher than the first preference rate, determining a fourth recommended commodity and a fourth recommended frequency of the first shop according to the third preference information and the third preference rate.
Specifically, by obtaining a fourth product purchased by the first member at the second store, it is determined whether the fourth product has a third association with the first identity information of the first member obtained on the second online platform, that is, whether the fourth product matches the first identity information of the first member. When the fourth commodity has a third correlation with the first identification information, third preference information of the first member and a third preference rate of the first member for the first store are determined according to the fourth commodity. And judging whether the third preference rate is higher than the first preference rate, and determining a fourth recommended commodity and a fourth recommended frequency of the first shop according to the third preference information and the third preference rate when the third preference rate is higher than the first preference rate. In other words, if the fourth item purchased by the first member at the second store matches the first identification information of the first member with a high degree of matching, the third preference rate is higher than the first preference rate, and the fourth recommended item is recommended to the first member according to the third preference information. The first shop determines a fourth recommendation frequency for recommending a fourth recommended commodity to the first member according to the third liking rate.
Example two
Based on the same inventive concept as the multi-platform interaction method in the foregoing embodiment, the present invention further provides a multi-platform interaction method apparatus, as shown in fig. 2, the apparatus includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first member information of a first store, where the first store is from a first online platform, and the first member information includes phone information or mailbox information of a first member;
a second obtaining unit 12, wherein the second obtaining unit 12 is configured to obtain first commodity information of the first store purchased by the first member;
a first operation unit 13, wherein the first operation unit 13 is used for logging in a second online platform according to the telephone information or mailbox information of the first member;
a third obtaining unit 14, the third obtaining unit 14 being configured to obtain first identity information of the first member according to the second online platform;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain first preference information of the first member according to the first identity information and the first commodity information;
a first determining unit 16, wherein the first determining unit 16 is configured to determine a first preference rate of the first member for the first store according to the first preference information;
a second determining unit 17, wherein the second determining unit 17 is configured to determine a first recommended item and a first recommended frequency of the first store according to the first preference information and the first preference rate.
Further, the apparatus comprises:
a fifth obtaining unit, configured to obtain second commodity information of a second store purchased by the first member, where the second store is from a first online platform;
a sixth obtaining unit, configured to obtain a first purchasing activity of the first member to purchase the second commodity;
a first judging unit, configured to judge whether the first purchasing activity exceeds a first preset threshold;
a third determination unit configured to determine a first item category of the first item and a second item category of the second item when the first purchase activity exceeds a first preset threshold;
a second determination unit configured to determine whether the first item category and the second item category have a first correlation;
a fourth determination unit configured to determine a second recommendation frequency with which the first shop recommends the first item to the first member when the first item category and the second item category have a first association.
Further, the apparatus comprises:
a seventh obtaining unit configured to obtain first evaluation information of the first member;
an eighth obtaining unit configured to obtain third item information according to the first evaluation information, wherein the third item is an item sold by the second store;
a fifth determining unit configured to determine second preference information based on the third commodity information and the first identity information;
a sixth determining unit, configured to determine a second liking rate of the first member to the first store according to the second liking information;
a seventh determining unit configured to determine a second recommended item and a second recommended frequency of the first store according to the second taste information and the second taste rate.
Further, the apparatus comprises:
a ninth obtaining unit configured to obtain first viewed commodity information of the first member;
an eighth determining unit configured to determine first potential purchase demand information of the first member based on the first viewed commodity information;
a third determination unit configured to determine whether the first potential purchase demand information has a second association with the first store;
a ninth determining unit configured to determine a third recommended item and a third recommended frequency of the first store according to the first potential purchase demand information when the first potential purchase demand information has a second association with the first store.
Further, the apparatus comprises:
a tenth obtaining unit configured to obtain a fourth commodity purchased by the first member, wherein the fourth commodity is a commodity sold by the second store;
a fourth judging unit, configured to judge whether the fourth commodity has a third association with the first identity information;
a tenth determining unit configured to determine third preference information of the first member based on the fourth article when the fourth article has a third association with the first identification information;
an eleventh determining unit, configured to determine a third preference rate of the first member for the first store according to the third preference information;
a fifth judging unit, configured to judge whether the third preference rate is higher than the first preference rate;
a twelfth determining unit, configured to determine a fourth recommended item and a fourth recommended frequency of the first store according to the third preference information and the third preference ratio when the third preference ratio is higher than the first preference ratio.
Various changes and specific examples of the multi-platform interaction method in the first embodiment of fig. 1 are also applicable to the multi-platform interaction device in this embodiment, and a person skilled in the art can clearly know the implementation method of the multi-platform interaction device in this embodiment through the foregoing detailed description of the multi-platform interaction method, so for the brevity of the description, detailed descriptions are omitted here.
EXAMPLE III
Based on the same inventive concept as the multi-platform interaction method in the foregoing embodiment, the present invention further provides a multi-platform interaction apparatus, as shown in fig. 3, including a memory 304, a processor 302, and a computer program stored in the memory 304 and executable on the processor 302, wherein the processor 302 implements the steps of any one of the foregoing multi-platform interaction methods when executing the program.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
Example four
Based on the same inventive concept as the multi-platform interaction method in the foregoing embodiments, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor, implements the steps of: obtaining first member information of a first store, wherein the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information of the first member; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; and determining a first recommended commodity and a first recommended frequency of the first shop according to the first preference information and the first preference rate.
In a specific implementation, when the program is executed by a processor, any method step in the first embodiment may be further implemented.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
according to the multi-platform interaction method and device provided by the embodiment of the invention, first member information of a first shop is obtained, wherein the first shop is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member; obtaining first commodity information of the first shop purchased by the first member; logging in a second online platform according to the telephone information or the mailbox information of the first member; obtaining first identity information of the first member according to the second online platform; obtaining first preference information of the first member according to the first identity information and the first commodity information; determining a first preference rate of the first member to the first shop according to the first preference information; the first recommended commodity and the first recommendation frequency of the first shop are determined according to the first preference information and the first preference rate, so that the technical problems that in the prior art, commodities are recommended to users by shops of an e-commerce platform according to shopping preferences of the users, collected user information is one-sided, the preferences of the users cannot be completely mastered, the accuracy of recommended commodities is low, and the commodity conversion rate is reduced are solved, multi-platform interaction is achieved, preference information of the users is comprehensively optimized, the accuracy and the purchase rate of the recommended commodities are improved, and the technical effect of user experience is improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. A multi-platform interaction method, the method comprising:
obtaining first member information of a first store, wherein the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member;
obtaining first commodity information of the first shop purchased by the first member;
logging in a second online platform according to the telephone information or the mailbox information of the first member;
obtaining first identity information of the first member according to the second online platform;
obtaining first preference information of the first member according to the first identity information and the first commodity information;
determining a first preference rate of the first member to the first shop according to the first preference information;
and determining a first recommended commodity and a first recommended frequency of the first shop according to the first preference information and the first preference rate.
2. The method of claim 1, wherein the method comprises:
obtaining second commodity information of a second shop purchased by the first member, wherein the second shop is from a first online platform;
obtaining a first purchasing activity of the first member for purchasing the second commodity;
judging whether the first purchasing activity exceeds a first preset threshold value or not;
when the first purchasing activity exceeds a first preset threshold value, determining a first commodity category of the first commodity and a second commodity category of the second commodity;
judging whether the first commodity category and the second commodity category have a first relevance;
determining a second recommendation frequency with which the first store recommends the first item to the first member when the first item category has a first association with the second item category.
3. The method of claim 1, wherein the method comprises:
obtaining first evaluation information of the first member;
obtaining third commodity information according to the first evaluation information, wherein the third commodity is a commodity sold by the second shop;
determining second preference information according to the third commodity information and the first identity information;
determining a second preference rate of the first member to the first shop according to the second preference information;
and determining a second recommended commodity and a second recommended frequency of the first shop according to the second preference information and the second preference rate.
4. The method of claim 1, wherein the method comprises:
obtaining first browsing commodity information of the first member;
determining first potential purchase demand information of the first member according to the first browsed commodity information;
determining whether the first potential purchase demand information has a second association with the first store;
when the first potential purchase demand information has a second relevance with the first shop, determining a third recommended commodity and a third recommendation frequency of the first shop according to the first potential purchase demand information.
5. The method of claim 1, wherein the method comprises:
obtaining a fourth commodity purchased by the first member, wherein the fourth commodity is a commodity sold by the second store;
judging whether the fourth commodity has third relevance with the first identity information;
determining third preference information of the first member according to the fourth commodity when the fourth commodity has a third association with the first identity information;
determining a third preference rate of the first member to the first shop according to the third preference information;
judging whether the third preference rate is higher than the first preference rate;
and when the third preference rate is higher than the first preference rate, determining a fourth recommended commodity and a fourth recommended frequency of the first shop according to the third preference information and the third preference rate.
6. A multi-platform interactive device, the device comprising:
the system comprises a first obtaining unit, a second obtaining unit and a third obtaining unit, wherein the first obtaining unit is used for obtaining first member information of a first store, the first store is from a first online platform, and the first member information comprises telephone information or mailbox information of a first member;
a second obtaining unit configured to obtain first commodity information of the first store purchased by the first member;
the first operation unit is used for logging in a second online platform according to the telephone information or the mailbox information of the first member;
a third obtaining unit configured to obtain first identity information of the first member according to the second online platform;
a fourth obtaining unit, configured to obtain first preference information of the first member according to the first identity information and the first commodity information;
a first determining unit, configured to determine a first preference rate of the first member for the first store according to the first preference information;
a second determining unit configured to determine a first recommended item and a first recommended frequency of the first store according to the first preference information and the first preference rate.
7. A multi-platform interactive device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any one of claims 1 to 5 are implemented when the program is executed by the processor.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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| CN201911389461.1A CN111192112A (en) | 2019-12-30 | 2019-12-30 | Multi-platform interaction method and device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112036984A (en) * | 2020-09-04 | 2020-12-04 | 烟台冰兔网络科技有限公司 | E-commerce operation big data management system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108960992A (en) * | 2018-06-29 | 2018-12-07 | 黄宗治 | A kind of information recommendation method and relevant device |
| CN109582859A (en) * | 2018-10-22 | 2019-04-05 | 中国平安人寿保险股份有限公司 | Insure method for pushing, device, computer equipment and storage medium |
| CN109636545A (en) * | 2018-12-26 | 2019-04-16 | 广州市耀锋电子网络科技有限公司 | A kind of electric business platform commercial product recommending algorithm |
| CN110490632A (en) * | 2019-07-01 | 2019-11-22 | 广州阿凡提电子科技有限公司 | A kind of potential customers' recognition methods, electronic equipment and storage medium |
| CN110489645A (en) * | 2019-08-15 | 2019-11-22 | 深圳市云积分科技有限公司 | A kind of brand association consumer orients the information processing method and device of marketing |
-
2019
- 2019-12-30 CN CN201911389461.1A patent/CN111192112A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108960992A (en) * | 2018-06-29 | 2018-12-07 | 黄宗治 | A kind of information recommendation method and relevant device |
| CN109582859A (en) * | 2018-10-22 | 2019-04-05 | 中国平安人寿保险股份有限公司 | Insure method for pushing, device, computer equipment and storage medium |
| CN109636545A (en) * | 2018-12-26 | 2019-04-16 | 广州市耀锋电子网络科技有限公司 | A kind of electric business platform commercial product recommending algorithm |
| CN110490632A (en) * | 2019-07-01 | 2019-11-22 | 广州阿凡提电子科技有限公司 | A kind of potential customers' recognition methods, electronic equipment and storage medium |
| CN110489645A (en) * | 2019-08-15 | 2019-11-22 | 深圳市云积分科技有限公司 | A kind of brand association consumer orients the information processing method and device of marketing |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112036984A (en) * | 2020-09-04 | 2020-12-04 | 烟台冰兔网络科技有限公司 | E-commerce operation big data management system |
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