CN110766478A - Method and device for improving user connectivity - Google Patents
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- CN110766478A CN110766478A CN201911054076.1A CN201911054076A CN110766478A CN 110766478 A CN110766478 A CN 110766478A CN 201911054076 A CN201911054076 A CN 201911054076A CN 110766478 A CN110766478 A CN 110766478A
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Abstract
The invention provides a method and a device for improving user connectivity, which relate to the technical field of data processing, and are characterized in that a first association relation between a first user and a second user is judged by obtaining purchase lists of the first user and the second user, wherein the purchase lists of the first user and the second user both have a first commodity and a second commodity, when the first association relation exists between the first user and the second user, a first recommended combination is obtained, then a third purchase list of a third user is obtained, the third purchase list has the first commodity, then the first association relation between the third user and the first user or between the third user and the second user is judged, when the third user has the first association relation with any one of the first user and the second user, the second commodity in the first recommended combination is recommended to the third user, and when the third user purchases the second commodity, the first association relation is weighted and assigned, and then reach and improve user connectivity, accurate target crowd of delineating marketing, improve marketing precision and hit rate.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for improving user connectivity.
Background
The electronic commerce is a novel business operation mode which is used for enabling buyers and sellers to conduct various business activities without conspiracy in the wide business activities around the world under the open network environment of the internet based on a browser/server application mode, and realizing online shopping of consumers, online transactions and online electronic payment among merchants, various business activities and related comprehensive service activities. Under the mobile internet era, the electric commodity cards have the current situations of information explosion, click rate reduction, slow growth of terminal users, gradual overdraft of population dividends and great increase of online flow cost. The electric commodity plate side needs to adopt a plurality of marketing modes to stimulate consumers to shop, and the user activity of the electric commodity plate side is improved.
However, the applicant of the present invention finds that the prior art has at least the following technical problems:
when the electric commodity plate side plans and markets, the target crowd cannot be locked quickly, so that the user connectivity is poor, and the business conversion rate is low.
Disclosure of Invention
The embodiment of the invention provides a method and a device for improving user connectivity, which solve the technical problems of poor user connectivity and low business conversion rate caused by the fact that target crowds cannot be quickly locked when an electronic commodity brand plans marketing in the prior art, achieve the technical effects of accurately delineating marketing target crowds of electronic commerce brand parties, improving user connectivity, improving marketing accuracy and hit rate, reducing transaction cost, improving transaction efficiency and improving service level and user experience of electronic commerce brands.
In view of the above problems, the present application embodiments are proposed to provide a method and apparatus for improving user connectivity.
In a first aspect, the present invention provides a method for improving user connectivity, the method comprising: obtaining a first purchase list of a first user, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories; obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity; judging whether the first user and the second user have a first association relation or not; when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity; obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity; judging whether the third user and the first user or the third user and the second user have the first association relationship; recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user; judging the purchase condition of the third user for purchasing the second commodity; and when the third user purchases the second commodity within the preset time, performing first weighted assignment on the first association relation.
Preferably, after determining the purchase condition of the second product purchased by the third user, the method includes:
and when the third user does not purchase the second commodity within the preset time, performing first weight reduction assignment on the first association relation.
Preferably, the determining whether the first user and the second user have a first association relationship includes:
obtaining a first tag of the first user; obtaining a second label of the second user; judging whether the first label and the second label have first similarity or not; when the first label and the second label have a first similarity, determining that the first user and the second user have a first association relationship.
Preferably, the determining whether the third user and the first user or the third user and the second user have the first association relationship includes:
obtaining a third label of a third user; judging whether the third label and the first label have first similarity or not, or whether the third label and the second label have first similarity or not; when the third label has a first similarity with the first label or the third label has a first similarity with the second label, determining that the third user has a first association relationship with the first user or the third user has a first association relationship with the second user.
Preferably, the method further comprises:
obtaining a commodity browsing record of the third user; judging whether the second commodity is in the commodity browsing record; when the second commodity is in the commodity browsing record, determining the browsing times of the second commodity; judging whether the browsing times exceed a first preset threshold value; and when the browsing times exceed a first preset threshold value, performing second weighted assignment on the first association relation.
Preferably, the method further comprises:
obtaining a fourth purchase list of a fourth user, wherein the fourth purchase list of the fourth user has a third commodity, and the third commodity and the first commodity belong to the same commodity class; judging whether the fourth user and the first user or the second user have the first association relationship; determining a first price for the first item and a second price for the third item when the fourth user has the first association with the first user or when the fourth user has the first association with the second user; judging whether the price difference between the first price and the second price exceeds a second preset threshold value or not; recommending the first commodity to the fourth user when the price difference does not exceed a preset threshold value; judging the purchase condition of the first commodity purchased by the fourth user; and when the fourth user purchases the first commodity within the preset time, performing third weighted assignment on the first association relation.
In a second aspect, the present invention provides an apparatus for improving user connectivity, the apparatus comprising:
the system comprises a first obtaining unit, a second obtaining unit and a display unit, wherein the first obtaining unit is used for obtaining a first purchase list of a first user, the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories;
a second obtaining unit, configured to obtain a second purchase list of a second user, where the second purchase list includes the first item and the second item;
the first judging unit is used for judging whether the first user and the second user have a first association relationship;
a third obtaining unit, configured to obtain a first recommended combination when the first user and the second user have a first association relationship, where the first recommended combination includes the first commodity and the second commodity;
a fourth obtaining unit, configured to obtain a third purchase list of a third user, where the third purchase list of the third user has the first product;
a second determining unit, configured to determine whether the third user and the first user or the third user and the second user have the first association relationship;
a first execution unit, configured to recommend the second product in the first recommended combination to the third user when the third user has the first association relationship with the first user or when the third user has the first association relationship with the second user;
a third judging unit, configured to judge a purchase condition of the second product purchased by the third user;
and the second execution unit is used for performing first weighted assignment on the first association relation when the third user purchases the second commodity within preset time.
Preferably, the third determination unit, after determining that the third user purchased the second product, includes:
and the third execution unit is used for performing first weight reduction assignment on the first association relation when the third user does not purchase the second commodity within preset time.
Preferably, the determining, by the first determining unit, whether the first user and the second user have a first association relationship includes:
a fifth obtaining unit, configured to obtain a first tag of the first user;
a sixth obtaining unit, configured to obtain a second tag of the second user;
a fourth judging unit, configured to judge whether the first tag and the second tag have a first similarity;
a fourth executing unit, configured to determine that the first user and the second user have a first association relationship when the first tag and the second tag have a first similarity.
Preferably, the determining, by the second determining unit, whether the third user and the first user or the third user and the second user have the first association relationship includes:
a seventh obtaining unit, configured to obtain a third tag of a third user;
a fifth judging unit, configured to judge whether the third tag and the first tag have a first similarity, or whether the third tag and the second tag have a first similarity;
a first determining unit, configured to determine that the third user has a first association relationship with the first user or the third user has a first association relationship with the second user when the third tag has a first similarity with the first tag or the third tag has a first similarity with the second tag.
Preferably, the apparatus further comprises:
an eighth obtaining unit, configured to obtain a commodity browsing record of the third user;
a sixth judging unit, configured to judge whether the second commodity is in the commodity browsing record;
a second determining unit, configured to determine the browsing times of the second item when the second item is in the item browsing record;
a sixth judging unit, configured to judge whether the browsing frequency exceeds a first preset threshold;
and the fifth execution unit is used for performing second weighted assignment on the first association relation when the browsing times exceed a first preset threshold value.
Preferably, the apparatus further comprises:
a ninth obtaining unit, configured to obtain a fourth purchase list of a fourth user, where the fourth purchase list of the fourth user has a third article, and the third article and the first article belong to the same article class;
a seventh determining unit, configured to determine whether the fourth user and the first user or the fourth user and the second user have the first association relationship;
a third determining unit configured to determine a first price of the first item and a second price of the third item when the fourth user has the first association with the first user or when the fourth user has the first association with the second user;
an eighth judging unit, configured to judge whether a price difference between the first price and the second price exceeds a second preset threshold;
a sixth executing unit, configured to recommend the first commodity to the fourth user when the price difference does not exceed a preset threshold;
a ninth judging unit configured to judge a purchase condition of the first commodity by the fourth user;
a seventh executing unit, configured to perform third weighted assignment on the first association relationship when the fourth user purchases the first commodity within a predetermined time.
In a third aspect, the invention provides a server comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor performing the steps of any of the methods described above.
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 method and the device for improving the user connectivity, a first purchase list of a first user is obtained, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories; obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity; judging whether the first user and the second user have a first association relation or not; when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity; obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity; judging whether the third user and the first user or the third user and the second user have the first association relationship; recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user; judging the purchase condition of the third user for purchasing the second commodity; when the third user purchases the second commodity within the preset time, the first weighting assignment is carried out on the first association relation, so that the technical problems that target crowds cannot be locked quickly when the electric commodity brand plans marketing in the prior art are solved, user connectivity is poor, and business conversion rate is low are solved, the marketing target crowds of electric commodity brand parties are accurately defined, user connectivity is improved, marketing accuracy and hit rate are improved, the transaction cost is reduced, the transaction efficiency is improved, and the service level and the user experience of the electric commodity brand are 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 schematic flow chart of a method for improving user connectivity according to a first aspect of an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an apparatus for improving user connectivity according to a second aspect of an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a server according to a third aspect of the embodiment of the present invention.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first judging unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a second judging unit 16, a first executing unit 17, a third judging unit 18, a second executing unit 19, 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 method and a device for improving user connectivity, which are used for solving the technical problems of poor user connectivity and low business conversion rate caused by the fact that target crowds cannot be locked quickly when electric commodity plate planning and marketing in the prior art.
The technical scheme provided by the invention has the following general idea: obtaining a first purchase list of a first user, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories; obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity; judging whether the first user and the second user have a first association relation or not; when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity; obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity; judging whether the third user and the first user or the third user and the second user have the first association relationship; recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user; judging the purchase condition of the third user for purchasing the second commodity; when the third user purchases the second commodity in preset time, first weighting assignment is carried out on the first association relation, and therefore marketing target crowds of e-commerce brand parties are accurately defined, user connectivity is improved, marketing accuracy and hit rate are improved, trading efficiency is improved while trading cost is reduced, and the service level and the user experience of the e-commerce brand are 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 method for improving user connectivity according to an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides a method for improving user connectivity, where the method includes steps 110 to 190 as follows:
step 110: a first purchase list of a first user is obtained, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories.
Step 120: a second purchase list of a second user is obtained, wherein the second purchase list comprises the first commodity and the second commodity.
Specifically, the method for improving user connectivity in the embodiment of the present application obtains purchase lists of two different users, where the purchase lists of the two different users both have a first commodity and a second commodity, and further determines an association relationship between the first user and the second user, and when the two users have an association relationship, obtains a first recommended combination, and then obtains a third purchase list of a third user, where the third purchase list has the first commodity, and further determines an association relationship between the third user and the first user or between the third user and the second user, and when the third user and any one of the first user and the second user have an association relationship, recommends the second commodity in the first recommended combination to the third user, and further when the third user purchases the second commodity, performs weighted assignment on the association relationship, which indicates that the association relationship between the three users is close and has a high association degree, and then user connectivity is improved, marketing target crowds of electronic commerce brand parties are accurately determined, marketing accuracy and hit rate are improved, and trading efficiency is improved while trading cost is reduced. First, the first user and the second user are registered users of the same e-commerce platform. The first purchase list is a list of commodities purchased by the first user on the E-commerce platform, and the second purchase list is a list of commodities purchased by the second user on the E-commerce platform. In the first purchase list, there are a plurality of commodities, in which there are a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories such as cosmetics and foods. There are also a plurality of items in the second purchase list, including the first item and the second item.
Step 130: and judging whether the first user and the second user have a first association relation.
Step 140: when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity.
Further, the determining whether the first user and the second user have a first association relationship includes: obtaining a first tag of the first user; obtaining a second label of the second user; judging whether the first label and the second label have first similarity or not; when the first label and the second label have a first similarity, determining that the first user and the second user have a first association relationship.
Specifically, the purchasing lists of the first user and the second user are obtained on the same e-commerce platform, and then the first association relationship between the first user and the second user is determined, that is, whether the first user and the second user have the first association relationship is determined. Wherein, the first association relationship is the association relationship existing between the users in the self attribute or the purchasing characteristic. The first label is an inherent attribute or purchasing behavior characteristic of the first user, and the second label is an inherent attribute or purchasing behavior characteristic of the second user. And judging whether the first label and the second label have a first similarity, and determining that the first user and the second user have a first association relationship when the first label and the second label have the first similarity. When the first user and the second user have the first association relationship, the first commodity and the second commodity are used as a combined commodity, namely a first recommended combination. For example, a certain purchase list and a certain plum purchase list are obtained on a small red book, the shopping lists of two persons both have a Xin La face and a glacier mask, the Zhang Yi often shares various gourmets on the small red book, so that the first label of the Zhang Yi is a gourmet darner, the second label of the Lian Yi is a Baoma, the two labels are compared to determine that the two labels have a certain association degree with food, the first similarity obtained by the comparison is 60%, the fact that the Lian and the Zhang Yi have a first association relation is determined, and the Xin La face and the glacier mask are taken as a combined commodity.
Step 150: obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity.
Specifically, the third user is a registered user on the same e-commerce platform as the first user and the second user. The third purchase list is a list of purchased commodities of a third user on the e-commerce platform, the first commodity exists in the third purchase list, or the second commodity exists in the third purchase list, namely any one of the first commodity and the second commodity exists in the third purchase list. That is, the third purchase list of the third user is different from the first purchase list of the first user and the second purchase list of the second user, and only includes one of the common commodities in the first purchase list and the second purchase list. For example, if there is a spicy noodle in the shopping list of Wangzao on the small red book, the shopping list of Wangzao is obtained. In addition, the first commodity can be obtained by obtaining collection information, sharing information or high-frequency browsing information of a third user on the e-commerce platform, and the first commodity is a commodity in a purchase list of the first user and the second user.
Step 160: and judging whether the third user and the first user or the third user and the second user have the first association relationship.
Step 170: recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user.
Further, the determining whether the third user and the first user or the third user and the second user have the first association relationship includes: obtaining a third label of a third user; judging whether the third label and the first label have first similarity or not, or whether the third label and the second label have first similarity or not; when the third label has a first similarity with the first label or the third label has a first similarity with the second label, determining that the third user has a first association relationship with the first user or the third user has a first association relationship with the second user.
Specifically, it is determined whether the third user has a first association relationship with the first user or the third user has a first association relationship with the second user, that is, whether the tag information of the third user and the tag information of the first user or the second user have a first similarity. The third label is an inherent attribute or purchasing behavior characteristic of the third user. Judging whether the third label has a first similarity with the first label or whether the third label has the first similarity with the second label, namely judging whether the third label has a similarity with the first label or the second label on the inherent attribute or the purchasing behavior characteristic, calculating the similarity, and determining that the third label has the first similarity with the first label or the second label when the first similarity exceeds a set threshold, such as the set threshold is 50%. And when the third label has the first similarity with the first label or the third label has the first similarity with the second label, determining that the third user has the first association relationship with the first user or the third user has the first association relationship with the second user. When the third user has the first association relationship with the first user, or when the third user has the first association relationship with the second user, the second item in the first recommended combination in step 140 is recommended to the third user. For example, the label information of wang in the small red book is a travel fan, local gourmet can be shared at a travel destination, through data comparison, the label information of wang and zhang has a first similarity, and the value of the first similarity is 62%, so that wang and zhang have a first association relationship, the purchased glacier mask is recommended to wang, and the small red book can adopt a short message or push information about the glacier mask, the discount condition of the glacier mask, efficacy information and the like to wang in the first page of the small red book.
Step 180: and judging the purchase condition of the third user for purchasing the second commodity.
Step 190: and when the third user purchases the second commodity within the preset time, performing first weighted assignment on the first association relation.
Further, after the determining the purchase condition of the second product purchased by the third user, the method includes: and when the third user does not purchase the second commodity within the preset time, performing first weight reduction assignment on the first association relation.
Specifically, after the second commodity information is recommended to the third user through step 170, it is determined whether the third user purchases the second commodity, and when the third user purchases the second commodity within the predetermined time, a first weighting assignment is performed on the first association relationship, that is, when the third user purchases the second commodity within the predetermined time, it is determined that the association degree of the first association relationship between the third user and the first user or between the third user and the second user is large, and then a first weighting assignment is performed on the first association relationship. The first weighted assignment is obtained by calculating according to the value of the first similarity, the times of purchasing the second commodity by the third user, the quantity of purchasing the second commodity and the evaluation of the second commodity, and the first weighted assignment is a natural number larger than 1. The preset time is one month after the E-commerce platform sends the recommended second commodity information to the third user. And when the third user does not purchase the second commodity within the preset time, performing first weight reduction assignment on the first association relation, wherein the first weight reduction assignment is obtained by calculation according to the information of the second commodity pushed by the e-commerce platform and the value of the first similarity, and the first weight reduction assignment is a natural number between 0 and 1. For example, if a wang sends a recommended glacier mask to a wang-hong book and purchases the glacier mask one week later, a first weighted assignment is performed on a first association relationship between the wang and the wang, and the coefficient of the first association relationship is 1.8 after the first weighted assignment is calculated to be 1.8.
Therefore, the method for improving the user connectivity in the embodiment can further determine the magnitude of the incidence relation of the users according to the relation between the purchase lists of different users and the users on the e-commerce platform, so that the target population of the e-commerce brand can be accurately obtained, the user connectivity is improved, the marketing accuracy and the hit rate are improved, the transaction efficiency is improved while the transaction cost is reduced, the service level and the user experience of the e-commerce brand are improved, the customers can be helped to quickly know the marketing activities of the intention products, the customers can conveniently and efficiently shop, and the technical problems that in the prior art, when the e-commerce brand plans and markets, the target population cannot be quickly locked, the user connectivity is poor, and the service conversion rate is low are solved.
Furthermore, the method for improving user connectivity in this embodiment may also be implemented by combining an Artificial Intelligence technology, where Artificial Intelligence (AI) is also called intelligent machine and machine Intelligence, and 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 a computer realizes Intelligence, and manufacturing a computer similar to human brain Intelligence, so that the computer can realize higher-level applications. The method comprises the following specific steps: the method comprises the steps of obtaining photos of a first user, a second user and a third user, wherein the photos of the first user, the second user and the third user comprise a first purchase list of the first user, a second purchase list of the second user and a third purchase list of the third user, the first purchase list and the second purchase list comprise a first commodity and a second commodity, and the third purchase list comprises the first commodity; inputting the pictures of the first user, the second user and the third user into a model, wherein the model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: the system comprises photos of a first user, a second user and a third user, a first identifier used for identifying a first incidence relation between the third user and the first user or the second user, and a second identifier used for identifying the third user to purchase a second commodity; acquiring output information of the model, wherein the output information is obtained by performing first weighted assignment on a first incidence relation; and after the output information of the model determines that a first association relationship exists between the first user and the second user by screening, further screening and determining that a first association relationship exists between the third user and the first user or the second user, recommending the second commodity to the third user, and outputting a first weighted assignment to the first association relationship after determining that the third user purchases the second commodity.
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 a commodity browsing record of the third user; judging whether the second commodity is in the commodity browsing record; when the second commodity is in the commodity browsing record, determining the browsing times of the second commodity; judging whether the browsing times exceed a first preset threshold value; and when the browsing times exceed a first preset threshold value, performing second weighted assignment on the first association relation.
Specifically, whether the second commodity is in the commodity browsing record is judged by obtaining the commodity browsing record of the third user on the e-commerce platform, and when the third user browses the second commodity, the frequency of browsing the second commodity by the third user is further determined. And judging the times of browsing the second commodity by the third client, and setting a first preset threshold value for the browsing times, such as 3 times. And when the times of browsing the second commodity by the third client exceed a first preset threshold value, performing second weighted assignment on the first association relation, wherein the second weighted assignment is obtained by calculation according to the number of the browsing times and the browsing time, for example, setting the value of the second weighted assignment to be a natural number between 1 and 2.
Further, the method further comprises: obtaining a fourth purchase list of a fourth user, wherein the fourth purchase list of the fourth user has a third commodity, and the third commodity and the first commodity belong to the same commodity class; judging whether the fourth user and the first user or the second user have the first association relationship; determining a first price for the first item and a second price for the third item when the fourth user has the first association with the first user or when the fourth user has the first association with the second user; judging whether the price difference between the first price and the second price exceeds a second preset threshold value or not; recommending the first commodity to the fourth user when the price difference does not exceed a preset threshold value; judging the purchase condition of the first commodity purchased by the fourth user; and when the fourth user purchases the first commodity within the preset time, performing third weighted assignment on the first association relation.
Specifically, a fourth purchase list of a fourth user on the e-commerce platform is obtained, and a third commodity is arranged in the fourth purchase list, wherein the third commodity and the first commodity belong to the same commodity class, for example, the third commodity and the first commodity belong to a household commodity class. And judging whether the fourth user and the first user or the second user have a first association relationship, namely judging whether the label of the fourth user and the first user or the second user has a first similarity through the label information of the fourth user. When the fourth user has the first association relationship with the first user or when the fourth user has the first association relationship with the second user, the first price of the first commodity and the second price of the third commodity are further determined. And judging the price difference between the first price and the second price, and setting a second preset threshold value of the price difference, such as 50 yuan. And recommending the first commodity to the fourth user when the price difference does not exceed the second preset threshold value. And further judging whether the fourth user purchases the first commodity at a predetermined time, wherein the predetermined time is set to 1 month. And when the fourth user purchases the first commodity within the preset time, performing third weighted assignment on the first association relationship, wherein the third weighted assignment is obtained by calculating the value of the first similarity between the fourth user and the first user or the second user, the frequency of purchasing the second commodity by the fourth user, the number of purchasing the second commodity, the evaluation of the second commodity and the price difference.
Example two
Based on the same inventive concept as the method for improving user connectivity in the foregoing embodiment, the present invention further provides a method and an apparatus for improving user connectivity, as shown in fig. 2, where the apparatus includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain a first purchase list of a first user, where the first purchase list includes a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a second purchase list of a second user, where the second purchase list includes the first product and the second product;
a first judging unit 13, where the first judging unit 13 is configured to judge whether the first user and the second user have a first association relationship;
a third obtaining unit 14, where the third obtaining unit 14 is configured to obtain a first recommended combination when the first user and the second user have a first association relationship, where the first recommended combination includes the first commodity and the second commodity;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a third purchase list of a third user, where the third purchase list of the third user has the first item;
a second determining unit 16, where the second determining unit 16 is configured to determine whether the third user and the first user or the third user and the second user have the first association relationship;
a first executing unit 17, where the first executing unit 17 is configured to recommend the second product in the first recommended combination to the third user when the third user has the first association relationship with the first user or when the third user has the first association relationship with the second user;
a third judging unit 18, wherein the third judging unit 18 is configured to judge a purchase condition of the second product purchased by the third user;
a second executing unit 19, where the second executing unit 19 is configured to perform a first weighted assignment on the first association relationship when the third user purchases the second product within a predetermined time.
Further, after the third determining unit determines that the third user purchases the second product, the method includes:
and the third execution unit is used for performing first weight reduction assignment on the first association relation when the third user does not purchase the second commodity within preset time.
Further, the determining, by the first determining unit, whether the first user and the second user have a first association relationship includes:
a fifth obtaining unit, configured to obtain a first tag of the first user;
a sixth obtaining unit, configured to obtain a second tag of the second user;
a fourth judging unit, configured to judge whether the first tag and the second tag have a first similarity;
a fourth executing unit, configured to determine that the first user and the second user have a first association relationship when the first tag and the second tag have a first similarity.
Further, the determining, by the second determining unit, whether the third user and the first user or the third user and the second user have the first association relationship includes:
a seventh obtaining unit, configured to obtain a third tag of a third user;
a fifth judging unit, configured to judge whether the third tag and the first tag have a first similarity, or whether the third tag and the second tag have a first similarity;
a first determining unit, configured to determine that the third user has a first association relationship with the first user or the third user has a first association relationship with the second user when the third tag has a first similarity with the first tag or the third tag has a first similarity with the second tag.
Further, the apparatus further comprises:
an eighth obtaining unit, configured to obtain a commodity browsing record of the third user;
a sixth judging unit, configured to judge whether the second commodity is in the commodity browsing record;
a second determining unit, configured to determine the browsing times of the second item when the second item is in the item browsing record;
a sixth judging unit, configured to judge whether the browsing frequency exceeds a first preset threshold;
and the fifth execution unit is used for performing second weighted assignment on the first association relation when the browsing times exceed a first preset threshold value.
Further, the apparatus further comprises:
a ninth obtaining unit, configured to obtain a fourth purchase list of a fourth user, where the fourth purchase list of the fourth user has a third article, and the third article and the first article belong to the same article class;
a seventh determining unit, configured to determine whether the fourth user and the first user or the fourth user and the second user have the first association relationship;
a third determining unit configured to determine a first price of the first item and a second price of the third item when the fourth user has the first association with the first user or when the fourth user has the first association with the second user;
an eighth judging unit, configured to judge whether a price difference between the first price and the second price exceeds a second preset threshold;
a sixth executing unit, configured to recommend the first commodity to the fourth user when the price difference does not exceed a preset threshold;
a ninth judging unit configured to judge a purchase condition of the first commodity by the fourth user;
a seventh executing unit, configured to perform third weighted assignment on the first association relationship when the fourth user purchases the first commodity within a predetermined time.
Various modifications and specific examples of the method for improving user connectivity in the first embodiment of fig. 1 are also applicable to the apparatus for improving user connectivity in the present embodiment, and a detailed description of the method for improving user connectivity is given above to make it clear to those skilled in the art that the method for improving user connectivity in the present embodiment is implemented, so for brevity of description, detailed descriptions are omitted here.
EXAMPLE III
Based on the same inventive concept as the method for improving user connectivity in the previous embodiment, the present invention further provides a server, 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 executes the computer program to implement the steps of any one of the methods for improving user connectivity.
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 method of improving user connectivity in the previous embodiments, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of: obtaining a first purchase list of a first user, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories; obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity; judging whether the first user and the second user have a first association relation or not; when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity; obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity; judging whether the third user and the first user or the third user and the second user have the first association relationship; recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user; judging the purchase condition of the third user for purchasing the second commodity; and when the third user purchases the second commodity within the preset time, performing first weighted assignment on the first association relation.
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 method and the device for improving the user connectivity, a first purchase list of a first user is obtained, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories; obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity; judging whether the first user and the second user have a first association relation or not; when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity; obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity; judging whether the third user and the first user or the third user and the second user have the first association relationship; recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user; judging the purchase condition of the third user for purchasing the second commodity; when the third user purchases the second commodity within the preset time, the first weighting assignment is carried out on the first association relation, so that the technical problems that target crowds cannot be locked quickly when the electric commodity brand plans marketing in the prior art are solved, user connectivity is poor, and business conversion rate is low are solved, the marketing target crowds of electric commodity brand parties are accurately defined, user connectivity is improved, marketing accuracy and hit rate are improved, the transaction cost is reduced, the transaction efficiency is improved, and the service level and the user experience of the electric commodity brand are 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 (9)
1. A method for improving user connectivity, the method comprising:
obtaining a first purchase list of a first user, wherein the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories;
obtaining a second purchase list of a second user, wherein the second purchase list comprises the first commodity and the second commodity;
judging whether the first user and the second user have a first association relation or not;
when the first user and the second user have a first association relationship, obtaining a first recommended combination, wherein the first recommended combination comprises the first commodity and the second commodity;
obtaining a third purchase list of a third user, wherein the third purchase list of the third user has the first commodity;
judging whether the third user and the first user or the third user and the second user have the first association relationship;
recommending the second commodity in the first recommendation combination to the third user when the third user has the first association relation with the first user or when the third user has the first association relation with the second user;
judging the purchase condition of the third user for purchasing the second commodity;
and when the third user purchases the second commodity within the preset time, performing first weighted assignment on the first association relation.
2. The method of claim 1, wherein said determining said third user's purchase of said second item comprises:
and when the third user does not purchase the second commodity within the preset time, performing first weight reduction assignment on the first association relation.
3. The method of claim 1, wherein said determining whether the first user has a first relationship with the second user comprises:
obtaining a first tag of the first user;
obtaining a second label of the second user;
judging whether the first label and the second label have first similarity or not;
when the first label and the second label have a first similarity, determining that the first user and the second user have a first association relationship.
4. The method of claim 1, wherein said determining whether the third user has the first association with the first user or the third user has the second user comprises:
obtaining a third label of a third user;
judging whether the third label and the first label have first similarity or not, or whether the third label and the second label have first similarity or not;
when the third label has a first similarity with the first label or the third label has a first similarity with the second label, determining that the third user has a first association relationship with the first user or the third user has a first association relationship with the second user.
5. The method of claim 1, wherein the method further comprises:
obtaining a commodity browsing record of the third user;
judging whether the second commodity is in the commodity browsing record;
when the second commodity is in the commodity browsing record, determining the browsing times of the second commodity;
judging whether the browsing times exceed a first preset threshold value;
and when the browsing times exceed a first preset threshold value, performing second weighted assignment on the first association relation.
6. The method of claim 1, wherein the method further comprises:
obtaining a fourth purchase list of a fourth user, wherein the fourth purchase list of the fourth user has a third commodity, and the third commodity and the first commodity belong to the same commodity class;
judging whether the fourth user and the first user or the second user have the first association relationship;
determining a first price for the first item and a second price for the third item when the fourth user has the first association with the first user or when the fourth user has the first association with the second user;
judging whether the price difference between the first price and the second price exceeds a second preset threshold value or not;
recommending the first commodity to the fourth user when the price difference does not exceed a preset threshold value;
judging the purchase condition of the first commodity purchased by the fourth user;
and when the fourth user purchases the first commodity within the preset time, performing third weighted assignment on the first association relation.
7. An apparatus for improving user connectivity, the apparatus comprising:
the system comprises a first obtaining unit, a second obtaining unit and a display unit, wherein the first obtaining unit is used for obtaining a first purchase list of a first user, the first purchase list comprises a first commodity and a second commodity, and the first commodity and the second commodity belong to different commodity categories;
a second obtaining unit, configured to obtain a second purchase list of a second user, where the second purchase list includes the first item and the second item;
the first judging unit is used for judging whether the first user and the second user have a first association relationship;
a third obtaining unit, configured to obtain a first recommended combination when the first user and the second user have a first association relationship, where the first recommended combination includes the first commodity and the second commodity;
a fourth obtaining unit, configured to obtain a third purchase list of a third user, where the third purchase list of the third user has the first product;
a second determining unit, configured to determine whether the third user and the first user or the third user and the second user have the first association relationship;
a first execution unit, configured to recommend the second product in the first recommended combination to the third user when the third user has the first association relationship with the first user or when the third user has the first association relationship with the second user;
a third judging unit, configured to judge a purchase condition of the second product purchased by the third user;
and the second execution unit is used for performing first weighted assignment on the first association relation when the third user purchases the second commodity within preset time.
8. A server 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 of claims 1-6 are implemented when the program is executed by the processor.
9. 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 6.
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