CN109711917B - Information pushing method and device - Google Patents
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- CN109711917B CN109711917B CN201711021154.9A CN201711021154A CN109711917B CN 109711917 B CN109711917 B CN 109711917B CN 201711021154 A CN201711021154 A CN 201711021154A CN 109711917 B CN109711917 B CN 109711917B
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Abstract
The embodiment of the application discloses an information pushing method and device. One embodiment of the method comprises: acquiring a shop address set and a historical order set; generating a user identification set based on the historical order set; for each user identification in the user identification set, determining the residence address of the user indicated by the user identification based on the delivery address included in the historical order including the user identification in the historical order set; selecting user identifications in the user identification set based on the residence address to generate a first user identification set corresponding to each shop address; and generating selection recommendation information corresponding to the store address based on the first user identification set corresponding to the store address in the store address set and the item information included in the historical order set, and pushing the selection recommendation information to the terminal equipment of the user to which the store indicated by the store address belongs. The embodiment realizes targeted information push.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to the technical field of internet, and particularly relates to an information pushing method and device.
Background
With the rapid development of electronic commerce, more and more users are used to online consumption. But most life styles of users still occur on line, such as shopping, supermarket shopping and the like are also indispensable life styles under the subscriber line. In order to promote the development of off-line stores, how to combine the consumption data of on-line users to recommend the selection of off-line stores is a problem worthy of research.
Disclosure of Invention
The embodiment of the application aims to provide an information pushing method and device.
In a first aspect, an embodiment of the present application provides an information pushing method, where the method includes: the method comprises the steps of obtaining a shop address set and a historical order set, wherein the historical order comprises a user identification, a receiving address, an order placing time and article information; extracting user identifications from each historical order in the historical order set when the order is placed within a first preset time period, and generating a user identification set; for each user identifier in the user identifier set, determining a residence address of a user indicated by the user identifier based on a receiving address included in a history order including the user identifier in each history order; for each shop address in the shop address set, determining a target user identifier in the user identifier set to generate a first user identifier set corresponding to the shop address, wherein the distance between a place indicated by the residential address of the user indicated by the target user identifier and the shop indicated by the shop address is not greater than a first distance threshold value; and generating selection recommendation information corresponding to the shop address based on the first user identification set corresponding to the shop address in the shop address set and the article information included in the historical order set, and pushing the selection recommendation information to the terminal equipment of the user to which the shop indicated by the shop address belongs.
In some embodiments, the generating of the item recommendation information corresponding to the store address based on the first user identifier set corresponding to the store address in the store address set and the item information included in the historical order set includes: for each shop address in the shop address set, selecting a historical order which has a second preset time period at the order taking time and comprises a user identifier in a first user identifier set corresponding to the shop address from the historical order set, and generating a first historical order set corresponding to the shop address; and generating item recommendation information corresponding to the shop address based on the item information included in the historical order in the first historical order set corresponding to the shop address in the shop address set.
In some embodiments, the item information includes an item identification, an item identification corresponding to the item identification, and an item quantity corresponding to the item identification.
In some embodiments, the generating of the item recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set includes: for each store address in the store address set, extracting a category identifier from historical orders in a first historical order set corresponding to the store address, generating a category identifier set corresponding to the store address, counting the number of items under the category indicated by each category identifier in the category identifier set purchased by a user indicated by the user identifier in the first user identifier set corresponding to the store address in each unit time period in the second preset time period based on the first historical order set, and determining the number as the sales volume corresponding to the store address; merging the item identification sets corresponding to all the store addresses in the store address set to generate a first item identification set; determining, for each item identifier in the first set of item identifiers, whether a first targeted store address and a second targeted store address are present in the set of store addresses based on the sales volume of the item indicated by the item identifier corresponding to the store address in the set of store addresses, wherein a hot-sales time of the item in the item indicated by the item identifier in the first targeted store indicated by the first targeted store address has a hysteresis with respect to a hot-sales time of the second targeted store indicated by the second targeted store address; if yes, further determining information of a first preset number of articles with highest sales volume under the category indicated by the category identification sold by the second target store in a third preset time period, and classifying the information of the first preset number of articles into item selection recommendation information corresponding to the address of the first target store.
In some embodiments, the historical order further includes user attribute information and item attribute information; and generating item recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set, the item recommendation information including: for each store address in the store address set, analyzing a first historical order set corresponding to the store address, and determining at least one of the following items: and generating item recommendation information corresponding to the shop address and including at least one item selected from the information of the first second preset number of items with the largest purchased amount under different categories, the information of the first second preset number of items with the largest purchased amount under different user attributes, and the information of the first second preset number of items with the largest purchased amount under different item attributes.
In some embodiments, the above method further comprises: for each shop address in the shop address set, selecting a preset shop address of which the distance between the indicated shop and the shop indicated by the shop address is not more than a second distance threshold value from a preset shop address set, and generating a first preset shop address set corresponding to the shop address, wherein the preset shop address has a corresponding category identification set; for each store address in the store address set, determining whether the item recommendation information corresponding to the store address contains information of an item under the item indicated by the item identification in the item identification set corresponding to the preset store address in the first preset store address set corresponding to the store address; and if so, generating marking information corresponding to the shop address, and pushing the marking information to the terminal equipment of the user to which the shop indicated by the shop address belongs, wherein the marking information is used for indicating that the shop indicated by the shop address has a competitor under the category.
In some embodiments, the generated item recommendation information corresponding to the store address includes an item identification; and the above method further comprises: for each store address in the store address set, analyzing the historical orders in the first historical order set corresponding to the store address for the item identifier in the generated item recommendation information corresponding to the store address, determining at least one associated item identifier associated with the item identifier, and generating corresponding relation information corresponding to the item identifier and used for representing the corresponding relation between the item identifier and the associated item identifier; and pushing the corresponding relation information corresponding to the article identification in the item recommendation information corresponding to the shop address in the shop address set to the terminal equipment of the user to which the shop indicated by the shop address belongs.
In some embodiments, the analyzing the historical orders in the first historical order set corresponding to the store address to determine at least one associated item identifier associated with the item identifier includes: selecting a historical order including the item identifier from a first historical order set corresponding to the shop address, and generating a second historical order set corresponding to the shop address; and determining the associated item identifier based on the second historical order set by utilizing a preset association rule algorithm.
In some embodiments, the determining the residential address of the user indicated by the user identifier based on the shipping address included in the historical order including the user identifier in the historical orders includes: extracting a receiving address from the historical orders including the user identification in the historical orders to generate a receiving address set; for each delivery address in the delivery address set, counting the order placing times of a user indicated by the user identification for placing an order by using the delivery address in a unit time period in the first preset time period and the number of months from the unit time period to the month based on the historical orders which simultaneously comprise the user identification and the delivery address in each historical order; and selecting the delivery address from the delivery address set as the living address of the user indicated by the user identifier based on the number of orders and the number of months corresponding to each delivery address in the delivery address set.
In some embodiments, the selecting a delivery address from the delivery address set as the residential address of the user indicated by the user identifier based on the number of orders placed and the number of months corresponding to each delivery address in the delivery address set includes: for each shipping address in the set of shipping addresses, scoring the shipping address using the following formula:
wherein y represents a score obtained by scoring the shipping address; m represents the total number of each unit time period within the first preset time period, wherein the unit time periods are the unit time periods within which the user indicated by the user identification places the order by using the receiving address; i is a natural number in the interval [1, M ], and n represents the order placing times of the user indicated by the user identification for placing orders in the ith unit time period in each unit time period by using the delivery address; m represents the number of months from the month in the ith unit time period;
and selecting the delivery address with the highest score in the delivery address set as the residence address of the user indicated by the user identification.
In a second aspect, an embodiment of the present application provides an information pushing apparatus, where the apparatus includes: the system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is configured to acquire a shop address set and a historical order set, and the historical order comprises a user identifier, a receiving address, an order placing time and article information; the first generation unit is configured to extract a user identifier from each historical order in the historical order set when the order is placed within a first preset time period, and generate a user identifier set; a determining unit, configured to determine, for each user identifier in the user identifier set, a residential address of the user indicated by the user identifier based on a shipping address included in a history order including the user identifier in the history orders; a second generating unit configured to determine, for each store address in the store address set, a target user identifier in the user identifier set to generate a first user identifier set corresponding to the store address, wherein a distance between a place indicated by a residential address of a user indicated by the target user identifier and a store indicated by the store address is not greater than a first distance threshold; and a pushing unit configured to generate option recommendation information corresponding to the store address based on the first user identifier set corresponding to the store address in the store address set and the item information included in the history order set, and push the option recommendation information to a terminal device of a user to which the store indicated by the store address belongs.
In some embodiments, the pushing unit includes: the first generation subunit is configured to, for each store address in the store address set, select a historical order from the historical order set, the order taking time of which is within a second preset time period and which includes a user identifier in a first user identifier set corresponding to the store address, and generate a first historical order set corresponding to the store address; and a second generation subunit configured to generate item recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set.
In some embodiments, the item information includes an item identification, an item identification corresponding to the item identification, and an item quantity corresponding to the item identification.
In some embodiments, the second generating subunit is further configured to: for each store address in the store address set, extracting a category identifier from historical orders in a first historical order set corresponding to the store address, generating a category identifier set corresponding to the store address, counting the number of items under the category indicated by each category identifier in the category identifier set purchased by a user indicated by the user identifier in the first user identifier set corresponding to the store address in each unit time period in the second preset time period based on the first historical order set, and determining the number as the sales volume corresponding to the store address; merging the item identification sets corresponding to all the store addresses in the store address set to generate a first item identification set; determining, for each item identifier in the first set of item identifiers, whether a first targeted store address and a second targeted store address are present in the set of store addresses based on the sales volume of the item indicated by the item identifier corresponding to the store address in the set of store addresses, wherein a hot-sales time of the item in the item indicated by the item identifier in the first targeted store indicated by the first targeted store address has a hysteresis with respect to a hot-sales time of the second targeted store indicated by the second targeted store address; if yes, further determining information of a first preset number of articles with highest sales volume under the category indicated by the category identification sold by the second target store in a third preset time period, and classifying the information of the first preset number of articles into item selection recommendation information corresponding to the address of the first target store.
In some embodiments, the historical order further includes user attribute information and item attribute information; and the second generating subunit is further configured to: for each store address in the store address set, analyzing a first historical order set corresponding to the store address, and determining at least one of the following items: and generating item recommendation information corresponding to the shop address and including at least one item selected from the information of the first second preset number of items with the largest purchased amount under different categories, the information of the first second preset number of items with the largest purchased amount under different user attributes, and the information of the first second preset number of items with the largest purchased amount under different item attributes.
In some embodiments, the above apparatus further comprises: a third generating unit, configured to select, for each store address in the store address set, a preset store address in which a distance between the indicated store and the store indicated by the store address is not greater than a second distance threshold from a preset store address set, and generate a first preset store address set corresponding to the store address, where the preset store address has a corresponding category identifier set; the first pushing unit is configured to determine whether the item recommendation information corresponding to the store address contains information of an item in a category indicated by a category identifier in a category identifier set corresponding to a preset store address in a first preset store address set corresponding to the store address or not for each store address in the store address set; and if so, generating marking information corresponding to the shop address, and pushing the marking information to the terminal equipment of the user to which the shop indicated by the shop address belongs, wherein the marking information is used for indicating that the shop indicated by the shop address has a competitor under the category.
In some embodiments, the generated item recommendation information corresponding to the store address includes an item identification; and the above apparatus further comprises: a fourth generating unit, configured to, for each store address in the store address set, analyze, for an item identifier in the generated item recommendation information corresponding to the store address, historical orders in the first historical order set corresponding to the store address, determine at least one associated item identifier associated with the item identifier, and generate correspondence information corresponding to the item identifier and used for representing a correspondence between the item identifier and the associated item identifier; and a second pushing unit configured to push the correspondence information corresponding to the item identifier in the item recommendation information corresponding to the store address in the store address set to the terminal device of the user to which the store indicated by the store address belongs.
In some embodiments, the fourth generating unit is further configured to: selecting a historical order including the item identifier from a first historical order set corresponding to the shop address, and generating a second historical order set corresponding to the shop address; and determining the associated item identifier based on the second historical order set by utilizing a preset association rule algorithm.
In some embodiments, the determining unit includes: the third generation subunit is configured to extract a receiving address from the historical orders including the user identifier in each historical order, and generate a receiving address set; a counting subunit, configured to count, for each of the shipping addresses in the shipping address set, a number of orders to be placed by a user using the shipping address within a unit time period within the first preset time period and a number of months from the unit time period to the current month, where the number of orders is indicated by the user identifier, based on the historical orders that include the user identifier and the shipping address at the same time in the historical orders; and the selecting subunit is configured to select the receiving address from the receiving address set as the living address of the user indicated by the user identifier based on the number of orders and the number of months corresponding to each receiving address in the receiving address set.
In some embodiments, the selecting subunit is further configured to: for each shipping address in the set of shipping addresses, scoring the shipping address using the following formula:
wherein y represents a score obtained by scoring the shipping address; m represents the total number of each unit time period within the first preset time period, wherein the unit time periods are the unit time periods within which the user indicated by the user identification places the order by using the receiving address; i is a natural number in the interval [1, M ], and n represents the order placing times of the user indicated by the user identification for placing orders in the ith unit time period in each unit time period by using the delivery address; m represents the number of months from the month in the ith unit time period;
and selecting the delivery address with the highest score in the delivery address set as the residence address of the user indicated by the user identification.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; storage means for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described in any implementation manner of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
According to the information pushing method and device provided by the embodiment of the application, a shop address set and a historical order set are obtained, user identifications are extracted from historical orders in the historical order set when orders are placed within a first preset time period, a user identification set is generated, the living address of a user indicated by the user identification is determined based on a receiving address included in the historical orders including the user identifications in the user identification set in the historical orders, so that the user identifications are selected in the user identification set based on the determined living address, and a first user identification set corresponding to each shop address in the shop address set is generated. And finally, based on the first user identification set corresponding to the store address in the store address set and the item information included in the historical order set, generating the option recommendation information corresponding to the store address so as to push the option recommendation information to the terminal equipment of the user to which the store indicated by the store address belongs. Therefore, the acquired historical order set is effectively utilized, the first user identification set corresponding to the shop address in the shop address set is generated, the option recommendation information corresponding to the shop address is generated, and the targeted information pushing is realized.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of an information push method according to the present application;
FIG. 3 is a schematic diagram of an application scenario of an information push method according to the present application;
FIG. 4 is a flow diagram of yet another embodiment of an information push method according to the present application;
FIG. 5 is a schematic diagram of an embodiment of an information pushing device according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing an electronic device according to embodiments of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the information pushing method or information pushing apparatus of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as a web browser application, a shopping application, an instant messaging tool, and the like. The terminal apparatuses 101, 102, and 103 may be terminal apparatuses of users belonging to the entity store.
The terminal devices 101, 102, 103 may be various electronic devices including, but not limited to, smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server that provides various services, for example, analyzes and the like the acquired store address set and the history order set, and pushes a processing result (generated item recommendation information corresponding to the store address in the store address set) to a corresponding terminal device, for example, the terminal devices 101, 102, and 103.
It should be noted that the information pushing method provided in the embodiment of the present application is generally executed by the server 105, and accordingly, the information pushing apparatus is generally disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of an information push method according to the present application is shown. The process 200 of the information pushing method includes the following steps:
In this embodiment, the electronic device (for example, the server 105 shown in fig. 1) on which the information push method operates may acquire the store address set and the historical order set from a server connected to the electronic device in remote communication via a wired connection or a wireless connection. Of course, if the electronic device locally stores the store address set and the history order set in advance, the electronic device may locally acquire the store address set and the history order set.
The store address in the store address set may be an address of an actual store. The historical order set may be a set of orders generated by a group of online users while shopping in an electronic mall within a predetermined period of time (e.g., last 2 years, etc.). Here, the historical order may include, for example, user identification, shipping address, order placement time, item information, and the like. The user identifier may include characters such as numbers and/or letters. The item information may include information such as item name, number of items, and brand name, for example.
Optionally, the item information may include an item identifier, an item identifier corresponding to the item identifier, and an item quantity corresponding to the item identifier. Here, the item identification may be, for example, the number of the item indicated by the item identification. The item identification may be, for example, a SKU (Stock Keeping Unit) code of the item indicated by the item identification.
In this embodiment, the electronic device may extract a user identifier from each historical order in the historical order set when the order placing time is within a first preset time period (for example, last 1 year), and generate a user identifier set. Wherein, each user identifier in the user identifier set may be different from each other.
In this embodiment, for each user identifier in the user identifier set, the electronic device may determine, based on a shipping address included in a history order including the user identifier in the history orders, a residence address of the user indicated by the user identifier. As an example, the electronic device may first find each receiving address from a historical order including the user identifier in the historical orders, count the number of times that each receiving address appears in the historical order, and determine the receiving address with the largest number of occurrences as the residential address of the user indicated by the user identifier.
In some optional implementations of this embodiment, the electronic device may determine the residential address of the user indicated by the user identifier by performing the following steps: extracting a receiving address from the historical orders including the user identification in the historical orders to generate a receiving address set; for each delivery address in the delivery address set, counting the number of orders placed by a user using the delivery address within a unit time period (the duration of the unit time period may be 1 month) within the first preset time period and the number of months from the unit time period to the month, where the number of orders is indicated by the user identification, based on the historical orders which include the user identification and the delivery address at the same time in the historical orders; and selecting the delivery address in the delivery address set as the living address of the user indicated by the user identification based on the order placing times and the month number corresponding to each delivery address in the delivery address set.
For example, the electronic device may compare minimum months corresponding to each of the shipping addresses in the shipping address set, and if the minimum months corresponding to the same are the same, the electronic device may further compare the number of orders placed corresponding to the minimum months corresponding to each of the shipping addresses, and determine the shipping address corresponding to the maximum number of orders placed as the residence address of the user indicated by the user identifier. For example, the set of shipping addresses includes shipping address A and shipping address B; the initial month of the first preset time period is 10 months in 2016, and the end month is 9 months in 2017; this month is 2017, month 10. If the user indicated by the user id places an order twice in 6 months of 2017 using the shipping address a, the number of times of placing an order is 2, and the number of months from this month is 4. If the user places an order 5 times in the 6 th month of 2017 using the shipping address B, the number of orders is 5, and the number of months from this month is 4. The electronic device may determine that the minimum number of months corresponding to the receiving address a and the receiving address B are the same, that is, both are 4. The electronic device may further compare the order placing times of 3 with the order placing times of 5, and may determine that 5 is greater than 3, so the electronic device may determine the shipping address B as the residence address of the user.
In some optional implementations of this embodiment, the electronic device may select, based on the number of orders and the number of months that each delivery address in the delivery address set corresponds to, a delivery address in the delivery address set as a living address of the user indicated by the user identifier by performing the following steps:
first, for each shipping address in the set of shipping addresses, the electronic device may score the shipping address using the following formula:
wherein y may represent a score obtained by scoring the shipping address; m may represent the total number of each unit time period within the first preset time period, in which the user indicated by the user identifier has placed an order using the shipping address; i can be a natural number in the interval [1, M ], and n can represent the order placing times of the user indicated by the user identification for placing orders in the ith unit time period in each unit time period by using the receiving address; m may represent the number of months from the month for the ith unit time period.
Then, the electronic device may select the delivery address with the highest score in the delivery address set as the residence address of the user indicated by the user identifier.
In this embodiment, for each store address in the store address set, the electronic device may determine a target user identifier in the user identifier set to generate a first user identifier set corresponding to the store address. Wherein the distance between the place indicated by the residence address of the user indicated by the target user identification and the shop indicated by the shop address is not more than a first distance threshold (for example, 5, the unit may be kilometers). It should be noted that the first distance threshold may be adjusted according to actual needs, and this embodiment does not limit this aspect at all.
It should be noted that the electronic device may map the store address to longitude and latitude coordinates, and map the residence address of the user indicated by each user identifier in the user identifier set to longitude and latitude coordinates. For each user identifier in the user identifier set, the electronic device may calculate a distance between a location indicated by the residence address and a store indicated by the store address by using the longitude and latitude coordinates obtained by mapping the store address and the longitude and latitude coordinates obtained by mapping the residence address of the user indicated by the user identifier, and compare the distance with the first distance threshold value to determine whether the user identifier is a target user identifier.
In this embodiment, the electronic device may generate option recommendation information corresponding to the store address based on the first user identifier set corresponding to the store address in the store address set and item information included in the history order set, and push the option recommendation information to the terminal device of the user to which the store indicated by the store address belongs.
As an example, for each store address, the electronic device may count the purchased amount of each item in different categories based on the history order in the history order set including the user identifier in the first user identifier set corresponding to the store address, and classify the following information of the item with the largest purchased amount in different categories into the item recommendation information corresponding to the store address: item name, brand name, category name of the category to which it belongs.
In some optional implementation manners of this embodiment, for each store address in the store address set, the electronic device may select, from the history order set, a history order that has an order release time in a second preset time period (for example, a last half year or a last 2 years), and includes a user identifier in a first user identifier set corresponding to the store address, and generate a first history order set corresponding to the store address. The electronic device may generate item recommendation information corresponding to a store address based on item information included in a history order in a first history order set corresponding to the store address in the store address set.
Here, the historical order may also include user attribute information and item attribute information. For each store address in the set of store addresses, the electronic device may analyze a first historical order set corresponding to the store address to determine at least one of: and generating item recommendation information corresponding to the shop address and including the at least one item, wherein the item recommendation information includes information of a first second preset number of items with the largest purchased amount under different categories, information of a first second preset number of items with the largest purchased amount under different user attributes, and information of a first second preset number of items with the largest purchased amount under different item attributes. Here, the second preset number may be adjusted according to actual needs, and this embodiment does not limit this aspect at all.
The user attributes may include, for example, the user's age, gender, occupation, academic calendar, and the like. The item attribute may be a basic attribute of the item, such as a price interval in which the price of the item is located, a place of origin, a time to market, and the like. Here, the determined information of the item may include, for example, an item identifier and corresponding dimension information (e.g., an item identifier or an attribute identifier, which may include an attribute identifier of a user attribute or an item attribute) of the item. Taking the information of the first second preset number of items with the largest purchased amount under different item attributes as an example, if the first second preset number of items with the largest purchased amount under the price interval attribute include the item a, the determined information of the item a may include an item identifier of the item a and an attribute identifier of the price interval attribute (for example, an attribute name of the price interval attribute).
It should be noted that, the information of the articles with large purchased quantities determined in different dimensions is used to generate item recommendation information, and the item recommendation information is pushed, so that the user who acquires the item recommendation information can select the items according to actual needs. For example, in the section of thirty-eight women, the user can select a product according to the product recommendation information with women as the dimension and perform corresponding marketing activities.
In some optional implementation manners of the embodiment, for each store address in the store address set, the electronic device may select a preset store address, in a preset store address set, where a distance between the indicated store and the store indicated by the store address is not greater than a second distance threshold (for example, 5, a unit may be kilometer), and generate a first preset store address set corresponding to the store address. The preset store address may be an address of a physical store, and the preset store address may have a corresponding item identification set. For each store address in the store address set, the electronic equipment can determine whether the item recommendation information corresponding to the store address contains information of an item under the item indicated by the item identification in the item identification set corresponding to the preset store address in the first preset store address set corresponding to the store address; if so, the electronic equipment can generate marking information corresponding to the shop address and push the marking information to the terminal equipment of the user to which the shop indicated by the shop address belongs. The label information can be used to indicate that the store indicated by the store address has a competitor under the category.
Optionally, the electronic device may determine whether the item recommendation information includes information of an item in the category indicated by the category identifier by searching whether the item recommendation information corresponding to the store address includes the category identifier in a category identifier set corresponding to a preset store address in a first preset store address set corresponding to the store address.
It should be noted that the second distance threshold may be the same as or different from the first distance threshold. The second distance threshold may be adjusted according to actual needs, and this embodiment does not limit this aspect at all.
The user receiving the label information generated by the electronic device may determine, according to the label information, which categories the user's shop is in a competitive relationship with other shops, and further, the user may take some preferential measures and the like for the items under the categories, so as to increase the sales volume of the items under the categories, and further, promote the development of the shops.
In some optional implementation manners of this embodiment, the item recommendation information generated by the electronic device may include an item identifier. For each store address in the store address set, for the item identifier in the generated item recommendation information corresponding to the store address, the electronic device may analyze the historical orders in the first historical order set corresponding to the store address, determine at least one associated item identifier associated with the item identifier, and generate correspondence information corresponding to the item identifier and used for representing a correspondence between the item identifier and the associated item identifier. Then, the electronic device may push the correspondence information corresponding to the item identifier in the item recommendation information corresponding to the store address in the store address set to the user terminal of the user to which the store indicated by the store address belongs. Thus, after obtaining the corresponding relation information, the user can determine which items have relevance, and further can perform binding marketing and the like on the items with relevance.
The analyzing the historical orders in the first historical order set corresponding to the store address to determine at least one associated item identifier associated with the item identifier may include: selecting a historical order including the item identifier from a first historical order set corresponding to the shop address, and generating a second historical order set corresponding to the shop address; and determining the associated item identifier associated with the item identifier based on the second historical order set by utilizing a preset association rule algorithm (such as an Apriori algorithm). The Apriori algorithm is an algorithm for mining a frequent item set of boolean association rules. The core of the method is a recursion algorithm based on a two-stage frequency set idea.
As an example, taking the item identifier as an identifier of an item to be processed, the electronic device may first extract an item identifier pair from the historical orders in the second historical order set, and generate an item identifier pair set. Wherein each item identification pair comprises the to-be-processed item identification and an item identification of an item that is purchased at the same time as the item indicated by the to-be-processed item identification. Then, the electronic device may calculate a support degree of each item identifier pair in the set of item identifier pairs, that is, a number of times that the item identifier pair appears in the historical orders in the second historical order set. Then, the electronic device may remove the item identifier pair with the support degree smaller than the preset support degree from the item identifier pair set to obtain the first item identifier pair. Next, the electronic device may calculate a confidence level of each item identification pair in the first set of item identification pairs, where the confidence level may be a ratio of the number of historical orders in the second set of historical orders that simultaneously include the item identification in the item identification pair to the total number of historical orders included in the second set of historical orders. Then, the electronic device may remove the item identification pair with the confidence coefficient smaller than the preset confidence coefficient from the first item identification pair set to obtain a second item identification pair set. Finally, the electronic device may extract an item identifier other than the to-be-processed item identifier from the item identifier pairs in the second item identifier pair set, and determine the extracted item identifier as the associated item identifier associated with the to-be-processed item identifier.
With continuing reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the information push method according to the present embodiment. In the application scenario of fig. 3, the server 301 may first obtain a store address set 302 and a historical order set 303 locally, where the store address set 302 includes a store address 3021 and a store address 3022, and the historical order includes a user identifier, a shipping address, a placing time, and item information. Then, the service 301 may extract the user identifier from each historical order in the historical order set 303 within the last 1 year of the order placement time, and generate the user identifier set 304. Then, for each user identifier in the user identifier set 304, the server 301 may determine the residential address of the user indicated by the user identifier based on the shipping address included in the historical order including the user identifier in the above historical orders, to obtain the residential address group 305. Then, for each store address in the store address set 302, the server 301 may select, from the user identification set 304, a user identification whose distance between the place indicated by the residence address of the indicated user and the store indicated by the store address is not greater than 50 kilometers, and generate a first user identification set corresponding to the store address, where the store address 3021 corresponds to the first user identification set 306, and the store address 3022 corresponds to the first user identification set 307. Finally, the server 301 may generate the option recommendation information 308 corresponding to the store address 3021 based on the item information included in the history order including the user identifier in the first user identifier set 306 in the history order set 303, and generate the option recommendation information 309 corresponding to the store address 3022 based on the item information included in the history order including the user identifier in the first user identifier set 307 in the history order set 303, push the option recommendation information 308 to the terminal device 310 of the user to which the store indicated by the store address 3021 belongs, and push the option recommendation information 309 to the terminal device 311 of the user to which the store indicated by the store address 3022 belongs.
The method provided by the embodiment of the application effectively utilizes the acquired historical order set, realizes generation of the first user identification set corresponding to the store address in the store address set and generation of the option recommendation information corresponding to the store address, and realizes targeted information push.
With further reference to fig. 4, a flow 400 of yet another embodiment of an information push method is shown. The process 400 of the information pushing method includes the following steps:
In this embodiment, after the electronic device (for example, the server 105 shown in fig. 1) on which the information push method operates generates the first set of user identifiers corresponding to each store address in the set of store addresses, the electronic device may select a historical order from the historical order set, the historical order having a placing time in a second preset time period (for example, last 2 years and the like) and including the user identifiers in the first set of user identifiers corresponding to the store address, and generate the first historical order set corresponding to the store address.
In this embodiment, the item information in the historical order may include a category identifier, an item identifier corresponding to the category identifier, and an item quantity corresponding to the item identifier. For each store address in the store address set, the electronic device may extract a category identifier from the history orders in the first history order set corresponding to the store address, and generate a category identifier set corresponding to the store address. And counting the number of the items under the category indicated by each category identifier in the category identifier set purchased by the user indicated by the user identifier in the first user identifier set corresponding to the store address in each unit time period (for example, every month) in the second preset time period based on the first historical order set, and determining the number as the sales amount corresponding to the store address. Namely, the number of the items under the category indicated by the category identifier purchased by the user indicated by the user identifier in the first user identifier set in the unit time period is determined as the sales volume of the store indicated by the store address to the items under the category indicated by the category identifier in the unit time period.
As an example, assuming that the length of the unit time period is 1 month, the set of item identifications includes an item identification a. For each month in the second preset time period, the electronic device may find, in the historical orders in the first historical order set whose ordering time is in the month, the item quantities respectively corresponding to the item identifiers corresponding to the item identifier a, and sum the found item quantities to obtain the total item quantity. The electronic device may determine the total quantity of the items as the quantity of the items in the category indicated by the category identifier a purchased by the user in the month indicated by the user identifiers in the first user identifier set. And the electronic equipment can determine the quantity of sales of the goods under the category indicated by the category identification A in the month of the shop indicated by the shop address.
In this embodiment, the electronic device may merge category identifier sets corresponding to respective store addresses in the store address set to generate a first category identifier set. Here, the individual category identifications in the first set of category identifications may be different from each other.
In this embodiment, for each item identifier in the first set of item identifiers, the electronic device may determine whether a first target store address and a second target store address exist in the set of store addresses based on the sales volume of the item indicated by the item identifier corresponding to the store address in the set of store addresses. And the hot sale time of the item under the category indicated by the category identification in the first target store indicated by the first target store address has hysteresis relative to the hot sale time of the second target store indicated by the second target store address.
As an example, the store address set includes a store address a and a store address B, and for any one item identifier C in the first item identifier set, it is assumed that the store address a corresponds to a time series [10, 20, 30, 100, 80, 70, 50], and each component in the time series may represent a sales volume of the item under the item indicated by the item identifier C in a unit time period within the second preset time period for the store indicated by the store address a. The store address B corresponds to a time series [0, 0, 5, 20, 40, 50, 45], and each component in the time series may represent the sales volume of the item under the item indicated by the item identifier C in a unit time period within the second preset time period by the store indicated by the store address B. As can be seen from the time series corresponding to the store address a, the items in the category indicated by the category identification C are in the hot-selling stage in the 4 th unit time period, because the sales volume 100 is higher than other sales volumes in the time series. As can be seen from the time series corresponding to the store address B, the item under the category indicated by the category identification C is in the hot-selling stage at the 6 th unit time period because the sales volume 50 is higher than the other sales volume values in the time series. Further, as can be seen from these two hot-selling stages, the hot-selling time of the item under the category indicated by the category label C in the store indicated by the store address B is later than the hot-selling time of the store indicated by the store address a. Therefore, the hot-selling time of the item indicated by the item identifier C in the store indicated by the store address B is delayed from the hot-selling time of the store indicated by the store address a. The electronic device may determine the store address B as a first targeted store address and the store address a as a second targeted store address.
In this embodiment, for each item identifier in the first item identifier set, in response to the electronic device determining that the first target store address and the second target store address related to the item identifier exist in the store address set, the electronic device may further determine information (e.g., item identifiers of items) of a first preset number of items with a highest sales volume under the item indicated by the item identifier, which is sold by the second target store indicated by the second target store address, laid over a third preset time period (e.g., last 2 months) and include the information in the item recommendation information corresponding to the first target store address. It should be noted that the first preset number may be adjusted according to actual needs, and this embodiment does not limit this aspect at all.
In step 410, the item recommendation information corresponding to the store address in the store address set is pushed to the terminal device of the user to which the store indicated by the store address belongs.
In this embodiment, after the electronic device has executed step 409, the electronic device may push the item recommendation information corresponding to the store address in the store address set to the terminal device of the user to which the store indicated by the store address belongs.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the information push method in the present embodiment highlights the step of expanding the method for determining the option recommendation information corresponding to the store address in the store address set (step 406 and 409). Thus, the scheme described in the embodiment can realize the generation of the item recommendation information for stores with lagged hot-selling time under certain categories. By pushing the item recommendation information to the store, it is possible to contribute to an increase in sales volume of the store under the item.
With further reference to fig. 5, as an implementation of the method shown in the above-mentioned figures, the present application provides an embodiment of an information pushing apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which can be applied in various electronic devices.
As shown in fig. 5, the information pushing apparatus 500 shown in this embodiment includes: an acquisition unit 501, a first generation unit 502, a determination unit 503, a second generation unit 504, and a push unit 505. The obtaining unit 501 is configured to obtain a store address set and a historical order set, where the historical order includes a user identifier, a receiving address, an order placing time, and item information; the first generating unit 502 is configured to extract a user identifier from each historical order in the historical order set when the order is placed within a first preset time period, and generate a user identifier set; the determining unit 503 is configured to, for each user identifier in the user identifier set, determine a residential address of the user indicated by the user identifier based on a shipping address included in a history order including the user identifier in the history orders; the second generating unit 504 is configured to, for each store address in the store address set, determine a target user identifier in the user identifier set to generate a first user identifier set corresponding to the store address, where a distance between a place indicated by a residential address of a user indicated by the target user identifier and a store indicated by the store address is not greater than a first distance threshold; the pushing unit 505 is configured to generate option recommendation information corresponding to the store address based on the first user identifier set corresponding to the store address in the store address set and item information included in the history order set, and push the option recommendation information to a terminal device of a user to which the store indicated by the store address belongs.
In the present embodiment, in the information push apparatus 500: the specific processing of the obtaining unit 501, the first generating unit 502, the determining unit 503, the second generating unit 504, and the pushing unit 505 and the technical effects thereof can refer to the related descriptions of step 201, step 202, step 203, step 204, and step 205 in the corresponding embodiment of fig. 2, respectively, and are not repeated herein.
In some optional implementations of this embodiment, the pushing unit 505 may include: a first generation subunit (not shown in the figure), configured to, for each store address in the store address set, select, from the historical order set, a historical order that has a second preset time period at a drop time and includes a user identifier in a first user identifier set corresponding to the store address, and generate a first historical order set corresponding to the store address; and a second generation subunit (not shown in the figure) configured to generate item recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set.
In some optional implementations of this embodiment, the item information may include an item identifier, an item identifier corresponding to the item identifier, and an item quantity corresponding to the item identifier.
In some optional implementations of this embodiment, the second generating subunit may be further configured to: for each store address in the store address set, extracting a category identifier from historical orders in a first historical order set corresponding to the store address, generating a category identifier set corresponding to the store address, counting the number of items under the category indicated by each category identifier in the category identifier set purchased by a user indicated by the user identifier in the first user identifier set corresponding to the store address in each unit time period in the second preset time period based on the first historical order set, and determining the number as the sales volume corresponding to the store address; merging the item identification sets corresponding to all the store addresses in the store address set to generate a first item identification set; determining, for each item identifier in the first set of item identifiers, whether a first targeted store address and a second targeted store address are present in the set of store addresses based on the sales volume of the item indicated by the item identifier corresponding to the store address in the set of store addresses, wherein a hot-sales time of the item in the item indicated by the item identifier in the first targeted store indicated by the first targeted store address has a hysteresis with respect to a hot-sales time of the second targeted store indicated by the second targeted store address; if yes, further determining information of a first preset number of articles with highest sales volume under the category indicated by the category identification sold by the second target store in a third preset time period, and classifying the information of the first preset number of articles into item selection recommendation information corresponding to the address of the first target store.
In some optional implementations of this embodiment, the historical order may further include user attribute information and item attribute information; and the second generating subunit may be further configured to: for each store address in the store address set, analyzing a first historical order set corresponding to the store address, and determining at least one of the following items: and generating item recommendation information corresponding to the shop address and including at least one item selected from the information of the first second preset number of items with the largest purchased amount under different categories, the information of the first second preset number of items with the largest purchased amount under different user attributes, and the information of the first second preset number of items with the largest purchased amount under different item attributes.
In some optional implementations of this embodiment, the apparatus 500 may further include: a third generating unit (not shown in the figures) configured to, for each store address in the store address set, select a preset store address, of which the distance between the indicated store and the store indicated by the store address is not greater than a second distance threshold value, from a preset store address set, and generate a first preset store address set corresponding to the store address, where the preset store address may have a corresponding category identifier set; a first pushing unit (not shown in the figure) configured to determine, for each store address in the store address set, whether the item recommendation information corresponding to the store address includes information of an item under a category indicated by a category identifier in a category identifier set corresponding to a preset store address in a first preset store address set corresponding to the store address; if so, generating marking information corresponding to the shop address, and pushing the marking information to the terminal equipment of the user to which the shop indicated by the shop address belongs, wherein the marking information can be used for indicating that the shop indicated by the shop address has a competitor under the category.
In some optional implementations of this embodiment, the generated item recommendation information corresponding to the store address may include an item identifier; and the apparatus 500 may further include: a fourth generating unit (not shown in the figures) configured to, for each store address in the store address set, analyze, for an item identifier in the generated item recommendation information corresponding to the store address, historical orders in the first historical order set corresponding to the store address, determine at least one associated item identifier associated with the item identifier, and generate correspondence information corresponding to the item identifier and used for representing a correspondence between the item identifier and the associated item identifier; and a second pushing unit (not shown in the figure) configured to push the correspondence information corresponding to the item identifier in the item recommendation information corresponding to the store address in the store address set to the terminal device of the user to which the store indicated by the store address belongs.
In some optional implementations of this embodiment, the fourth generating unit may be further configured to: selecting a historical order including the item identifier from a first historical order set corresponding to the shop address, and generating a second historical order set corresponding to the shop address; and determining the associated item identifier based on the second historical order set by utilizing a preset association rule algorithm.
In some optional implementation manners of this embodiment, the determining unit may include: a third generating subunit (not shown in the figure), configured to extract a receiving address from the historical orders including the user identifier in the above historical orders, and generate a receiving address set; a counting subunit (not shown in the figure), configured to count, for each of the shipping addresses in the shipping address set, based on the historical orders that include the user identifier and the shipping address at the same time in the respective historical orders, the number of orders that the user indicated by the user identifier places an order using the shipping address in a unit time period within the first preset time period, and the number of months from the unit time period to the month; and a selecting subunit (not shown in the figure) configured to select the receiving address in the receiving address set as the living address of the user indicated by the user identifier based on the number of orders and the number of months corresponding to each receiving address in the receiving address set.
In some optional implementation manners of this embodiment, the selecting subunit may be further configured to:
for each shipping address in the set of shipping addresses, scoring the shipping address using the following formula:
wherein y may represent a score obtained by scoring the shipping address; m may represent the total number of each unit time period within the first preset time period, in which the user indicated by the user identifier has placed an order using the shipping address; i may be a natural number within the interval [1, M ], and n may represent the order placing times of the user indicated by the user identifier for placing an order in the ith unit time period in each unit time period by using the receiving address; m may represent the number of months from the month of the ith unit time period;
and selecting the delivery address with the highest score in the delivery address set as the residence address of the user indicated by the user identification.
The device provided by the above embodiment of the application effectively utilizes the acquired historical order set, realizes generation of the first user identification set corresponding to the store address in the store address set and generation of the item recommendation information corresponding to the store address, and realizes targeted information push.
Referring now to FIG. 6, shown is a block diagram of a computer system 600 suitable for use in implementing the electronic device of an embodiment of the present application. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a first generation unit, a determination unit, a second generation unit, and a pushing unit. Where the names of these units do not in some cases constitute a limitation on the units themselves, for example, the acquisition unit may also be described as a "unit that acquires a set of store addresses and a set of historical orders".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to include: the method comprises the steps of obtaining a shop address set and a historical order set, wherein the historical order comprises a user identification, a receiving address, an order placing time and article information; extracting user identifications from each historical order in the historical order set when the order is placed within a first preset time period, and generating a user identification set; for each user identifier in the user identifier set, determining a residence address of a user indicated by the user identifier based on a receiving address included in a history order including the user identifier in each history order; for each shop address in the shop address set, determining a target user identifier in the user identifier set to generate a first user identifier set corresponding to the shop address, wherein the distance between a place indicated by the residential address of the user indicated by the target user identifier and the shop indicated by the shop address is not greater than a first distance threshold value; and generating selection recommendation information corresponding to the shop address based on the first user identification set corresponding to the shop address in the shop address set and the article information included in the historical order set, and pushing the selection recommendation information to the terminal equipment of the user to which the shop indicated by the shop address belongs.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (13)
1. An information pushing method, characterized in that the method comprises:
the method comprises the steps of obtaining a shop address set and a historical order set, wherein the historical order comprises a user identification, a receiving address, an order placing time and article information;
extracting user identifications from all historical orders in the historical order set, wherein the ordering time is within a first preset time period, and generating a user identification set;
for each user identifier in the user identifier set, determining the residence address of the user indicated by the user identifier based on the delivery address included in the historical order including the user identifier in the historical orders;
for each store address in the store address set, determining a target user identifier in the user identifier set to generate a first user identifier set corresponding to the store address, wherein the distance between a place indicated by the residence address of the user indicated by the target user identifier and the store indicated by the store address is not greater than a first distance threshold value;
generating option recommendation information corresponding to the store address based on a first user identification set corresponding to the store address in the store address set and item information included in a history order in the history order set, and pushing the option recommendation information to terminal equipment of a user to which the store indicated by the store address belongs;
the generating of the item selection recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set includes: for each store address in the store address set, analyzing a first historical order set corresponding to the store address, and determining at least one of the following items: and generating item recommendation information corresponding to the shop address and including the at least one item, wherein the item recommendation information includes information of a first second preset number of items with the largest purchased amount under different categories, information of a first second preset number of items with the largest purchased amount under different user attributes, and information of a first second preset number of items with the largest purchased amount under different item attributes.
2. The method of claim 1, wherein generating item recommendation information corresponding to a store address based on a first user identification set corresponding to the store address in the store address set and item information included in a historical order in the historical order set comprises:
for each shop address in the shop address set, selecting a historical order which has a second preset time period and comprises a user identifier in a first user identifier set corresponding to the shop address from the historical order set, and generating a first historical order set corresponding to the shop address;
and generating selection recommendation information corresponding to the shop address based on the article information included in the historical orders in the first historical order set corresponding to the shop address in the shop address set.
3. The method of claim 2, wherein the item information comprises an item identification, an item identification corresponding to the item identification, and an item quantity corresponding to the item identification.
4. The method according to claim 3, wherein the generating of the item recommendation information corresponding to the store address based on the item information included in the history order in the first history order set corresponding to the store address in the store address set comprises:
for each store address in the store address set, extracting a category identifier from historical orders in a first historical order set corresponding to the store address, generating a category identifier set corresponding to the store address, counting the number of items under the category indicated by each category identifier in the category identifier set purchased by a user indicated by the user identifier in the first user identifier set corresponding to the store address in each unit time period in the second preset time period based on the first historical order set, and determining the number as the sales volume corresponding to the store address;
merging the item identification sets corresponding to all the store addresses in the store address set to generate a first item identification set;
for each item identifier in the first item identifier set, determining whether a first target store address and a second target store address exist in the store address set or not based on the sales volume of the item indicated by the item identifier corresponding to the store address in the store address set, wherein the hot sales time of the item in the item indicated by the item identifier in the first target store address has hysteresis relative to the hot sales time of the second target store indicated by the second target store address; if yes, further determining information of a first preset number of articles with highest sales volume under the category indicated by the category identification sold by the second target store in a third preset time period, and classifying the information of the first preset number of articles into item selection recommendation information corresponding to the address of the first target store.
5. The method of claim 3, wherein the historical orders further comprise user attribute information and item attribute information.
6. The method according to one of claims 1 to 5, characterized in that the method further comprises:
for each shop address in the shop address set, selecting a preset shop address of which the distance between the indicated shop and the shop indicated by the shop address is not more than a second distance threshold value from a preset shop address set, and generating a first preset shop address set corresponding to the shop address, wherein the preset shop address has a corresponding category identification set;
for each store address in the store address set, determining whether the item recommendation information corresponding to the store address contains information of an item under the item indicated by the item identification in the item identification set corresponding to the preset store address in the first preset store address set corresponding to the store address; if so, generating marking information corresponding to the shop address, and pushing the marking information to the terminal equipment of the user to which the shop indicated by the shop address belongs, wherein the marking information is used for indicating that the shop indicated by the shop address has a competitor under the category.
7. The method according to any one of claims 2 to 5, wherein the generated item recommendation information corresponding to the store address includes an item identification; and
the method further comprises the following steps:
for each store address in the store address set, analyzing the historical orders in the first historical order set corresponding to the store address for the item identifier in the generated item recommendation information corresponding to the store address, determining at least one associated item identifier associated with the item identifier, and generating corresponding relation information corresponding to the item identifier and used for representing the corresponding relation between the item identifier and the associated item identifier;
and pushing the corresponding relation information corresponding to the article identification in the item recommendation information corresponding to the shop address in the shop address set to the terminal equipment of the user to which the shop indicated by the shop address belongs.
8. The method of claim 7, wherein analyzing the historical orders in the first historical order set corresponding to the store address to determine at least one associated item identifier associated with the item identifier comprises:
selecting a historical order including the item identifier from a first historical order set corresponding to the shop address, and generating a second historical order set corresponding to the shop address;
and determining the associated item identifier based on the second historical order set by utilizing a preset association rule algorithm.
9. The method of claim 1, wherein determining the residence address of the user indicated by the user identifier based on the shipping address included in the historical order including the user identifier in the historical orders comprises:
extracting a receiving address from the historical orders including the user identification in each historical order to generate a receiving address set;
for each delivery address in the delivery address set, counting the order placing times of a user indicated by the user identification for placing an order by using the delivery address in a unit time period in the first preset time period and the number of months from the unit time period to the month based on the historical orders which simultaneously comprise the user identification and the delivery address in each historical order;
and selecting the receiving address from the receiving address set as the living address of the user indicated by the user identifier based on the number of orders and the number of months corresponding to each receiving address in the receiving address set.
10. The method of claim 9, wherein selecting the shipping address from the set of shipping addresses as the residence address of the user indicated by the user identifier based on the number of orders placed and the number of months corresponding to each shipping address in the set of shipping addresses comprises:
for each shipping address in the set of shipping addresses, scoring the shipping address using the following formula:
wherein y represents a score obtained by scoring the shipping address; m represents the total number of each unit time period within the first preset time period, wherein the unit time periods are the unit time periods within which the user indicated by the user identification places the order by using the receiving address; i is a natural number in the interval [1, M ], and n represents the order placing times of the user indicated by the user identification in the ith unit time period in each unit time period by using the receiving address; m represents the number of months from the month of the ith unit time period;
and selecting the delivery address with the highest score in the delivery address set as the residence address of the user indicated by the user identification.
11. An information pushing apparatus, characterized in that the apparatus comprises:
the system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is configured to acquire a shop address set and a historical order set, and the historical order comprises a user identifier, a receiving address, an order placing time and article information;
the first generation unit is configured to extract a user identifier from each historical order in the historical order set when the order is placed within a first preset time period, and generate a user identifier set;
a determining unit, configured to determine, for each user identifier in the set of user identifiers, a residential address of the user indicated by the user identifier based on a shipping address included in a history order including the user identifier in the history orders;
a second generating unit configured to determine, for each store address in the store address set, a target user identifier in the user identifier set to generate a first user identifier set corresponding to the store address, wherein a distance between a place indicated by a residential address of a user indicated by the target user identifier and a store indicated by the store address is not greater than a first distance threshold;
the pushing unit is configured to generate option recommendation information corresponding to the store address based on a first user identification set corresponding to the store address in the store address set and item information included in a historical order in the historical order set, and push the option recommendation information to a terminal device of a user to which the store indicated by the store address belongs;
wherein the pushing unit is further configured to: for each store address in the store address set, analyzing a first historical order set corresponding to the store address, and determining at least one of the following items: and generating item recommendation information corresponding to the shop address and including the at least one item, wherein the item recommendation information includes information of a first second preset number of items with the largest purchased amount under different categories, information of a first second preset number of items with the largest purchased amount under different user attributes, and information of a first second preset number of items with the largest purchased amount under different item attributes.
12. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-10.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-10.
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| CN110348909A (en) * | 2019-07-16 | 2019-10-18 | 百度在线网络技术（北京）有限公司 | Acquisition methods, device, equipment and the storage medium of shop evaluation |
| CN111178968B (en) * | 2019-12-30 | 2021-10-01 | 深圳市云积分科技有限公司 | Marketing method and device for online shop and offline shop |
| CN113111233B (en) * | 2020-02-13 | 2024-04-12 | 北京明亿科技有限公司 | Regular expression-based alarm receiving text residence address extraction method and device |
| CN112446768B (en) * | 2021-02-01 | 2021-07-13 | 北京每日优鲜电子商务有限公司 | Item information recommendation method and device, electronic equipment and computer readable medium |
| CN112529672B (en) * | 2021-02-18 | 2021-06-11 | 北京每日优鲜电子商务有限公司 | Article information pushing method and device, electronic equipment and computer readable medium |
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