CN111028040A - Object sorting method and device, readable storage medium and electronic equipment - Google Patents
Object sorting method and device, readable storage medium and electronic equipment Download PDFInfo
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the invention discloses a method and a device for object sorting, a readable storage medium and electronic equipment. According to the embodiment of the invention, a plurality of objects to be displayed are obtained, and the initial sequence of the plurality of objects to be displayed is determined; determining at least one target object in the plurality of objects to be displayed; determining a recommendation index of the at least one target object according to the object characteristics of the target object; and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object. According to the method, the target objects are adjusted to the preset sorting position according to the recommendation index, and the recommendation index during the target object adjustment considers the object characteristics of the target objects, so that the considered dimensionality is more comprehensive, and the sorting accuracy is improved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a method and a device for object sorting, a readable storage medium and electronic equipment.
Background
With the continuous development of the take-out industry, the number of merchants of the take-out platform is continuously increased, the competition among the merchants is more intense, and the click rate of the merchants is greatly influenced by the ranking of the merchants in the merchant list, so that the ranking of the merchants in the merchant list needs to be improved by target merchants in the take-out platform.
In the prior art, after the takeaway platform determines the merchant list, the merchant list is sent to the user terminal, and for each user, the merchant list sent to the user terminal is sorted according to the behavior data of the user.
In summary, how to improve the accuracy and flexibility of merchant ranking in the merchant list is a problem to be solved at present.
Disclosure of Invention
In view of this, embodiments of the present invention provide an object sorting method, an object sorting device, a readable storage medium, and an electronic device, which can improve accuracy and flexibility of target object sorting.
In a first aspect, an embodiment of the present invention provides an object sorting method, where the method includes: obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed; determining at least one target object in the plurality of objects to be displayed; determining a recommendation index of the at least one target object according to the object characteristics of the target object; and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
Preferably, the method further comprises: acquiring historical data of the target object in a set period every other set period; and adjusting the recommendation index according to the historical data.
Preferably, the determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object specifically includes: according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object; an updated ranking is determined.
Preferably, determining the initial ranking of the objects to be displayed specifically includes: and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
Preferably, the object characteristics include at least one of a conversion rate of the object to be displayed, and/or a business duration of the object to be displayed, and/or a passenger volume extreme parameter of the object to be displayed.
Preferably, the method further comprises: receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
In a second aspect, an embodiment of the present invention provides an apparatus for object sorting, where the method includes: the device comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring a plurality of objects to be displayed and determining the initial sequence of the objects to be displayed; the determining unit is used for determining at least one target object in the plurality of objects to be displayed; the determining unit is further configured to determine a recommendation index of the at least one target object according to the object characteristics of the target object; and the adjusting unit is used for determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium on which computer program instructions are stored, which when executed by a processor implement the method according to the first aspect or any one of the possibilities of the first aspect.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer program instructions, where the one or more computer program instructions are executed by the processor to implement the following steps: obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed; determining at least one target object in the plurality of objects to be displayed; determining a recommendation index of the at least one target object according to the object characteristics of the target object; and determining an updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the preset ranking position is a preset ranking position preset in the initial ranking, and the recommendation index is the level of the preset ranking position corresponding to the target object.
Preferably, the processor further performs the steps of: acquiring historical data of the target object in a set period every other set period; and adjusting the recommendation index according to the historical data.
Preferably, the processor specifically executes the following steps: according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object; an updated ranking is determined.
Preferably, the processor specifically executes the following steps: and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
Preferably, the object characteristics include at least one of a conversion rate of the object to be displayed, and/or a business duration of the object to be displayed, and/or a passenger volume extreme parameter of the object to be displayed.
Preferably, the processor further performs the steps of: receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
According to the embodiment of the invention, a plurality of objects to be displayed are obtained, and the initial sequence of the plurality of objects to be displayed is determined; determining at least one target object in the plurality of objects to be displayed; determining a recommendation index of the at least one target object according to the object characteristics of the target object; and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object. According to the method, the target objects are adjusted to the preset sorting position according to the recommendation index, and the recommendation index during the target object adjustment considers the object characteristics of the target objects, so that the considered dimensionality is more comprehensive, and the sorting accuracy is improved.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method of object ordering of a first embodiment of the present invention;
FIG. 2 is a schematic illustration of an ordered list of a first embodiment of the invention;
FIG. 3 is a schematic diagram of an up-ordered listing of a first embodiment of the present invention;
FIG. 4 is a schematic diagram of an up-ordered listing of a first embodiment of the present invention;
FIG. 5 is a schematic diagram of an up-ordered listing of a first embodiment of the present invention;
FIG. 6 is a flow chart of a method of object ordering according to a second embodiment of the invention;
FIG. 7 is a schematic view of a user terminal interface of a second embodiment of the present invention;
FIG. 8 is a schematic view of a user terminal interface of a second embodiment of the present invention;
FIG. 9 is a flow chart of a method of object ordering according to a third embodiment of the invention;
FIG. 10 is a diagram of an application scenario of the fourth embodiment of the present invention;
FIG. 11 is a schematic diagram of an apparatus for object sorting according to a fifth embodiment of the present invention;
fig. 12 is a schematic view of an electronic apparatus according to a sixth embodiment of the present invention.
Detailed Description
The present disclosure is described below based on examples, but the present disclosure is not limited to only these examples. In the following detailed description of the present disclosure, certain specific details are set forth. It will be apparent to those skilled in the art that the present disclosure may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present disclosure.
Further, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present disclosure, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present disclosure, "a plurality" means two or more unless otherwise specified.
After receiving a recall request sent by a user terminal, the takeout platform places a target merchant in a merchant list and feeds the target merchant back to the user terminal, or a server actively sends the merchant list to the user terminal, and displays one exposure of the target merchant called the target merchant in the user terminal through a browsable list, wherein the content in the browsable list is a part of the merchant list, and the exposure rate in the takeout platform is the ratio of the exposure times of the target merchant in a set period to the total exposure times of all merchants of the whole takeout platform. Since the number of merchants of the take-out platform is increasing, the competition among the merchants is more vigorous, and the exposure rate of the merchants in the take-out platform greatly affects the click rate of the merchants, the exposure rate of target merchants newly entering the take-out platform or target merchants wanting to improve the click rate needs to be improved in the platform. Because the sequencing position of the target merchant in the merchant list in the takeout platform greatly influences the exposure rate of the target merchant, the exposure rate of the target merchant is improved by adopting a mode of improving the sequencing position of the target merchant in the merchant list. In the prior art, the merchant list sent to the user terminal is sorted according to the behavior data of each user, because the sorting mode only considers the behavior data of the users, the considered dimensionality is not comprehensive, the display opportunities of merchants are unbalanced, the behaviors of the merchants cannot change the self sorting, the determined sorting in the merchant list is not accurate, and after the sorting is updated through the prior art, the sorting is updated only after long-time behavior data acquisition is carried out on the users, and the flexibility is poor. Therefore, how to improve the accuracy and flexibility of merchant ranking in the merchant list is a problem to be solved at present.
In a specific embodiment, the merchant may also be referred to as an object, and the target merchant may also be referred to as a target object, which is not limited by the present invention.
Fig. 1 is a flowchart of a method of object sorting according to a first embodiment of the present invention. As shown in fig. 1, the method specifically comprises the following steps:
step S100, obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed.
Optionally, the object may be a merchant or a commodity, which is not limited in the present invention.
Specifically, the initial ordering of the multiple objects to be displayed is determined according to the score values of the multiple objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed. The object characteristics comprise at least one of a conversion rate of the object to be displayed, and/or a business duration of the object to be displayed, and/or an extreme volume-gaining parameter of the object to be displayed, wherein the extreme volume-gaining parameter can be full reduction.
In the embodiment of the invention, all merchants are scored according to the characteristics of the conversion rate, the business hours, the extreme parameters of customer volume and the like of each merchant, wherein the conversion rate is the ratio of the exposure rate of each merchant in a set period to the income value in the set period, or the ratio of the exposure rate of each merchant in the set period to the order number in the set period; the extreme consumer volume parameter may also be referred to as activity intensity of the merchant, such as a full-reduction activity of a certain profit value minus a certain profit value, a red-pack reward activity, and the like.
For example, assuming that 20 objects to be displayed are obtained and are respectively an object 1, an object 2, an object 3, an object 4, an object 5, an object 6, an object 7, an object 8, an object 9, an object 10, an object 11, an object 12, an object 13, an object 14, an object 15, an object 16, an object 17, an object 18, an object 19, and an object 20, a score value of each displayed object is determined according to an object characteristic of each displayed object, and assuming that a score value of the object 1 is 70, a score value of the object 2 is 72, a score value of the object 3 is 74, a score value of the object 4 is 68, a score value of the object 5 is 81, a score value of the object 6 is 66, a score value of the object 7 is 82, a score value of the object 8 is 84, a score value of the object 9 is 88, a score value of the object 10 is 71, a score value of the object 11 is 75, a score value of the object 12 is 76, a score value of the object 13 is 78, The score value of the object 14 is 67, the score value of the object 15 is 80, the score value of the object 16 is 65, the score value of the object 17 is 83, the score value of the object 18 is 86, the score value of the object 19 is 89, and the score value of the object 20 is 73, the 20 objects to be displayed are sorted according to the score values, as shown in table 1 below specifically:
TABLE 1
Step S101, determining at least one target object in the plurality of objects to be displayed.
Step S102, determining the recommendation index of the at least one target object according to the object characteristics of the target object.
Specifically, the recommendation index is a level of a preset ranking position corresponding to the target object, the recommendation index of the target object is preset, or is determined according to object characteristics of the target object, where the recommendation index of the target object may be at 1 level, 2 levels, and 3 levels, and in the embodiment of the present invention, the recommendation index may also have other levels, for example, may also be at 4 levels or 5 levels, which is not limited by the present invention, and the level identifier may also be at a level, a level B, a level C, or the like, which is not limited by the present invention.
In the embodiment of the present invention, the object characteristics may further include a rating, an average delivery duration, a business hour, and the like, which is not limited by the present invention.
For example, the following steps are carried out: assuming that the object 11 and the object 14 are target objects, the goodness of the object 11 is 95%, the average delivery time is 40 minutes, and the business hours are from 9 am to 6 pm, the recommendation index of the object 11 may be determined to be level 2 according to a preset rule, the goodness of the object 14 is 90%, the average delivery time is 40 minutes, and the business hours are from 10 am to 5 pm, the recommendation index of the object 14 may be determined to be level 1 according to a preset rule, specifically, the rule for determining the recommendation index according to the object characteristics is determined according to actual conditions, and the present invention does not limit the same.
Step S103, determining an updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
Specifically, the at least one target object is adjusted from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object according to the recommendation index of the at least one target object, and an updated ranking is determined.
For example, the preset sorting position is a sorting position of 5, 10, 15, and 20 in the sorted list, which is specifically shown in fig. 2. In the above embodiment, the target objects are the object 11 and the object 14, the recommendation index of the object 11 is level 2, the 11 th sorting position of the object 11 in the sorted list 1 is a preset sorting position, and after the 5 th sorting position and the 10 th sorting position are preset sorting positions, the object 11 is adjusted up to the 5 th preset sorting position after being adjusted up by level 2; the object 14 is located at the 18 th sorting position in the sorted list 1, since the 15 th is the preset sorting position, after the object 14 is up-regulated to the 1 st level, the object is up-regulated to the 15 th preset sorting position, other objects are sequentially sorted downwards, a specific up-regulation diagram is shown in fig. 3, and the sorted list 2 after being regulated is as follows:
TABLE 2
| Sorting | Object | Score value | |
| 1 | |
89 | |
| 2 | |
88 | |
| 3 | |
86 | |
| 4 | |
84 | |
| 5 | |
75 | |
| 6 | |
83 | |
| 7 | |
82 | |
| 8 | |
81 | |
| 9 | |
80 | |
| 10 | |
78 | |
| 11 | |
76 | |
| 12 | |
74 | |
| 13 | |
73 | |
| 14 | |
72 | |
| 15 | |
67 | |
| 16 | |
71 | |
| 17 | |
70 | |
| 18 | |
68 | |
| 19 | |
66 | |
| 20 | |
65 |
The score value columns in tables 1 and 2 may not be shown, and the present invention is not limited thereto.
In a possible embodiment, assuming that more than two target objects are adjusted up at the same time and then are adjusted up to the same preset sorting position, the two target objects adjusted up to the same position are alternately placed at the preset sorting position according to a set ratio, taking the two target objects as an example, assuming that the recommendation indexes of the objects 14 and the objects 6 in table 1 are all in 2 levels, the initial position of the object 14 is 18, the object 14 is adjusted up to the preset sorting position 10 after being adjusted up to 2 levels, the initial position of the object 6 is 19, the object 6 is adjusted up to the preset sorting position 10 after being adjusted up to 2 levels, and the specific up-adjustment is shown in fig. 4, since the positions of the object 14 and the object 6 after being adjusted up are both the preset sorting position 10, the preset sorting position 10 can alternately place the objects 14 or the objects 6 according to the set ratio, or perform matching according to the user characteristics of the user client, place the objects 14 or the objects 6 with a high degree of matching with the user at the preset sorting position 10, assuming that the objects 14 are adjusted up to the predetermined sort position 10, the adjusted sorted list is shown in table 3 below:
TABLE 3
Wherein the other objects are moved one bit down in sequence.
In the above embodiment, since the objects 14 and the objects 6 in table 1, the recommendation indexes are all in level 2, the initial position of the object 14 is 18, the object 14 is adjusted to the preset sorting position 10 after being adjusted up to level 2, the initial position of the object 6 is 19, the object 6 is adjusted to the preset sorting position 10 after being adjusted up to level 2, a conflict is sent, any one of the objects can be adjusted down by one level, that is, the object 6 or the object 14 is placed at the preset sorting position 15, and if the object 14 is adjusted up to the preset sorting position 10, the object 6 is adjusted up to the preset sorting position 15, specifically, the up-adjustment indicating intent is shown in fig. 5, in an embodiment of the present invention, the objects 14 or the objects 6 can be placed at the preset sorting position 10 according to a set proportion, or matching is performed according to a user characteristic of a user client, the objects 14 or the objects 6 with a high degree of matching with the, then, after modulating the remaining objects to the preset sorting position 15, for example, up-regulating the object 14 to the preset sorting position 10, up-regulating the object 6 to the preset sorting position 15, and the adjusted sorting list is shown in table 4 below:
TABLE 4
Wherein the other objects are sequentially moved down one or 2 bits.
FIG. 6 is a flow chart of another method for ordering objects according to the second embodiment of the present invention. As shown in fig. 6, before step S100, the method further includes the following steps:
step S104, receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
For example, the following steps are carried out: the recall request refers to a request triggered by a user terminal through a specific tag or in a manner of inputting a specific character in a search box, and is used for requesting a server to feed back an updated list, in example 1, as shown in fig. 7, fig. 7 is a user terminal, and the user terminal displays a taste tag: when a user selects a specific taste label, for example, "spicy" is selected, all the lists fed back by the server are objects with spicy tastes, and after receiving the lists, the user terminals display the lists in the user terminal interface according to the sequence of the updated lists as a browsable list of the user, for example, a recall request is triggered by the user clicking the "spicy" label, and the browsable list displayed on the user terminal interface is as shown in fig. 7: spicy duck necks, Chongqing spicy pots, hot lives, special spicy pots, potato powder, spicy king pots and the like. The food or store name in the embodiment of the present invention is a specific object, for example, the spicy duck neck as object 19, and the spicy hot spicy pot as object 9, and the specific food or store name is not limited in the present invention.
Example 2, as shown in fig. 8, fig. 8 shows a user terminal, and a name of a product desired by a user is input in a search box of the user terminal: for example, "congee", click "search", trigger a recall request, all businesses related to congee in the updated list fed back by the server, and after receiving the updated list, the user terminal displays the updated list on the user terminal interface in the order of the updated list as a browsable list of the user, for example, the browsable list displayed on the user terminal interface is shown in fig. 8: porridge pie houses, coarse grain houses, Jiahe Yipin, Gongtan steamed stuffed buns and the like. In the embodiment of the present invention, the names of the foods or stores are specifically referred objects, for example, the object 19 is a porridge cake house, and the object 9 is a roughage house.
FIG. 9 is a flowchart of another method for ordering objects according to the third embodiment of the present invention. As shown in fig. 9, after step S103, the method further includes the following steps:
and step S105, acquiring historical data of the target object in a set period every set period.
For example, after every set period, a first ratio of the exposure rate of the at least one target object at the preset sorting position to the revenue value of the at least one target object in the set period and/or a second ratio of the exposure rate of the at least one target object at the preset sorting position to the amount of orders of the at least one target object in the set period are/is determined. And judging the size relationship between the first ratio and a first set threshold value and a second set threshold value, and/or the size relationship between the second ratio and a third set threshold value and a fourth set threshold value. And in response to that the first ratio is smaller than a first set threshold and is greater than or equal to a second set threshold, and/or the second ratio is smaller than a third set threshold and is greater than or equal to a fourth set threshold, down-adjusting the target object to a next preset sorting position of the current preset sorting position, or, according to step S106, down-adjusting the recommendation index of the target object.
Assuming that the first ratio is a specific numerical value, for example, the initial ranking of the target object a is 16 th, the recommendation index of the target object a is 2, the 5 th, 10 th and 15 th ranking positions in the ranking list are preset ranking positions, the position of the target object a after being adjusted up is the 10 th ranking position, the first threshold is 0.7, and the second threshold is 0.3, after the set period, the first ratio of the target object a is determined to be 0.4, the first ratio is smaller than the first set threshold and larger than the second set threshold, and the target object a is adjusted down to the next preset ranking position 15 of the current preset ranking position 10; assuming that the second ratio is a specific value, for example, the initial ranking of the target object a is 16 th, the recommendation index of the target object a is 2, the 5 th, 10 th, and 15 th ranking positions in the ranking list are preset ranking positions, the position of the target object a after being adjusted up is the 10 th ranking position, the third threshold is 0.8, and the fourth threshold is 0.4, after the set period, it is determined that the second ratio of the target object a is 0.5, the second ratio is smaller than the first set threshold and larger than the second set threshold, and the target object a is adjusted down to the next preset ranking position 15 of the current preset ranking position 10. In the embodiment of the present invention, the two assumptions may be satisfied simultaneously or separately during the adjustment. In the embodiment of the present invention, the preset sorting positions may also be 4, 8, 12, 16, and the like, and the specific preset sorting positions and the intervals between the preset sorting positions are not limited in the present invention.
Optionally, in response to that the first ratio is smaller than a second set threshold, and/or that the second ratio is smaller than a fourth set threshold, the target object is adjusted downward to an initial position in the initial ranking. That is, the recommendation index is adjusted to 0 according to step S106.
If the first ratio is 0.2 and is smaller than the second threshold value 0.3, the target object a is adjusted downward to the current initial position 16; if the second ratio is 0.3 and is less than the fourth threshold value 0.4, the target object a is adjusted downward to the current initial position 16; in the embodiment of the present invention, the two assumptions may be satisfied simultaneously or separately during the adjustment.
And S106, adjusting the recommendation index according to the historical data.
In the embodiment of the invention, the recommendation index is adjusted every set period, namely, the ranking can be readjusted according to the adjusted recommendation index every set period, so that the flexibility of ranking is improved, and the ranking is more accurate.
Fig. 10 is an application scenario diagram of a fourth embodiment of the present invention, where a server or a takeout platform receives recall requests from a plurality of user terminals, and sends the updated rankings of all objects to the user terminals each time a recall request from a user terminal is received. According to the method, the target objects are adjusted to the preset sorting position according to the recommendation index, and the recommendation index during the target object adjustment considers the object characteristics of the target objects, so that the considered dimensionality is more comprehensive, and the sorting accuracy is improved.
Fig. 11 is a schematic diagram of an apparatus for object sorting according to a fifth embodiment of the present invention. As shown in fig. 11, the apparatus of the present embodiment includes an acquisition unit 1101, a determination unit 1102, and an adjustment unit 1103.
The acquiring unit 1101 is configured to acquire a plurality of objects to be displayed, and determine an initial ordering of the plurality of objects to be displayed; a determining unit 1102, configured to determine at least one target object in the multiple objects to be displayed; the determining unit 1102 is further configured to determine a recommendation index of the at least one target object according to the object characteristics of the target object; an adjusting unit 1103, configured to determine an updated ranking according to the initial ranking and a recommendation index of the at least one target object, where the recommendation index is a level of a preset ranking position corresponding to the target object.
Further, the obtaining unit 1101 is further configured to: acquiring historical data of the target object in a set period every other set period; the determining unit 1102 is further configured to adjust the recommendation index according to the historical data.
Further, the adjusting unit 1103 is specifically configured to, according to the recommendation index of the at least one target object, adjust the at least one target object from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object; an updated ranking is determined.
Further, the obtaining unit 1101 is specifically configured to: and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
Further, the object characteristics comprise at least one of conversion rate of the object to be displayed, business duration of the object to be displayed and/or extreme passenger volume parameters of the object to be displayed.
Further, the apparatus further includes a receiving unit 1104, configured to receive a recall request, where the recall request is used to obtain the plurality of objects to be displayed after the sorting is updated.
Fig. 12 is a schematic view of an electronic apparatus according to a sixth embodiment of the present invention. In this embodiment, the electronic device is a server. It should be understood that other electronic devices, such as raspberry pies, are also possible. As shown in fig. 12, the electronic apparatus: at least one processor 1201; and a memory 1202 communicatively coupled to the at least one processor 1201; and a communication component 1203 communicatively coupled to the scanning device, the communication component 1203 receiving and transmitting data under the control of the processor 1201; wherein the memory 1202 stores instructions executable by the at least one processor 1201, the instructions being executable by the at least one processor 1201 to implement: obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed; determining at least one target object in the plurality of objects to be displayed; determining a recommendation index of the at least one target object according to the object characteristics of the target object; and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
Further, the processor performs the steps of: acquiring historical data of the target object in a set period every other set period; and adjusting the recommendation index according to the historical data.
Further, the processor specifically executes the following steps: and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
Further, the processor specifically executes the following steps: according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object; an updated ranking is determined.
Further, the object characteristics comprise at least one of conversion rate of the object to be displayed, business duration of the object to be displayed and/or extreme passenger volume parameters of the object to be displayed.
Further, the processor performs the steps of: receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
Specifically, the electronic device includes: one or more processors 1201 and a memory 1202, one processor 1201 being exemplified in fig. 12. The processor 1201 and the memory 1202 may be connected by a bus or other means, and fig. 12 illustrates an example of the bus connection. Memory 1202, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 1201 executes various functional applications of the device and data processing, i.e., implements the above-described object ordering method, by executing nonvolatile software programs, instructions, and modules stored in the memory 1202.
The memory 1202 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory 1102 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 1102 may optionally include memory located remotely from the processor 1101, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 1102 that, when executed by the one or more processors 1101, perform the method of object ordering in any of the method embodiments described above.
The product can execute the method provided by the embodiment of the application, has corresponding functional modules and beneficial effects of the execution method, and can refer to the method provided by the embodiment of the application without detailed technical details in the embodiment.
A seventh embodiment of the invention relates to a non-volatile storage medium for storing a computer-readable program for causing a computer to perform some or all of the above-described method embodiments.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific embodiments for practicing the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
The embodiment of the application discloses A1 and an object sorting method, which comprises the following steps:
obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed;
determining at least one target object in the plurality of objects to be displayed;
determining a recommendation index of the at least one target object according to the object characteristics of the target object;
and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
A2, the method of a1, the method further comprising:
acquiring historical data of the target object in a set period every other set period;
and adjusting the recommendation index according to the historical data.
A3, the method as in a1, wherein the determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object specifically includes:
according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to the preset ranking position corresponding to the recommendation index of the at least one target object;
an updated ranking is determined.
A4, the method as in a1, determining the initial ranking of the objects to be displayed, specifically comprising:
and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
A5, the method according to a1 or a4, wherein the object characteristics include at least one of conversion rate of the object to be displayed, and/or operating time of the object to be displayed, and/or extreme volume of the object to be displayed.
A6, the method of a1, the method further comprising:
receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
The embodiment of the application also discloses B1, a device for object sorting, which comprises:
the device comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring a plurality of objects to be displayed and determining the initial sequence of the objects to be displayed;
the determining unit is used for determining at least one target object in the plurality of objects to be displayed;
the determining unit is further configured to determine a recommendation index of the at least one target object according to the object characteristics of the target object;
and the adjusting unit is used for determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
The embodiment of the application also discloses C1, a computer readable storage medium, on which computer program instructions are stored, the computer program instructions, when executed by a processor, implement the method according to any one of A1-A6.
The embodiment of the application also discloses a D1 electronic device, comprising a memory and a processor, wherein the memory is used for storing one or more computer program instructions, and the one or more computer program instructions are executed by the processor to realize the following steps:
obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed;
determining at least one target object in the plurality of objects to be displayed;
determining a recommendation index of the at least one target object according to the object characteristics of the target object;
and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
D2, the electronic device as recited in D1, the processor further performing the steps of:
acquiring historical data of the target object in a set period every other set period;
and adjusting the recommendation index according to the historical data.
D3, the electronic device as recited in D1, the processor specifically performs the following steps:
according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to a preset ranking position corresponding to the recommendation index of the at least one target object;
an updated ranking is determined.
D4, the electronic device as recited in D1, the processor specifically performs the following steps:
and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
D5 the electronic device according to D1 or D4, wherein the object characteristics include at least one of a conversion rate of the object to be displayed, and/or a business hours of the object to be displayed, and/or a volume capture level of the object to be displayed.
D6, the electronic device as recited in D1, the processor further performing the steps of:
receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
Claims (10)
1. A method of object ranking, the method comprising:
obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed;
determining at least one target object in the plurality of objects to be displayed;
determining a recommendation index of the at least one target object according to the object characteristics of the target object;
and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
2. The method of claim 1, further comprising:
acquiring historical data of the target object in a set period every other set period;
and adjusting the recommendation index according to the historical data.
3. The method of claim 1, wherein the determining an updated ranking according to the initial ranking and the recommendation index of the at least one target object comprises:
according to the recommendation index of the at least one target object, the at least one target object is adjusted from the position in the initial ranking to the preset ranking position corresponding to the recommendation index of the at least one target object;
an updated ranking is determined.
4. The method of claim 1, wherein determining the initial ranking of the objects to be displayed specifically comprises:
and determining the initial ordering of the objects to be displayed according to the score values of the objects to be displayed, wherein the score values are determined according to the object characteristics corresponding to each object to be displayed.
5. The method according to claim 1 or 4, wherein the object characteristics comprise at least one of conversion rate of the object to be displayed, and/or business hours of the object to be displayed, and/or extreme volume of the object to be displayed.
6. The method of claim 1, further comprising:
receiving a recall request, wherein the recall request is used for acquiring the plurality of objects to be displayed after sequencing updating.
7. An apparatus for object ranking, the apparatus comprising:
the device comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring a plurality of objects to be displayed and determining the initial sequence of the objects to be displayed;
the determining unit is used for determining at least one target object in the plurality of objects to be displayed;
the determining unit is further configured to determine a recommendation index of the at least one target object according to the object characteristics of the target object;
and the adjusting unit is used for determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
8. A computer-readable storage medium on which computer program instructions are stored, which computer program instructions, when executed by a processor, implement the method of any one of claims 1-6.
9. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to perform the steps of:
obtaining a plurality of objects to be displayed, and determining the initial sequence of the objects to be displayed;
determining at least one target object in the plurality of objects to be displayed;
determining a recommendation index of the at least one target object according to the object characteristics of the target object;
and determining the updated ranking according to the initial ranking and the recommendation index of the at least one target object, wherein the recommendation index is the level of a preset ranking position corresponding to the target object.
10. The electronic device of claim 9, wherein the processor further performs the steps of:
acquiring historical data of the target object in a set period every other set period;
and adjusting the recommendation index according to the historical data.
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