CN111125536A - Information pushing method and device, computer equipment and storage medium - Google Patents
Information pushing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention discloses an information pushing method and device, computer equipment and a storage medium, and belongs to the technical field of networks. The embodiment of the invention determines the preferred product of each target user based on the historical consumption record; and further determining a target hot sales product from a plurality of user preference products of a plurality of target users, sending pushing information of the target hot sales product to a target user set, and pushing group hot sales products in a group of the target user set, so that the information pushing efficiency and accuracy are improved, and the conversion rate of the pushed products into effective products in the group is improved.
Description
Technical Field
The present invention relates to the field of network technologies, and in particular, to an information pushing method and apparatus, a computer device, and a storage medium.
Background
With the explosion of network technology, users can browse a wide variety of information from network platforms, such as browsing news from news platforms, browsing merchandise from e-commerce platforms, and so on. Wherein, various network platforms can also push proper information like users.
In the related art, the information pushing process may include: the server builds a recommendation model in advance based on a large amount of historical click data of the user, when pushing is needed, a vector corresponding to the positive behavior and a vector corresponding to the negative behavior of the user can be input into the recommendation model by using the recommendation model, wherein the message pushed by the user when clicked is the positive behavior, and the message pushed by the user when not clicked is the negative behavior, the server outputs information to be pushed, and pushes the information to the user.
The recommendation model needs to be trained in advance in the process, and when the historical click data used by the training model is less, the model is over-fitted, so that the information pushing efficiency and accuracy are lower. In addition, in the information pushing process, only the click behavior of the user on the pushed message is considered, but the user can also purchase, download and the like the pushed message, so that the process enables the probability of converting the pushed message into effective information to be low, that is, the conversion rate of the information pushing to be low.
Disclosure of Invention
The embodiment of the invention provides an information pushing method, an information pushing device, computer equipment and a storage medium, which can solve the problem of low conversion rate of information pushing in the related technology. The technical scheme is as follows:
in one aspect, an information pushing method is provided, where the method includes:
receiving a target pushing instruction, wherein the target pushing instruction is used for indicating that a hot-selling product is pushed to a target user set;
determining a user preference product of each target user according to the historical consumption record of each target user in the target user set;
determining a user popularity for each user preference product based on a plurality of user preference products for a plurality of target users, the user popularity being indicative of how much the user preference product is liked in the set of target users;
and screening target hot sales products from the multiple user preference products according to the user heat of each user preference product, generating push information of the target hot sales products, and sending the push information to each target user in the target user set.
In one possible implementation, the determining the user popularity for each user preference product based on a plurality of user preference products of a plurality of target users comprises any one of:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users who trade the user preference product in the target user set;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
In one possible implementation, the determining, according to the historical consumption record of each target user in the set of target users, a user preference product of each target user includes:
according to the historical consumption record of each target user in the target user set, counting the historical transaction times of each product of the historical transaction of each target user;
and according to the historical transaction times of each product, the multiple products of each target user are arranged in a descending order, and multiple user preference products with the historical transaction times at the previous first target number are screened out from the multiple products.
In one possible implementation manner, the counting the historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the target user set includes:
for each target user, screening a plurality of target consumption records of which the historical transaction environmental states are matched with the environmental states from the historical consumption records of the target user according to the corresponding environmental states at the target time, wherein the target time is the time of pushing the pushing information;
according to the target consumption records of the target user, counting the historical transaction times of each product of the historical transaction of the target user;
wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time.
In one possible implementation, the screening out the target hot-selling product from the plurality of user-preferred products according to the user heat of each user-preferred product comprises:
according to the user heat of various user preference products, performing descending order arrangement on the various user preference products;
and screening out target hot sales products with the user heat degrees in the second target number from the multiple user preference products according to the descending order.
In one possible implementation, the generating push information for the target hot-sell product, and sending the push information to each target user in the set of target users includes:
screening out a target information template corresponding to each hot-sold product from the corresponding relation between the plurality of product categories and the plurality of information templates according to the product category to which each target hot-sold product belongs;
and generating push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sending the push information to each target user in the target user set.
In another aspect, an information pushing apparatus is provided, the apparatus including:
the receiving module is used for receiving a target pushing instruction, and the target pushing instruction is used for indicating that a hot-selling product is pushed to a target user set;
the determining module is used for determining a user preference product of each target user according to the historical consumption record of each target user in the target user set;
the determining module is further used for determining the user popularity of each user preference product based on a plurality of user preference products of a plurality of target users, and the user popularity is used for indicating the degree of the user preference products being favored in the target user set;
and the pushing module is used for screening target hot selling products from the various user preference products according to the user heat of each user preference product, generating pushing information of the target hot selling products, and sending the pushing information to each target user in the target user set.
In one possible implementation, the determining module is further configured to:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users who trade the user preference product in the target user set;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
In a possible implementation manner, the determining module is further configured to count historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the set of target users; and according to the historical transaction times of each product, the multiple products of each target user are arranged in a descending order, and multiple user preference products with the historical transaction times at the previous first target number are screened out from the multiple products.
In a possible implementation manner, the determining module is further configured to, for each target user, screen out, from historical consumption records of the target user, a plurality of target consumption records of which historical transaction environmental states are matched with the environmental states according to the environmental state corresponding to target time, where the target time is a time to push the push information; according to the target consumption records of the target user, counting the historical transaction times of each product of the historical transaction of the target user;
wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time.
In one possible implementation manner, the pushing module is further configured to sort the plurality of user-preferred products in a descending order according to the user popularity of the plurality of user-preferred products; and screening out target hot sales products with the user heat degrees in the second target number from the multiple user preference products according to the descending order.
In a possible implementation manner, the pushing module is further configured to screen out a target information template corresponding to each hot-sold product from correspondence between multiple product categories and multiple information templates according to a product category to which each target hot-sold product belongs; and generating push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sending the push information to each target user in the target user set.
In another aspect, a computer device is provided, and the computer device includes a processor and a memory, where the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the operation performed by the information pushing method as described above.
In another aspect, a computer-readable storage medium is provided, where at least one instruction is stored, and the instruction is loaded and executed by a processor to implement the operation performed by the information push method as described above.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
determining a preferred product of each target user based on historical consumption records; and further determining a target hot sales product from a plurality of user preference products of a plurality of target users, sending pushing information of the target hot sales product to a target user set, and pushing group hot sales products in a group of the target user set, so that the information pushing efficiency and accuracy are improved, and the conversion rate of the pushed products into effective products in the group is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of an implementation environment of an information pushing method according to an embodiment of the present invention;
fig. 2 is a flowchart of an information pushing method according to an embodiment of the present invention;
fig. 3 is a flowchart of an information pushing method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of user screening according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of preferred product screening provided by an embodiment of the present invention;
FIG. 6 is a schematic diagram of a target hot-sell product screening provided by an embodiment of the invention;
FIG. 7 is a schematic diagram of a document generation process according to an embodiment of the present invention;
fig. 8 is a flowchart of an information pushing process provided by an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an information pushing apparatus according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an implementation environment of an information pushing method according to an embodiment of the present invention, as shown in fig. 1, the implementation environment includes a server 101 and a terminal 102, the number of the terminal 102 may be one or more, the server 101 may be a background server of an e-commerce platform, the e-commerce platform may be installed on the terminal 102, and the server 101 and the terminal 102 may establish a communication connection based on the e-commerce platform.
In one possible implementation environment, a plurality of products are provided on the e-commerce platform, and a user can purchase any one of the products on the e-commerce platform on the terminal 102 according to the demand, and the consumption demand of the user is realized between the terminal 102 and the server 101 based on the communication connection.
Based on the implementation environment, the server 101 may further store the historical consumption records of the users, determine the hot-selling products in the user group based on the historical consumption records of each user in the user group, and push the hot-selling products to the user group in real time, so as to promote the purchasing behavior of the users and further achieve the purpose of stimulating consumption.
The following describes a plurality of terms related to embodiments of the present invention:
e, E-commerce platform: the system is a network platform for providing product transaction for users, the e-commerce platform can provide full-grade product transaction, and can also provide a transaction platform mainly for a certain large class of products, for example, the e-commerce platform can provide fresh products for users, such as fruit and vegetable, seafood, meat and poultry, milk and snack, and the like; alternatively, the e-commerce platform may be a clothing e-commerce platform or a book e-commerce platform. The e-commerce platform can also push information of related products to the user, for example, push information carrying product selling prices, product consumption links and the like, so as to prompt the consumption behavior of the user on the e-commerce platform. The Push information may be a Push message, and the type of information carried by the Push message may include, but is not limited to, text, pictures, or video.
User preference product: in the embodiment of the invention, the products preferred by the user are determined based on the historical consumption records of the user.
User heat: the user popularity is used for indicating the popularity of the user preference product in the target user set, and the higher the user popularity is, the higher the popularity of the target user to the product is.
It should be noted that the e-commerce platform may be in the form of a separate application or a program plug-in configured in an application, for example, a separate e-commerce application may be installed on the terminal 102, or a plug-in applet of the e-commerce platform may be installed on another separate application. Types of terminals 102 include, but are not limited to: mobile terminals and fixed terminals. As an example, mobile terminals include, but are not limited to: smart phones, tablet computers, notebook computers, e-readers, and the like; the fixed terminal includes, but is not limited to, a desktop computer, and the embodiment of the present invention is not limited thereto. Exemplarily, fig. 1 is only illustrated by taking the terminal 102 as a smart phone. The server 101 may be an independent server, or may be a server cluster composed of a plurality of servers, which is also not specifically limited in this embodiment of the present invention.
Fig. 2 is a flowchart of an information pushing method according to an embodiment of the present invention. The execution subject of the embodiment of the present invention is a computer device, for example, the computer device may be a server. Referring to fig. 2, the method includes:
201. receiving a target pushing instruction, wherein the target pushing instruction is used for indicating that a hot-selling product is pushed to a target user set;
202. determining a user preference product of each target user according to the historical consumption record of each target user in the target user set;
203. determining a user popularity of each user preference product based on a plurality of user preference products of a plurality of target users, the user popularity being used for indicating the degree of the user preference product being liked in the target user set;
204. and screening target hot sales products from the multiple user preference products according to the user heat of each user preference product, generating push information of the target hot sales products, and sending the push information to each target user in the target user set.
In one possible implementation, the determining the user popularity for each user preference product based on a plurality of user preference products for a plurality of target users comprises any one of:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users in the target user set who trade the user preference product;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of the transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
In one possible implementation, the determining the user preference product of each target user in the set of target users according to the historical consumption record of each target user comprises:
according to the historical consumption record of each target user in the target user set, counting the historical transaction times of each product of the historical transaction of each target user;
and according to the historical transaction times of each product, the multiple products of each target user are arranged in a descending order, and multiple user preference products with the historical transaction times at the previous first target number are screened out from the multiple products.
In one possible implementation, the counting the historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the set of target users comprises:
for each target user, screening a plurality of target consumption records of which the historical transaction environmental states are matched with the environmental states from the historical consumption records of the target user according to the corresponding environmental states at the target time, wherein the target time is the time for pushing the pushing information;
according to a plurality of target consumption records of the target user, counting the historical transaction times of each product of the historical transaction of the target user;
wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time.
In one possible implementation, the screening the target hot-sell products from the plurality of user-preferred products according to the user-popularity of each of the user-preferred products comprises:
according to the user heat of various user preference products, performing descending order arrangement on the various user preference products;
and screening out target hot sales products with the user heat degrees in the second target number from the multiple user preference products according to the descending order.
In one possible implementation, the generating push information for the target hot-sell product, the sending the push information to each target user in the set of target users includes:
screening out a target information template corresponding to each hot-sold product from the corresponding relation between the plurality of product categories and the plurality of information templates according to the product category to which each target hot-sold product belongs;
and generating push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sending the push information to each target user in the target user set.
In the embodiment of the invention, the preferred product of each target user is determined based on the historical consumption record; and further determining a target hot sales product from a plurality of user preference products of a plurality of target users, sending pushing information of the target hot sales product to a target user set, and pushing group hot sales products in a group of the target user set, so that the information pushing efficiency and accuracy are improved, and the conversion rate of the pushed products into effective products in the group is improved.
Fig. 3 is a flowchart of an information pushing method according to an embodiment of the present invention. The execution subject of the embodiment of the invention is a computer device, and the computer device may be any electronic device, for example, the computer device may be a server. Referring to fig. 3, the method includes:
301. the computer device receives a target push instruction.
Wherein the target push instruction is used for instructing to push the hot sales product to the target user set. The set of target users includes a plurality of target users. In this step, the computer device may screen out the target user set from the mass of the e-commerce platform based on the target push instruction, and the process may include: the computer device has preliminarily screened a plurality of users to be pushed from massive users of the e-commerce platform, and further, the computer device can screen a plurality of target users corresponding to a plurality of target devices of which the device notification states are allowed to notify push information from the plurality of users according to the device notification states of each user in the user set to obtain the target user set, wherein the device notification states refer to states of whether the device is allowed to notify the push information of the e-commerce platform. For example, the computer device may filter out the set of target users from a large number of users geographically located in the north China area. The device information may include a message notification status of the device, that is, whether the device allows notification of push information to a user, and the computer device may use a user corresponding to a device that starts a push information notification function as a target user of information to be pushed.
In one possible example, the user may also change the device used for logging in to the e-commerce platform, for example, when the user purchases a new mobile phone, the user may change to the e-commerce platform logged in to the new mobile phone. The device information may also include a latest mapping relationship between the device and the user, further locating the latest device of the user. As shown in fig. 4, the process may include: the computer equipment obtains a mapping relation between users and equipment, searches equipment corresponding to each user from the mapping relation, screens out a plurality of effective users of which the current use states of the corresponding equipment are available from the plurality of users according to the equipment corresponding to each user, and the terminal can screen out a plurality of target users corresponding to a plurality of target equipment which allow to inform information push from the plurality of effective users to obtain the target user set. The computer device may determine whether the current device usage status of the device is available according to one or more device statuses of each device. In one possible example, the computer device may log in to the device corresponding to the user according to the latest login time of the device corresponding to the user, the login times of the device corresponding to the login of the user in the target time period, and the like. For example, the computer device may determine that the current usage state of the device is unavailable when the user logs into the corresponding device no more than a target number of times within a target time period. Alternatively, the computer device may determine that the current usage state of the first device is unavailable and the current usage state of the second device is available when the number of times the user logs in to the first device in the target time period does not exceed the target number of times and the number of times the user logs in to the second device exceeds the target number of times. For example, if the number of times that the user records the device a in the last three months is not more than 1, and the number of times that the user records the device B in the last three months is 28, the state of the device a is determined to be unavailable, and the state of the device B is determined to be available, then the device B is an effective device; and when the computer equipment further judges that the notification of pushing information is started on the B equipment, determining that the user corresponding to the B equipment is a target user.
302. The computer device determines a user-preferred product for each target user in the set of target users based on the historical consumption record for each target user.
In the embodiment of the invention, the computer equipment can collect and count the historical consumption records of each target user and select the preferred products of the target users according to the historical consumption conditions. In one possible embodiment, the step may comprise: the computer equipment counts the historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the target user set; the computer device is used for sorting the plurality of products of each target user in a descending order according to the historical transaction times of each product, and screening out a plurality of user preference products with the historical transaction times at the previous first target quantity from the plurality of products. As shown in fig. 5, for each target user, the computer device may first obtain a historical consumption record matched with each target user, and count the number of purchases of multiple products historically purchased by the target user, that is, the number of historical transactions, based on the historical consumption record matched with the target user, the computer device may perform descending order arrangement on the multiple products according to the historical number of transactions of each product, and the computer device may screen the first target number of products from the multiple products in the descending order arrangement as a preferred product of the target user. For example, the computer device may find the target user in the descending order product.
In one possible implementation, the computer device may also integrate into consideration the preferred products of each target user in connection with environmental conditions such as season, weather, etc. Step 302 may include: for each target user, the computer device screens out a plurality of target consumption records of which the historical transaction environmental states are matched with the environmental states from the historical consumption records of the target user according to the environmental states corresponding to the target time, wherein the target time is the time for pushing the pushing information; the computer equipment counts the historical transaction times of each product of the historical transaction of the target user according to a plurality of target consumption records of the target user; wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time. The computer device may determine that the historical transaction environmental state matches the environmental state when the historical transaction environmental state is the same as the environmental state or an environmental parameter difference between the historical transaction environmental state and the environmental state is within a threshold range. In one particular example, a match is determined if the local current weather and the trade time weather are both cloudy; alternatively, a match may be determined where the current ambient temperature is 30 ℃ and the ambient temperature at the time of the transaction is in the range of 30 ℃ to 25 ℃. In one possible example, the computer device may determine the preferred product of the user at summer time from consumption records of the plurality of users at summer time based on the season in which the current time is in summer. Or the computer equipment can also find out the preference product of the user from the consumption records of the multiple users in the previous cloudy haze weather period according to the current cloudy haze weather.
303. The computer device determines a user popularity for each user-preferred product based on a plurality of user-preferred products for a plurality of target users.
The user popularity is used to indicate how well the user prefers products to be liked in the target set of users. The computer device may use the number of transactions and/or the product transaction amount for each user preference product to determine the user popularity. Accordingly, the present step may include the following three implementations.
In the first mode, the computer device counts the number of transaction users of each user preference product, and determines the number of the transaction users as the user popularity of each user preference product.
The number of the transaction users trading the user preference product refers to the number of the target users trading the user preference product in the target user set. In this step, the computer device determines the user preference product of each target user in sequence, and then obtains a plurality of user preference products of the plurality of target users. For each user preference product, the computer device may count a number of users of the plurality of target users who have historically transacted the user preference product. For example, the user preference products of the user a include a product a, a product B and a product C, the user preference products of the user B include a product a, a product C and a product D, and the user preference products of the user C include a product a, a product E and a product F, so that the number of transaction users of the product a is 3, including the user a, the user B and the user C.
In the second mode, the computer device counts the product transaction amount of each user preference product, and determines the product transaction amount as the user popularity of each user preference product.
In this step, the computer device may obtain, for each user preference product, a product transaction amount for each target user when historically trading the user preference product, and accumulate the product transaction amounts for a plurality of historically traded user preference products to obtain a product transaction amount for each user preference product.
For example, the user-preferred products of user A include product A, product B, and product C, wherein the transaction amount of product A is 10, and the user-preferred products of user B include product A, product C, and product D, wherein the transaction amounts of product A are 15, respectively, and the transaction amount of product A is 25.
And in the third mode, the computer equipment counts the number of transaction users and the product transaction amount of each kind of user preference product, and determines the user popularity of each kind of user preference product according to the number of transaction users and the product transaction amount.
In this step, the computer device may count the number of transaction users and the transaction amount of products of each user preferred product according to the first manner and the second manner, the computer device may determine a first popularity score of each user preferred product according to the number of transaction users, and determine a second popularity score of each user preferred product according to the transaction amount of products, and the computer device determines the target popularity score of each user preferred product according to the first popularity score and the second popularity score. In one possible example, the computer device may further obtain a first weight of the number of transaction users and a second weight of the product transaction amount, calculate a first product of the first weight and the first popularity score and a second product of the second weight and the second popularity score, respectively, and determine a sum of the first product and the second product as the target popularity score.
304. And the computer equipment screens out target hot sales products from the multiple user preference products according to the user heat of each user preference product, generates push information of the target hot sales products, and sends the push information to each target user in the target user set.
In this step, the computer device screens out the group hot-selling products preferred by the group of the target user set, namely the target hot-selling products according to the user popularity, so that information pushing of the group hot-selling products is realized, and the conversion rate of effectively pushing information is promoted.
In one possible embodiment, the step may comprise: the computer equipment performs descending order arrangement on the various user preference products according to the user heat of the various user preference products; the computer device screens out a target hot-selling product with the user heat degree positioned at the front second target quantity from the plurality of user preference products according to the arrangement sequence of descending order. As shown in fig. 6, the computer device counts the user heat of each product, sorts the products based on the counted user heat, and selects the products in reverse order according to the number, that is, selects the second target number of target hot-sell products located before in the descending order after the products are sorted in descending order, and outputs the selected target hot-sell products.
In one possible implementation, the computer device may first filter out the target template information of each template hot-sell product, and generate corresponding push information for pushing based on the target template information of each hot-sell product. The process may include: the computer equipment screens out a target information template corresponding to each hot-sold product from the corresponding relation between a plurality of product categories and a plurality of information templates according to the product category to which each target hot-sold product belongs; the computer equipment generates push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sends the push information to each target user in the target user set. The product category may be set based on needs, which is not specifically limited in the embodiment of the present invention, for example, the apple, the peach, the orange, and the like belong to a fruit category, and the cup, the toothbrush, and the like belong to a daily article category. In a specific example, the product information may include a product identifier and a selling price, and the computer device obtains the selling price of each target hot-sold product according to the product identifier of each target hot-sold product; the computer equipment correspondingly adds the product identification and the selling price of each target hot-selling product into the corresponding target information template, generates the push information of the target hot-selling product and sends the push information to the target user set. For example, as shown in fig. 7, the computer device adds the product identifier and the selling price of the target hot-sold product to be pushed to the selected file template in a file filling manner to obtain a complete file, and pushes the complete file to each target user, thereby implementing an information pushing process based on the hot-sold product.
It should be noted that, the computer device further filters the group hot-sales products preferred by the group, and pushes the related information of the group hot-sales products to the target user set, so as to improve the purchase rate of the pushed products in the target user set, thereby improving the conversion rate of the pushed product information into the effective information in the target user set as much as possible.
In the embodiment of the present invention, in order to describe the specific process of the embodiment of the present invention more clearly, the above steps 301 and 304 are further described with reference to the process shown in fig. 8. As shown in fig. 8, when the computer device receives the target pushing instruction, the computer device initially filters out a user set, and then filters out a target user set through a user filter, based on the historical consumption records of the target users, matches out the commodities historically purchased by each target user, further counts out the preferred products of each target user, and pools a plurality of preferred products of a plurality of target users, so as to further sort out the target hot-selling products with the user heat degree in the second target number before based on the user preference number of the plurality of preferred products, thereby generating the file of the target hot-selling products to push to the target users.
In the embodiment of the invention, the preferred product of each target user is determined based on the historical consumption record; and further determining a target hot sales product from a plurality of user preference products of a plurality of target users, sending pushing information of the target hot sales product to a target user set, and pushing group hot sales products in a group of the target user set, so that the information pushing efficiency and accuracy are improved, and the conversion rate of the pushed products into effective products in the group is improved.
Fig. 9 is a schematic structural diagram of an information pushing apparatus according to an embodiment of the present invention. Referring to fig. 9, the apparatus includes:
a receiving module 901, configured to receive a target push instruction, where the target push instruction is used to instruct to push a hot-sold product to a target user set;
a determining module 902, configured to determine a user preference product of each target user in the set of target users according to the historical consumption record of each target user;
the determining module 902 is further configured to determine a user popularity of each user preference product based on a plurality of user preference products of a plurality of target users, the user popularity being used for indicating a degree of likeness of the user preference product in the set of target users;
the pushing module 903 is configured to filter out a target hot-selling product from the multiple user-preferred products according to the user popularity of each user-preferred product, generate pushing information of the target hot-selling product, and send the pushing information to each target user in the target user set.
In a possible implementation, the determining module 902 is further configured to:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users in the target user set who trade the user preference product;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of the transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
In a possible implementation manner, the determining module 902 is further configured to count the historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the set of target users; and according to the historical transaction times of each product, the multiple products of each target user are arranged in a descending order, and multiple user preference products with the historical transaction times at the previous first target number are screened out from the multiple products.
In a possible implementation manner, the determining module 902 is further configured to, for each target user, screen, according to an environment state corresponding to a target time, a plurality of target consumption records of which historical transaction environment states are matched with the environment states from historical consumption records of the target user, where the target time is a time to push the push information; according to a plurality of target consumption records of the target user, counting the historical transaction times of each product of the historical transaction of the target user;
wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time.
In a possible implementation manner, the pushing module 903 is further configured to perform descending order arrangement on multiple user-preferred products according to the user popularity of the multiple user-preferred products; and screening out target hot sales products with the user heat degrees in the second target number from the multiple user preference products according to the descending order.
In a possible implementation manner, the pushing module 903 is further configured to screen out a target information template corresponding to each hot-sold product from correspondence relationships between multiple product categories and multiple information templates according to a product category to which each target hot-sold product belongs; and generating push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sending the push information to each target user in the target user set.
In the embodiment of the invention, the preferred product of each target user is determined based on the historical consumption record; and further determining a target hot sales product from a plurality of user preference products of a plurality of target users, sending pushing information of the target hot sales product to a target user set, and pushing group hot sales products in a group of the target user set, so that the information pushing efficiency and accuracy are improved, and the conversion rate of the pushed products into effective products in the group is improved.
All the above optional technical solutions may be combined arbitrarily to form the optional embodiments of the present disclosure, and are not described herein again.
It should be noted that: in the information pushing apparatus provided in the foregoing embodiment, only the division of the function modules is illustrated in the foregoing, and in practical applications, the function distribution may be completed by different function modules according to needs, that is, the internal structure of the computer device is divided into different function modules to complete all or part of the functions described above. In addition, the information pushing apparatus and the information pushing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.
Fig. 10 is a schematic structural diagram of a server according to an embodiment of the present invention, where the server 1000 may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 1001 and one or more memories 1002, where the memory 1002 stores at least one instruction, and the at least one instruction is loaded and executed by the processors 1001 to implement the information pushing method provided by each method embodiment. Of course, the server may also have components such as a wired or wireless network interface, a keyboard, and an input/output interface, so as to perform input/output, and the server may also include other components for implementing the functions of the device, which are not described herein again.
In an exemplary embodiment, a computer-readable storage medium, such as a memory, including instructions executable by a processor in a terminal or a server to perform the information pushing method in the above embodiments is also provided. For example, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. An information pushing method, characterized in that the method comprises:
receiving a target pushing instruction, wherein the target pushing instruction is used for indicating that a hot-selling product is pushed to a target user set;
determining a user preference product of each target user according to the historical consumption record of each target user in the target user set;
determining a user popularity for each user preference product based on a plurality of user preference products for a plurality of target users, the user popularity being indicative of how much the user preference product is liked in the set of target users;
and screening target hot sales products from the multiple user preference products according to the user heat of each user preference product, generating push information of the target hot sales products, and sending the push information to each target user in the target user set.
2. The method of claim 1, wherein determining the user popularity for each user preferred product based on a plurality of user preferred products for a plurality of target users comprises any one of:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users who trade the user preference product in the target user set;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
3. The method of claim 1, wherein determining the user-preferred product for each target user in the set of target users based on the historical consumption record of each target user comprises:
according to the historical consumption record of each target user in the target user set, counting the historical transaction times of each product of the historical transaction of each target user;
and according to the historical transaction times of each product, the multiple products of each target user are arranged in a descending order, and multiple user preference products with the historical transaction times at the previous first target number are screened out from the multiple products.
4. The method of claim 3, wherein the counting the historical transaction times of each product of the historical transaction of each target user according to the historical consumption record of each target user in the target user set comprises:
for each target user, screening a plurality of target consumption records of which the historical transaction environmental states are matched with the environmental states from the historical consumption records of the target user according to the corresponding environmental states at the target time, wherein the target time is the time of pushing the pushing information;
according to the target consumption records of the target user, counting the historical transaction times of each product of the historical transaction of the target user;
wherein the environmental state includes at least one of a season in which the target time is located, weather at the target time, and air quality at the target time.
5. The method of claim 1, wherein said screening said plurality of user preferred products for a target hot-sell product based on said user's popularity of each of said user preferred products comprises:
according to the user heat of various user preference products, performing descending order arrangement on the various user preference products;
and screening out target hot sales products with the user heat degrees in the second target number from the multiple user preference products according to the descending order.
6. The method of claim 1, wherein generating push information for the target hot-sell product, sending the push information to each target user in the set of target users comprises:
screening out a target information template corresponding to each hot-sold product from the corresponding relation between the plurality of product categories and the plurality of information templates according to the product category to which each target hot-sold product belongs;
and generating push information corresponding to each hot-selling product according to the product information of each hot-selling product and the corresponding target information template, and sending the push information to each target user in the target user set.
7. An information pushing apparatus, characterized in that the apparatus comprises:
the receiving module is used for receiving a target pushing instruction, and the target pushing instruction is used for indicating that a hot-selling product is pushed to a target user set;
the determining module is used for determining a user preference product of each target user according to the historical consumption record of each target user in the target user set;
the determining module is further used for determining the user popularity of each user preference product based on a plurality of user preference products of a plurality of target users, and the user popularity is used for indicating the degree of the user preference products being favored in the target user set;
and the pushing module is used for screening target hot selling products from the various user preference products according to the user heat of each user preference product, generating pushing information of the target hot selling products, and sending the pushing information to each target user in the target user set.
8. The apparatus of claim 7, wherein the determining module is further configured to any one of:
counting the number of transaction users of each user preference product, determining the number of the transaction users as the user popularity of each user preference product, wherein the number of the transaction users of the user preference product refers to the number of target users who trade the user preference product in the target user set;
counting the product transaction amount of each user preference product, and determining the product transaction amount as the user popularity of each user preference product;
and counting the number of transaction users and the product transaction amount of each user preference product, and determining the user popularity of each user preference product according to the number of the transaction users and the product transaction amount.
9. A computer device, comprising a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the operation performed by the information pushing method according to any one of claims 1 to 6.
10. A computer-readable storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the operation performed by the information pushing method according to any one of claims 1 to 6.
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