CN110738554A

CN110738554A - Task processing method and device, electronic equipment and computer readable storage medium

Info

Publication number: CN110738554A
Application number: CN201911032721.XA
Authority: CN
Inventors: 周凯荣; 李承波; 叶畅; 凌晨轩; 陈丹娃
Original assignee: Rajax Network Technology Co Ltd
Current assignee: Rajax Network Technology Co Ltd
Priority date: 2019-10-28
Filing date: 2019-10-28
Publication date: 2020-01-31
Anticipated expiration: 2039-10-28
Also published as: CN110738554B

Abstract

The task processing method comprises the steps of obtaining team task data, wherein the team task data comprise th product type set and the total number of members of team members, generating data collection questions according to the team task data, outputting the data collection questions to clients of at least team members, so that team characteristic data of the team members can be obtained from answers of the team members to the data collection questions.

Description

Task processing method and device, electronic equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of computer application technologies, and in particular, to task processing methods and apparatuses, an electronic device, and a computer-readable storage medium.

Background

When a team customizes products for users through the internet platform, generally determines or more product providers in advance and then determines products from or more product providers, when the team determines product providers, although the process is simple and the cost is easy to control, it is difficult to satisfy all users due to personalized differences among users in the team, when the team determines a plurality of product providers, it is necessary to customize products to each product provider separately, although the process is complicated and the cost is not easy to control, which can give consideration to the preferences of most users in the team.

Disclosure of Invention

In order to solve the problems in the related art, the embodiments of the present disclosure provide task processing methods, apparatuses, electronic devices, and computer-readable storage media.

, task processing methods are provided in the disclosed embodiments.

Specifically, the task processing method includes:

acquiring team task data, wherein the team task data comprises product type sets and the total number of members of a team;

generating a data collection problem according to the team task data;

and outputting the data collection question to clients of at least team members so as to obtain team characteristic data of the team members from answers of the team members to the data collection question, wherein the team characteristic data comprises a second product type set and a corresponding relation between a second product type in the second product type set and the team members, and the second product type is a subordinate type of a product type in the product type set.

With reference to aspect , the present disclosure in an implementation of aspect , the generating data collection questions from the team task data includes:

determining at least second product types under the product type from the product types in the team task data;

generating the data collection question and a plurality of candidate answers according to the second product type.

With reference to the implementation manner of the aspect, in a second implementation manner of the aspect, the present disclosure further includes:

receiving the candidate answers selected by at least team members for the data collection question;

determining team feature data of the team members according to the candidate answers.

With reference to the second implementation manner of the aspect, in a third implementation manner of the aspect, the present disclosure further includes:

determining a target product combination to be acquired by a team task according to the team task data and the team characteristic data; wherein the target product combination comprises target products and corresponding quantities under the second product type.

With reference to the third implementation manner of the aspect, in a fourth implementation manner of the aspect, the team task data further includes product limitation conditions, and the determining a target product combination to be obtained by a team task according to the team task data and the team feature data includes:

determining a second quantity of candidate products according to the th quantity of the team members having correspondence with the second product type for the second product type in the second product type set to form a th candidate product set, wherein the second quantity is in direct proportion to the th quantity;

determining a plurality of target products from the th candidate product set according to the product constraints.

With reference to the fourth implementation manner of the aspect, in a fifth implementation manner of the aspect, the determining, for the second product type in the second set of product types, a second number of th candidate products according to the th number of team members having a corresponding relationship with the second product type to form a th candidate product set includes:

determining th candidate product according to historical data of the team member having a corresponding relationship with the second product type, wherein the historical data comprises data generated when the team member acquires the product of the second product type within a historical time period.

With reference to the fifth implementation manner of the aspect, in a sixth implementation manner of the aspect, the determining the th candidate product according to the historical data of the team member having a correspondence with the second product type includes:

determining a trend feature value of the team member for a second candidate product according to the historical data;

determining th candidate product from the second candidate product based on the trend feature value.

With reference to the fifth implementation manner of the aspect, in the seventh implementation manner of the aspect, the product limitation includes a total cost of products to be acquired by the team task, and the determining a plurality of target products from the candidate product set according to the product limitation includes:

selecting number of the candidate products from the candidate product set corresponding to the second product type;

forming a plurality of different candidate product combinations according to the candidate products selected from the candidate product sets corresponding to all the second product types, wherein the total value of the candidate products in the candidate product combinations is less than or equal to the total cost;

determining the th candidate product of the of the candidate product combinations as the target product according to the team member's historical data.

With reference to the seventh implementation manner of the aspect, in an eighth implementation manner of the aspect, the determining the candidate product of the candidate product combinations as the target product according to the historical data of the team members includes:

determining the target product according to the tendency characteristic value of the team member to the th candidate product in the candidate product combination.

In a second aspect, task processing methods are provided in the disclosed embodiments.

Specifically, the task processing method includes:

acquiring team task data and team characteristic data of team members in a team task, wherein the team task data comprises an product type set, the total number of the team members and product limitation conditions, and the characteristic data comprises a second product type set and a corresponding relation between a second product type in the second product type set and the team members;

With reference to the second aspect, in an th implementation manner of the second aspect, the determining, for the second product type in the second set of product types, a second number of th candidate products according to a th number of the team members having a correspondence with the second product type, forming a th candidate product set includes:

With reference to the th implementation of the second aspect, in the second implementation of the second aspect, the determining the th candidate product according to the historical data of the team member having a correspondence with the second product type includes:

With reference to the th implementation manner of the second aspect, in a third implementation manner of the second aspect, the product limitation includes a total cost of products to be acquired by the team task, and determining a plurality of target products from the th candidate product set according to the product limitation includes:

forming a plurality of different candidate product combinations according to the candidate products selected from the candidate product set corresponding to all the second product types;

With reference to the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the determining the th candidate product of the candidate product combinations as the target product according to the historical data of the team members includes:

In a third aspect, task processing methods are provided in the embodiments of the present disclosure.

Specifically, the task processing method includes:

responding to a request of a creating user for creating a team task, and outputting a providing page of team task data to a client of the creating user;

determining team task data and an acquisition mode of team characteristic data according to the content input by the creating user on the provided page, wherein the team task data comprises product type sets and the total number of team members;

and when the acquisition mode of the team characteristic data is to be acquired from a team member, the characteristic acquisition link is sent to a client of the team member, so that the team member can provide answers according to the data collection questions pointed by the characteristic acquisition link.

With reference to the third aspect, in an implementation manner of the third aspect, the present disclosure further includes:

and sending the team task data to a server side, and receiving the characteristic acquisition link from the server side.

With reference to the implementation manners of the third aspect, in a second implementation manner of the third aspect, the present disclosure further includes:

sending answers of the data collection questions to a server side, and receiving team characteristic data of team members and/or at least target product combinations from the server side, wherein the characteristic data comprise a second product type set and corresponding relations between second product types in the second product type set and the team members, the second product types are subordinate types of product types in the product type set, and the target product combinations comprise target products and corresponding quantities under the second product types;

outputting the team characteristic data and/or the target product combination to the client of the creating user.

With reference to the second implementation manner of the third aspect, in a third implementation manner of the third aspect, the present disclosure further includes:

and responding to the selected request of the creating user for target product combinations, and requesting a server side to generate orders corresponding to the target product combinations.

With reference to the third implementation manner of the third aspect, in a fourth implementation manner of the third aspect,

in response to a request to join a created team task, returning status data for the team task to the client that sent the request.

In a fourth aspect, task processing devices are provided in the disclosed embodiments.

Specifically, the task processing device includes:

an acquisition module configured to acquire team task data, wherein the team task data comprises a product type set and a total number of members of a team;

, a generation module configured to generate data collection questions from the team task data;

an output module configured to output the data collection question to a client of at least team members to obtain team feature data of the team members from answers to the data collection question by the team members, wherein the team feature data comprises a second set of product types and a corresponding relationship between a second product type in the second set of product types and the team members, and the second product type is a subordinate type of a th product type in the product type set.

With reference to the fourth aspect, in an th implementation manner of the fourth aspect, the generating a data collection question according to the team task data includes:

With reference to the implementation manner of the fourth aspect, in a second implementation manner of the fourth aspect, the present disclosure further includes:

an receiving module configured to receive the candidate answers selected by at least team members for the data collection question;

an determination module configured to determine team feature data of the team member from the candidate answer.

With reference to the second implementation manner of the fourth aspect, in a third implementation manner of the fourth aspect, the present disclosure further includes:

the second determination module is configured to determine a target product combination to be acquired by the team task according to the team task data and the team characteristic data; wherein the target product combination comprises target products and corresponding quantities under the second product type.

With reference to the third implementation manner of the fourth aspect, in a fourth implementation manner of the fourth aspect, the team task data further includes product limitation conditions; the step of determining the target product combination to be acquired by the team task according to the team task data and the team characteristic data comprises the following steps:

With reference to the fourth implementation manner of the fourth aspect, in a fifth implementation manner of the fourth aspect, the determining, for the second product type in the second set of product types, a second number of th candidate products according to an th number of the team members having a corresponding relationship with the second product type to form a th candidate product set includes:

With reference to the fifth implementation manner of the fourth aspect, in a sixth implementation manner of the fourth aspect, the determining the candidate product according to the historical data of the team member having a corresponding relationship with the second product type includes:

With reference to the fifth implementation manner of the fourth aspect, in a seventh implementation manner of the fourth aspect,

determining a plurality of target products from the th candidate product set according to the product constraints, wherein the product constraints comprise the total cost of the products to be acquired by the team mission, and the determining comprises the following steps:

With reference to the seventh implementation manner of the fourth aspect, in an eighth implementation manner of the fourth aspect, the determining the candidate product of the candidate product combinations as the target product according to the historical data of the team members includes:

In a fifth aspect, task processing devices are provided in the disclosed embodiments.

Specifically, the task processing device includes:

the team mission data comprises an th product type set, the total number of members of a team member and product limiting conditions, and the characteristic data comprises a second product type set and a corresponding relation between a second product type in the second product type set and the team member;

a third determining module configured to determine, for the second product type in the second set of product types, a second number of candidate products according to an th number of the team members having a correspondence with the second product type, forming a th set of candidate products, wherein the second number is in direct proportion to the th number;

a fourth determination module configured to determine a plurality of target products from the th candidate product set according to the product constraints.

With reference to the fifth aspect, in an implementation manner of the fifth aspect, the determining, for the second product type in the second set of product types, a second number of candidate products according to a number of the team members having a correspondence with the second product type to form a candidate product set includes:

With reference to the implementation manner of the fifth aspect, in a second implementation manner of the fifth aspect, the determining the th candidate product according to the historical data of the team member having a corresponding relationship with the second product type includes:

With reference to the th implementation manner of the fifth aspect, in a third implementation manner of the fifth aspect, the product limitation includes a total cost of products to be acquired by the team task, and determining a plurality of target products from the th candidate product set according to the product limitation includes:

With reference to the third implementation manner of the fifth aspect, in a fourth implementation manner of the fifth aspect, the determining the candidate product of the candidate product combinations as the target product according to the historical data of the team members includes:

In a sixth aspect, task processing devices are provided in embodiments of the present disclosure.

Specifically, the task processing device includes:

a second output module configured to output a providing page of team task data to a client of a creating user in response to a request of the creating user for creating a team task;

a fifth determining module, configured to determine team task data and an acquisition mode of team feature data according to the content input by the creating user on the providing page, wherein the team task data includes product type set and the total number of team members;

, a sending module configured to send a characteristic obtaining link to a team member client when the team characteristic data is obtained from the team member, so that the team member can provide an answer according to the data collection question pointed by the characteristic obtaining link.

With reference to the sixth aspect, in an implementation manner of the sixth aspect, the present disclosure further includes:

and the second sending module is configured to send the team task data to a server side and receive the feature acquisition link from the server side.

With reference to the implementation manner of the sixth aspect, in a second implementation manner of the sixth aspect, the present disclosure further includes:

a second receiving module, configured to send answers to the data collection questions to a server, and receive team characteristic data of team members and/or at least target product combinations from the server, wherein the characteristic data includes a second product type set and a corresponding relationship between a second product type in the second product type set and the team members, the second product type is a subordinate type of a product type in the product type set, and the target product combinations include target products under the second product type and corresponding quantities;

a third output module configured to output the team characteristic data and/or the target product combination to the client of the creating user.

With reference to the second implementation manner of the sixth aspect, in a third implementation manner of the sixth aspect, the present disclosure further includes:

and the second generation module is configured to respond to the selected request of the creating user for target product combinations, and request the server side to generate orders corresponding to the target product combinations.

With reference to the third implementation manner of the sixth aspect, in a fourth implementation manner of the sixth aspect, the present disclosure further includes:

a return module configured to return status data of the team task to a client sending the request in response to a request to join the created team task.

In a seventh aspect, an embodiment of the present disclosure provides electronic devices, including a memory and a processor, where the memory is configured to store one or more computer instructions, where the one or more computer instructions are executed by the processor to implement the following method steps:

generating a data collection problem according to the team task data;

In an eighth aspect, the disclosed embodiments provide electronic devices comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of:

In a ninth aspect, the disclosed embodiments provide electronic devices comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of:

In a tenth aspect, embodiments of the present disclosure provide computer readable storage media having stored thereon computer instructions that, when executed by a processor, implement the method as recited in any of the , -eighth implementation of aspect .

In a tenth aspect, embodiments of the present disclosure provide computer readable storage media having stored thereon computer instructions that, when executed by a processor, implement the method as in the second aspect, any of the aspects of the implementation to the fourth implementation.

In a twelfth aspect, there are computer readable storage media provided in embodiments of the present disclosure, having stored thereon computer instructions that, when executed by a processor, implement the method as described in the third aspect, the implementation of the third aspect, or any of the fourth implementation.

According to the technical scheme provided by the embodiment of the disclosure, after team task data are acquired, wherein the team task data comprise th product type sets and the total number of members of team members, data collection questions are generated according to the team task data, the data collection questions are output to clients of at least team members, so that team characteristic data of the team members are acquired from answers of the team members to the data collection questions, the characteristic data comprise corresponding relations between second product types in second product type sets and the team members and second product types in the second product type sets, and the second product types are lower types of th product types in product type sets.

It is to be understood that both the foregoing -general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:

FIG. 1 shows a task processing system schematic according to an embodiment of the present disclosure;

FIG. 2 shows a flow diagram of a task processing method according to an embodiment of the present disclosure;

FIG. 3 illustrates a flow diagram for generating a data collection question from the team task data according to an embodiment of the present disclosure;

FIG. 4 illustrates a flow diagram for determining a target product portfolio to be captured by a team mission based on the team mission data and the team characteristic data in accordance with an embodiment of the present disclosure;

FIG. 5 illustrates a flow diagram for determining th candidate products based on historical data of the team members having a correspondence with the second product type, according to an embodiment of the disclosure;

FIG. 6 illustrates a flow diagram for determining th candidate products based on historical data of the team members having a correspondence with the second product type, according to an embodiment of the disclosure;

FIG. 7 shows a flow diagram of a task processing method according to an embodiment of the present disclosure;

FIG. 8 shows a flow diagram of a task processing method according to an embodiment of the present disclosure;

FIG. 9 is a schematic diagram illustrating an application scenario of a task processing method according to an embodiment of the disclosure;

fig. 10 shows a block diagram of a task processing device 1000 according to an embodiment of the present disclosure;

fig. 11 shows a block diagram of a task processing device 1100 according to an embodiment of the present disclosure;

fig. 12 shows a block diagram of a task processing device 1200 according to an embodiment of the present disclosure;

fig. 13 shows a block diagram of an electronic device 1300 according to an embodiment of the disclosure;

fig. 14 shows a schematic structural diagram of a computer system suitable for implementing a task processing method according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof in the specification, and are not intended to exclude the possibility that or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.

It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

As described above, the present disclosure has been made to at least partially solve the problems in the prior art found by the inventors.

The task processing system for executing the task processing method in the embodiment of the present disclosure includes at least , th computer devices and at least second computer devices, where at least , th computer devices and at least second computer devices are connected through a network, for example, through a wired or wireless network, the th computer device may be an internet platform end device such as a server or a cloud computing platform, for example, a single server, or a server cluster composed of a plurality of servers, and the second computer device may be a client, for example, a notebook computer, a tablet computer, or a smartphone, and it should be understood that the number, the type, and the specific connection mode of the th computer device and the second computer device are determined according to specific application needs, and the present disclosure is not particularly limited.

In the task processing system for executing the task processing method in the embodiment of the present disclosure, an th computer device is taken as a server, and a second computer device is taken as a mobile phone and/or a computer client.

As shown in FIG. 1, the task processing system comprises at least servers 101 and at least mobile phone and/or computer clients 102, wherein at least servers 101 and at least mobile phone and/or computer clients 102 are connected through a limited or wireless network, at least servers 101 can be used for obtaining team task data and performing team task processing, and at least mobile phone and/or computer clients 102 can be used for interacting with users such as a group leader (a creation user of a team task), a team member and the like, obtaining team task data from the group leader, obtaining answers to questions from the team member and the like, and simultaneously outputting team task processing results to the group leader, the team member and the like.

Fig. 2 shows a flowchart of a task processing method according to an embodiment of the present disclosure, which is performed on the server 101 side. As shown in fig. 2, the task processing method includes the following steps S201 to S203:

in step S201, team task data are obtained, wherein the team task data comprise th product type set and the total number of members of a team;

in step S202, generating a data collection question according to the team task data;

in step S203, the data collection question is output to a client of at least team members, so as to obtain team feature data of the team members from answers to the data collection question by the team members, wherein the team feature data includes a second set of product types and a corresponding relationship between a second product type in the second set of product types and a team member, and the second product type is a subordinate type of the th product type in the product type set.

According to the embodiment of the present disclosure, a team may be groups composed of two or more team members, a team task may be tasks related to the team, for example, the team members in the team need a product customized through the internet platform where the server 101 is located, wherein the product may include a service and/or an article, for example, a work team in a business customizes a work meal for employees through the internet platform where the server 101 is located, or a team in the business organizes activities by customizing activity props, prizes, or subject meals for participating members through the internet platform where the server 101 is located, when the team has a demand for customizing products, or more team tasks may be created by creating users in the team, for example, a team leader through the client 102, it should be understood that the embodiment of the present disclosure will be exemplified by creating a team task based on a new team, but the present disclosure is not limited thereto.

According to an embodiment of the present disclosure, when a creating user creates a team task through a client 102, the client 102 may obtain team task data from the creating user, wherein the team task data includes data related to the team task, for example, a product type set and a total number of members of the team, wherein a product type set includes or more product types, a product type may be a superior type of a product to be customized by the team task, and the team task aims to customize a product under a product type for the team members, and the total number of members may be a total number of team members in the team, the total number of team members may be determined by creating data provided by the user, or may be determined by counting a number of persons who actively join the team, it should be understood that the present disclosure will exemplify an internet platform where the server 101 is located, a team task is an active meal for the group, but the present disclosure is not limited thereto, and the present disclosure may also be applicable to other applications that can be processed using the method provided by the present disclosure, such as a diet task set including a set of a diet products of a variety of fruit type 735, snack products, a diet product type of a variety of fruit type, a set, a snack product type of a fruit type of a variety of a fruit type , a fruit type, a snack product type of a fruit type of a snack product type of.

According to the embodiment of the disclosure, after the client 102 determines the team task data, the team task data can be sent to the server 101, in order to take account of personalized differences of team members, the server 101 generates a data collection problem according to th product types in the acquired team task data, wherein the data collection problem comprises a problem for determining requirement information of the team members on th product types, for example, service requirements, product requirements, merchant requirements, cuisine requirements, offer sensitivity, price requirements, resource requirements and the like.

, the creating user may further forward or more link addresses to the clients 102 of other team members through the clients 102, so that the data collection questions are output to the clients 102 of at least team members, the disclosure does not specifically limit the form of the link addresses, for example, may be a Uniform Resource Locator (URL) of system , the team members who acquire the data collection questions may give corresponding answers to different data collection questions in combination with their own needs, and send to the server 101, so that the server 101 may acquire team feature data of the team members according to the above answers, wherein the team feature data is used to indicate the information of the requirements of the team members on a subordinate type of a product type, for example, the feature data may include a second team product type and a corresponding relationship between the second team member type and the second product type, wherein the second team feature data may include a product type, and the second product type may be determined after the product type is a product type corresponding to the second team member type, and the product type corresponding relationship between the second team member type and the second product type may be determined by a mapping relationship between the second product type 46 .

FIG. 3 illustrates a flow diagram for generating a data collection question from the team task data according to an embodiment of the present disclosure. As shown in FIG. 3, the step S202 of generating a data collection question according to the team task data includes the following steps S301-S302:

in step S301, determining at least second product types under the product type from the product type in the team mission data;

in step S302, the data collection question and a plurality of candidate answers are generated according to the second product type.

According to an embodiment of the present disclosure, since th product types are -level categories of products, and each th product type includes or more second product types, in order to understand more accurate demand information of different team members for th product type, at least second product types under th product type may be determined first, and then a data collection question may be generated for the second product types, so as to obtain the tendency degree of different team members for each different second product type, the higher the tendency degree, the more the team members tend to customize the corresponding second product type, in order to improve the convenience of team members to answer the data collection question, a plurality of candidate answers to the data collection question may be provided at the same time as the data collection question is provided, and in addition, the team members may be allowed to freely supplement other candidate answers, the present disclosure embodiment will establish an active meal for a team mission, the set of product types includes a main food, dishes, and beverages for example, th second product types may be determined first, then a main food collection question may be generated for a corresponding plurality of main food, and:

(1) do you like salad or steak? A, salad and B steak;

(2) what is you like for salad? A Kaiser salad, B Mediterranean salad, C Greek salad, D Wal Doff salad, E Neiss;

(3) what kind of steak you like? A western-style cold beefsteak, B Feili beefsteak, C French beefsteak, D naked eye beefsteak, E American beefsteak, F dried beefsteak, G Korean beefsteak;

(4) is bread and cookies placed to eat better

The data collection question (4) is a fun question, since bread and cookies do not affect each other, but from the fun answer, the user attributes of team members can be determined, for example, the team member selecting answer A is a biased team member, and the team member selecting answer B is a biased team member.

Fig. 2 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 2, the task processing method further includes the following steps S204 to S205:

receiving the candidate answers selected by at least team members for the data collection question in step S204;

in step S205, team feature data of the team members is determined according to the candidate answers.

According to an embodiment of the present disclosure, after the server 101 acquires candidate answers of team members, feature data of each team member may be determined for the candidate answer of each team member, and then, according to the feature data of all team members that provide the candidate answers, the team feature data may be determined. The embodiment of the present disclosure will be described by taking a team task as a group to build an active meal, taking 10 persons as an example, and assuming that candidate answers of 10 persons are: (1) and (3) salad: 5 people prefer Kaesar salad, 5 people prefer Mediterranean salad; (2) beefsteak: 5 people like western cold steak, 2 people like phenanthrene steak, 3 people like naked eye steak, team characteristic data can be determined, namely the second product type set is { Kaisar salad, Mediterranean salad, western cold steak, phenanthrene steak, naked eye steak }, and the corresponding relation between the second product type and team members is as follows: 5 people prefer Kaesar salad, 5 people prefer Mediterranean salad, 5 people prefer West cold steak, 2 people prefer Feili steak, and 3 people prefer naked eye steak.

Fig. 2 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 2, the task processing method further includes the following step S206:

in step S206, determining a target product combination to be acquired by the team task according to the team task data and the team feature data; wherein the target product combination comprises target products and corresponding quantities under the second product type.

According to the embodiment of the disclosure, after determining the team task data and the team feature data, the server 101 may determine candidate product combinations according to the team feature data, that is, determine candidate second product types and corresponding relations between each candidate second product type and different team members, and then determine target product combinations to be obtained by the team task from the candidate product combinations according to the team task data, that is, target products of the second product types and corresponding relations between the target products and different team members.

According to the technical scheme provided by the embodiment of the disclosure, the target product combination to be acquired by the team task is determined by determining the team task data and the team characteristic data, so that the problems of low task processing efficiency, unsatisfactory task processing result and the like caused by complex flow, difficult control of cost and the like in the process of customizing a product by a team are avoided.

FIG. 4 illustrates a flow diagram for determining a target product portfolio to be captured by a team mission based on the team mission data and the team characteristic data, according to an embodiment of the disclosure. As shown in fig. 4, the team task data further includes product limitation conditions, and the step S206, namely determining the target product combination to be obtained by the team task according to the team task data and the team feature data, includes the following steps S401 to S402:

in step S401, for the second product type in the second product type set, determining a second quantity candidate products according to the th quantity of the team members having correspondence with the second product type, and forming a th candidate product set, wherein the second quantity is in direct proportion to the th quantity;

in step S402, a plurality of target products are determined from the th candidate product set according to the product limitation condition.

According to the embodiment of the disclosure, since the second product type set includes or more second product types, and each second product type has a corresponding correspondence relationship with team members, that is, the number of team members preferring the second product type is , the 1 th candidate product of the second product type can be determined based on the 0 th quantity, all th candidate products corresponding to the second product type can be determined as the th candidate product set, wherein the th candidate product is the second quantity, and there can be an association relationship, such as a direct relationship, between the second quantity and the th quantity, the embodiment of the disclosure will explain that a team task is a meal for the event, and the second quantity is 10 times the number, for example, assuming 5-person hamburger and 5-person favorite steak, then the th candidate product corresponding to hamburger is 50 hamburger, the th candidate product corresponding to hamburger, and the th candidate product set is 50 { 50.6352 } hamburger.

According to an embodiment of of the present disclosure, a candidate product set includes a larger number of th candidate products, and thus, according to product constraints, a part of th candidate products in the candidate product set 1 may be determined as target products, and when determining target products, the number of target products belonging to the second product type 3 may be made smaller than or equal to the number of th candidate products corresponding to the second product type, and the number of target products belonging to the th product type may be made smaller than or equal to the total number of team members, it is understood that the most desirable case is that target products belonging to the second product type correspond to th number of the second product type , and in the above-described group meal ordering task, including 5 team members in the team characteristic data corresponds to the second product type of "hamburger", then the final target product may include 5 hamburger products, while in the group meal ordering task 6862, if the number of target products belonging to the second product type is smaller than the target product type 82865, and thus, it is possible that the target product types may be a group meal ordering task, and the number of products corresponding to control product types may be smaller than the target product types , and thus, and if the target product types may be a target product types , and the group ordering task may be a case that the number of products belonging to a group meal ordering task may be equal to a target product type , and further, and that the target product types may be a group product type , and that the group product type may be a group ordering task may be a group product type may be a group ordering task with a group ordering task, and that a group ordering task may be a group ordering task may include a group.

According to an embodiment of the present disclosure, the step S401 of determining, for the second product type in the second set of product types, a second number of candidate products according to an th number of the team member having a correspondence with the second product type, forming a th set of candidate products, may be implemented to determine the th candidate product according to historical data of the team member having a correspondence with the second product type, wherein the historical data includes data generated when the team member acquires a product of the second product type within a historical period of time.

The acquisition mode of the historical data is not particularly limited in the disclosure, for example, click data, browsing data, ordering data and/or transaction data and the like in an internet platform for customizing products in a historical time period by team members can be used, and association data of different team members and products of a second product type with corresponding relations to the second product type can be extracted from the click data, browsing data, ordering data and/or transaction data and the like as historical data, and tendency characteristics of the team members to the products of the second product type can be acquired from the historical data, so that a candidate product can be further determined in step .

FIG. 5 shows a flow chart of determining th candidate product based on historical data of the team member having a correspondence with the second product type, according to an embodiment of the present disclosure, as shown in FIG. 5, the determining th candidate product based on historical data of the team member having a correspondence with the second product type comprises the following steps S501-S502:

in step S501, determining tendency characteristic values of the team members for a second candidate product according to the historical data;

in step S502, the th candidate product is determined from the second candidate products according to the tendency feature value.

According to the embodiment of the disclosure, since the product categories of the second product type are numerous and include a plurality of second candidate products, different team members have different degrees of tendency to different second candidate products, the tendency characteristic value of the team members to the second candidate products can be determined according to the historical data, and then part of the second candidate products can be determined as th candidate products according to the tendency characteristic value.

The method for determining the tendency characteristic value is not particularly limited in the present disclosure, for example, the tendency characteristic value may be determined through a prediction model, input parameters of the prediction model include but are not limited to historical data of a team member for a product, output parameters are tendency characteristic values of the team member for the product, the prediction model is trained through the historical data, and after the prediction model is trained, the historical data of the team member for a second candidate product is input to the trained prediction model, so that the tendency characteristic value of the team member for the second candidate product may be determined.

For another example, the calculation formula of the tendency feature value may be defined as: the trend characteristic value is a1 × second candidate product sales amount + a2 × second candidate product price + A3 × second candidate product score, where a1, a2, and A3 are weights of the second candidate product sales amount, the second candidate product price, and the second candidate product score in a calculation formula of the trend characteristic value, and may be set according to an actual application scenario, and the disclosure does not specifically limit the calculation formula.

According to an embodiment of the present disclosure, after determining the trend characteristic values of team members and second candidate products corresponding to the second product type, determining the trend characteristic values of second candidate products and all the team members corresponding to the second product type, i.e., adding all the team members to second candidate products, thereby determining candidate products according to the trend characteristic values, for example, assuming that the second product type is steak, the second candidate products may be western cold steak, philippine steak, french steak, unaided steak, american steak, dry-fried steak, and korean steak, and based on historical data, such as or more of click data, browsing data, ordering data, or transaction data of the team members on the 7 steaks, the trend characteristic values of the team members to the corresponding steaks may be determined by using the predictive model or the calculation formula of the trend characteristic values, thereby determining second candidate products.

FIG. 6 shows a flow chart of determining th candidate product based on historical data of team members having correspondence with the second product type according to an embodiment of the present disclosure, as shown in FIG. 6, the product constraint includes a total cost of products to be acquired by the team mission, and the step S402 of determining th candidate product set a plurality of target products based on the product constraint includes the following steps S601-S603:

in step S601, selecting number of candidate products from the candidate product set corresponding to the second product type;

in step S602, a plurality of different candidate product combinations are formed according to the candidate product selected from the candidate product sets corresponding to all the second product types, wherein the total value of the candidate product included in the candidate product combinations is less than or equal to the total cost;

in step S603, the th candidate product of the candidate product combinations is determined to be the target product according to the team member' S historical data.

According to the embodiment of the disclosure, th th candidate products can be selected from th candidate product sets corresponding to the second product type according to preset rules, the preset rules are not specifically limited, and the determination can be performed according to actual needs, for example, th th candidate products can be selected according to product prices, product sales or product scores of th candidate products, for example, 2 favorite steaks, two phenanthrene steaks can be selected from th candidate product sets assuming that prices of the phenanthrene steaks are lowest, for example, 3 favorite salads, and 3 cassarads can be selected from th candidate product sets assuming that sales of the cassarads are best.

According to an embodiment of the present disclosure, when the product limitation condition includes a total cost of products to be obtained by a team mission, wherein the total cost may include, but is not limited to, a total price of the target product and a total distribution cost, since each second product type has a candidate product corresponding to the selected candidate product, all candidate products corresponding to the selected second product type may be combined to form a plurality of different candidate product sets, and a total value of candidate products included in the candidate product set may be less than or equal to the total cost, and at the same time, a number of candidate products included in the candidate product set may be less than or equal to a total number of members, and a number of candidate products included in the candidate product set and belonging to the same second product type may be less than or equal to a number, then a candidate product of candidate product sets among them may be determined as the target product according to a history data of the team members, and a number of candidate products may be determined as a corresponding number of the target product.

According to an embodiment of the present disclosure, the step S603 of determining the th candidate product of the candidate product groups as the target product according to the team member 'S historical data may be implemented to determine the target product according to the team member' S propensity profile for the th candidate product of the candidate product groups.

According to the embodiment of the disclosure, a target candidate product combination can be determined according to a search algorithm according to the tendency characteristic value of a candidate product in the candidate product combination of team members, and then a candidate product in the target candidate product combination is determined as a target product.

According to an embodiment of the present disclosure, the task processing method further includes the steps of: acquiring feedback data of the team members on the target product combination; and determining the order of the target product combination according to the target product combination and the feedback data.

According to the requirement of a team for customizing a product, a target product combination, namely a target product and a corresponding quantity, can be recommended to the team, or more team members in the team can give feedback data to the target product and/or the corresponding quantity, the feedback data comprises replacement of the target product and/or the corresponding quantity, deletion of the target product and/or the corresponding quantity, addition of the target product and/or the corresponding quantity, suggestions about the target product and/or the corresponding quantity, and the like.

According to an embodiment of the present disclosure, when the team task data includes a delivery target place, the task processing method further includes the steps of: determining a target product provider according to the target product in the order of the target product combination; and scheduling a delivery resource to deliver the target product from the target product provider to the delivery destination. The server 101 may determine a target product provider of the target product based on historical data (e.g., preference data of team members for the target product provider), and after determining the target product provider, may schedule the delivery resource to deliver the target product from a different target product provider to a delivery destination designated by the team.

Fig. 7 shows a flowchart of a task processing method according to an embodiment of the present disclosure, which is performed on the server 101 side. As shown in fig. 7, the task processing method includes the following steps S701 to S703:

in step S701, team task data and team characteristic data of team members in a team task are obtained, wherein the team task data comprises th product type set, the total number of the team members and product limiting conditions, and the characteristic data comprises a second product type set and a corresponding relation between a second product type in the second product type set and the team members;

in step S702, for the second product type in the second product type set, determining a second number of candidate products according to the th number of the team members having correspondence with the second product type, forming a th candidate product set, wherein the second number is in direct proportion to the th number;

in step S703, a plurality of target products are determined from the th candidate product set according to the product limitation condition.

According to the embodiment of the present disclosure, a team may be groups composed of two or more team members, a team task may be tasks related to the team, for example, the requirement that the team members in the team need products customized through the internet platform where the server 101 is located, wherein the products may include services and/or articles, for example, a work team in a business customizes work meals for employees through the internet platform where the server 101 is located, or a team in the business organizes activities through the internet platform where the server 101 is located to customize activity props, prizes, or subject meals for participating members, etc. when the team has the requirement for customizing products, or more team tasks may be created by creating users in the team, for example, a team through the client 102, it should be understood that the embodiment of the present disclosure will be exemplified by creating a team task based on an existing team, but the present disclosure is not limited thereto, wherein the existing team members include a team having previously created similar team tasks, and thus, the creating users may directly determine team task data and team characteristic team task data of this time according to historical data.

According to an embodiment of the present disclosure, when a creating user creates a team task through the client 102, the client 102 may further obtain team feature data from the creating user, where the team feature data is used to represent requirement information of a team member for a subordinate type of an th product type, for example, the team feature data may include a second product type set and a corresponding relationship between a second product type in the second product type set and the team member, where the second product type set includes or more second product types, the second product type is a subordinate type of a th product type, and after the second product type is determined, a corresponding candidate product may be obtained through the second product type.

According to the embodiment of the disclosure, since the second product type set includes or more second product types, and each second product type has a corresponding correspondence relationship with team members, that is, the number of team members preferring the second product type is , the 1 th candidate product of the second product type can be determined based on the 0 th number, all th candidate products corresponding to the second product type can be determined as the th candidate product set, wherein the th candidate product is the second number, and there can be an association relationship, such as a direct relationship, between the second number and the th number, the embodiment of the disclosure will be described by taking a team task as a group activity meal, and the second number is 10 times the number, for example, assuming 5-person hamburger and 5-person favorite steak, then the th candidate product corresponding to hamburger is 50 salsa, the th candidate product corresponding to hamburger is 50, and the th candidate product set is 50 { 50.52.

Similar to the implementation shown in step S401, according to an embodiment of the present disclosure, the step S702 of determining a second number of candidate products according to an th number of team members having a correspondence with the second product type to form a th candidate product set for the second product type in the second product type set may be implemented to determine the th candidate product according to historical data of the team members having a correspondence with the second product type, wherein the historical data includes data generated when the team members acquire products of the second product type within a historical period of time.

For details of the foregoing implementation, reference may be made to the above description of the implementation shown in step S401, and details are not described here.

Similar to the implementation shown in fig. 5, according to an embodiment of the present disclosure, the determining th candidate product according to the historical data of the team member having a correspondence with the second product type may be implemented as:

Specific implementation details of the foregoing implementation may be described with reference to the implementation shown in fig. 5, and are not described here again.

Similar to the implementation shown in fig. 6, according to the embodiment of the present disclosure, the product limitation condition includes a total cost of the products to be acquired by the team task, and the step S703 of determining a plurality of target products from the th candidate product set according to the product limitation condition may be implemented as:

Specific implementation details of the foregoing implementation may be described with reference to the implementation shown in fig. 6, and are not described here again.

Similar to the implementation shown in step S603, according to an embodiment of the present disclosure, the determining th candidate product of the candidate product combinations as the target product according to the historical data of the team member may be implemented by determining the target product according to the tendency feature value of the team member to the th candidate product of the candidate product combinations.

The specific implementation details of the foregoing implementation have been described in step S603, and are not described here again.

Fig. 8 shows a flowchart of a task processing method, which is performed at the client 102, according to an embodiment of the present disclosure. As shown in fig. 8, the task processing method includes the following steps S801 to S803:

in step S801, in response to a request for creating a team task by a creating user, outputting a providing page of team task data to a client of the creating user;

in step S802, determining team task data and an acquisition mode of team characteristic data according to the content input by the creating user on the providing page, wherein the team task data comprises th product type set and the total number of members of a team;

in step S803, when the team feature data is obtained from a team member, the feature obtaining link is sent to a client of the team member, so that the team member can provide an answer according to the data collection question pointed by the feature obtaining link.

According to an embodiment of the present disclosure, a team may be groups of two or more team members, a team task may be tasks involved by the team, for example, the team members in the team commonly need the requirement of a product customized through the internet platform where the server 101 is located, wherein the product may include services and/or articles, for example, a certain work team in an enterprise customizes work meals for employees through the client 102 to the internet platform where the server 101 is located, or a certain team in the enterprise organizes activities through the client 102 to the internet platform where the server 101 is located, customizes activity props, prizes or theme meals for participating members, etc. when the team has the requirement of a customized product, or more team tasks may be created through the client 102 by a creating user, such as a team in the team, and the client 102 of the creating user outputs a providing page of team task data to the client 102 of the creating user in response to the request of the creating user for creating a team task, wherein the team task data includes data related to the team task.

According to the embodiment of the disclosure, a creating user can input corresponding content on a providing page of team task data through a client 102, the input content comprises team task data, the team task data comprises a product type set and the total number of members of a team member, the product type set comprises or more product types, the product type can be a superior type of a product to be customized by the team task, the goal of the team task is to customize a product under a product type for the team member, and the total number of members can be the total number of team members in a team, the total number of team members can be determined through data provided by the creating user, and can also be determined through counting the number of persons who actively join the team, it should be understood that the disclosed embodiment exemplifies that the Internet platform where the server 102 is located is a meal ordering platform, the team task is a meal for a group activity, but the disclosure is not limited thereto, and the disclosure can also be applied to other application scenarios where the task processing can be performed by using the method provided by the disclosed embodiment, the total number of members is a sub-group activity set of a meal type , a food product type such as a snack product, a snack product type , a snack product type such as a snack product , a snack product type of a fruit product set such as a snack product set { a snack product of a fruit product of an Internet product of a fruit product, a snack product of a.

According to an embodiment of the present disclosure, the content that needs to be input by the creating user through the providing page of the team task data may further include whether the team characteristic data is directly provided by the creating user (for example, the creating user may collect the team characteristic data from the team members in advance) or needs to be acquired from the team members respectively, thereby determining the acquisition manner of the team characteristic data, when the team characteristic data needs to be acquired from the team members respectively, i.e., the acquisition manner of the team characteristic data is acquired from the team members, the server 101 may generate a data collection question according to th product type in the acquired team task data, wherein the data collection question includes a question for determining information on th product type demand of the team members, for example, service demand, product demand, merchant demand, cuisine taste demand, benefit sensitivity demand, price demand, resource demand, and the like, the data collection question may further include a fun question and/or personality test data, wherein the fun question may be used to improve enthusiasm of the team member's data collection question in order to improve enthusiasm of data collection questions on data, the team members's data collection question, the interest may be used to learn preference information from a plurality of different perspectives, since the product information on the team members may include URL type, the link data collection server 101, the link data collection server may be generated in accordance with the link address collection server 102, and the link address collection server 102, so that the team member may be provided to the link data collection server 102, so that the team characteristic data collection server 102 may be provided to the team members may be provided in accordance with the client terminal 102, thus, the link data collection server 102, the link to the link data collection server 102, thus, the team characteristic data collection server 102, the link server may be provided in this example, the link collection server may.

According to the embodiment of the disclosure, when a team task is created based on an existing team, that is, the team feature data is obtained from a creating user, the existing team refers to a team that has previously created a similar team task, the team feature data of the team task at this time can be determined according to historical team feature data, and at this time, the creating user can send the team feature data to the server 101 through the client 102.

According to the technical scheme provided by the embodiment of the disclosure, in response to a request of a creating user for creating a team task, a providing page of team task data is output to a client 102 of the creating user, then the team task data and an acquisition mode of the team characteristic data are determined according to content input by the creating user on the providing page, wherein the team task data comprises product type sets and the total number of members of a team member, when the acquisition mode of the team characteristic data is acquired from the team member, a characteristic acquisition link is sent to the client of the team member, so that the team member can provide answers to data collection questions pointed by the characteristic acquisition link.

Fig. 8 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 8, the task processing method further includes the following step S804:

in step S804, the team task data is sent to a server, and the feature acquisition link is received from the server.

According to an embodiment of the present disclosure, after the creating user determines the team task data, the team task data may be transmitted to the server 101 through the creating user's client 102, the server 101 generates a data collection question based on the th product type in the team task data, and transmits the generated data collection question to the creating user's client 102 through a link address, so that the creating user transmits the link address to the or more other team member's clients 102 through the client 102.

Fig. 8 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 8, the task processing method further includes the following steps S805 to S806:

in step S805, the answer of the data collection question is sent to a server side, and team characteristic data and/or at least target product combinations of team members are received from the server side, wherein the characteristic data comprise a second product type set and the corresponding relation between a second product type in the second product type set and the team members, the second product type is a subordinate type of a product type in a product type set, and the target product combinations comprise target products under the second product type and corresponding quantity;

in step S806, the team characteristic data and/or the target product combination is output to the client of the creating user.

According to an embodiment of the present disclosure, after the server 101 acquires the candidate answers of the team members, feature data of each team member may be determined for the candidate answers of each team member, and then, from the feature data of all team members who provide the candidate answers, the team feature data may be determined, wherein the feature data is used to represent preference information of the team member for a second product type that is a subordinate type of the product type, for example, the feature data may include a second product type set including or more second product types and a correspondence of the second product type to the team member in the second product type set, and the correspondence of the second product type to the team member may include the number of team members who prefer each second product type.

After determining the team mission data and the team characteristics data, according to the embodiments of the present disclosure, the server 101 may determine candidate products according to the team characteristics data, i.e., determine candidate second product types and corresponding relations of each second product type to different team members, and then determine at least target product combinations to be obtained by the team mission according to the team mission data, i.e., target products of the second product types and corresponding relations of the target products to the different team members, the number of target products of the same product type may be less than or equal to the total number of members of the team members, and the number of target products of the same second product type may be greater than or equal to the number of team members having corresponding relations to the second product types, the server may further transmit the determined team characteristics data and/or at least target product combinations to the client 102 of the creating user.

Fig. 8 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 8, the task processing method further includes the following step S807:

in step S807, in response to the selection request of target product combinations by the creating user, an order corresponding to the target product combination is requested to be generated from a server side.

According to an embodiment of the present disclosure, when the server 101 sends at least target product combinations to the client 102 of the creating user, the client 102 may also send at least target product combinations to the clients 102 of other team members so that the team members give feedback data for at least target product combinations, the feedback data including selecting target product combinations thereof, or for target products in the target product combinations, replacing target products and/or corresponding quantities, deleting target products and/or corresponding quantities, adding target products and/or corresponding quantities, suggestions about target products and/or corresponding quantities, etc. the client 102 of the creating user determines a selection request according to the received feedback data and sends the selection request to the server 101 so that the server 101 generates an order corresponding to the selected target product combinations according to the request.

Fig. 8 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 8, the task processing method further includes the following step S808:

in step S808, in response to a request to join a created team task, status data of the team task is returned to the client that sent the request.

According to an embodiment of the present disclosure, since the created team task may be in different states, for example, a create task state, a state of sending a feature acquisition link, a state of receiving data collection question answers and a state of determining a target product combination, etc., after responding to a request of the created team task, the creating user may send state data of the created team task to the clients 102 of other team members through the clients 102.

Fig. 9 is a schematic diagram of an application scenario of a task processing method according to an embodiment of the present disclosure, as shown in fig. 9, the application scenario includes a server 901, a creating user client 902A, and other team member clients 902B, for convenience of description, only servers 901, clients 902A, and clients 902B are drawn in the application scenario of fig. 12, it should be understood that this example is used only as an example, and is not a limitation to the present disclosure, and the number, kinds, and connection manners of the servers 901, the clients 902A, and the clients 902B in the present disclosure may be set according to actual needs, and the present disclosure is not particularly limited thereto.

A creating user creates a team task through a client 902A, determines team task data, and sends the team task data to a server 901;

the server 901 generates a data collection problem based on the acquired team task data and sends the data collection problem to the client 902A of the creating user;

the creating user sends data collection questions to clients 902B of other team members through the clients 902A;

other team members input candidate answers to the data collection question through the client 902B, and send the candidate answers to the data collection question to the server 901;

the server 901 determines team feature data based on the candidate answers to the data collection questions, determines a target product combination to be acquired by a team task based on the team task data and the team feature data, wherein the target product combination comprises target products and corresponding quantities, and then sends the target product combination to the client 902A of the creating user;

creating a client 902B for the user to send the target product combination to other team members through the client 902A;

other team members input feedback data aiming at the target product combination through the client 902B and send the feedback data to the client 902A of the creating user;

the creating user sends the feedback data to the server 901 through the client 902A;

the server 901 determines an order corresponding to the target product combination based on the feedback data and the target product combination, and schedules a delivery resource to deliver the target product from the target product provider to a delivery destination.

Fig. 10 shows a block diagram of a task processing device 1000 according to an embodiment of the present disclosure, wherein the device may be implemented as part or all of an electronic device by software, hardware, or a combination of both, as shown in fig. 10, the data processing device includes an th acquisition module 1001, a th generation module 1002, and a th output module 1003, wherein:

the acquisition module 1001 configured to acquire team task data, wherein the team task data comprises a product type set and a total number of members of a team;

the generation module 1002 configured to generate data collection questions from the team task data;

the output module 1003 is configured to output the data collection question to clients of at least team members, so as to obtain team feature data of the team members from answers to the data collection question by the team members, wherein the team feature data includes a second set of product types and a corresponding relationship between a second product type in the second set of product types and the team members, and the second product type is a subordinate type of a th product type in the product type set.

According to an embodiment of the disclosure, generating a data collection question according to the team task data includes:

According to an embodiment of the present disclosure, further comprising:

an receiving module 1004 configured to receive the candidate answers selected by at least team members for the data collection question;

an th determining module 1005 configured to determine team feature data of the team members from the candidate answers.

According to an embodiment of the present disclosure, further comprising:

a second determining module 1006, configured to determine a target product combination to be obtained by a team task according to the team task data and the team feature data; wherein the target product combination comprises target products and corresponding quantities under the second product type.

According to an embodiment of the present disclosure, the team task data further includes product constraints; the step of determining the target product combination to be acquired by the team task according to the team task data and the team characteristic data comprises the following steps:

According to an embodiment of the present disclosure, the determining, for the second product type in the second set of product types, a second number of th candidate products according to an th number of the team members having a correspondence with the second product type, forming a th candidate product set, includes:

According to an embodiment of the present disclosure, the determining th candidate product from the historical data of the team members having a correspondence with the second product type includes:

According to the embodiment of the disclosure, the product limitation condition comprises the total cost of the products to be acquired by the team task, and the step of determining a plurality of target products from the candidate product set according to the product limitation condition comprises the following steps:

According to an embodiment of the present disclosure, said determining said candidate product of said candidate product combinations as said target product according to said team member's historical data comprises:

The data updating apparatus in the embodiment of the present disclosure corresponds to of the task processing method described in the embodiment and the related embodiment shown in fig. 2, and for specific details, reference is made to the task processing method shown in fig. 2, which is not described herein again.

Fig. 11 illustrates a block diagram of a task processing device 1100 according to an embodiment of the present disclosure. The apparatus may be implemented as part or all of an electronic device through software, hardware, or a combination of both. As shown in fig. 11, the data processing apparatus includes a second obtaining module 1101, a third determining module 1102, and a fourth determining module 1103, wherein:

the second obtaining module 1101 is configured to obtain team task data and team characteristic data of team members in a team task, wherein the team task data comprises an th product type set, the total number of members of the team members and product limitation conditions, and the characteristic data comprises a second product type set and a corresponding relationship between a second product type in the second product type set and the team members;

the third determining module 1102 is configured to determine, for the second product type in the second set of product types, a second number of candidate products according to an th number of the team members having a correspondence with the second product type, forming a th set of candidate products, wherein the second number is in direct proportion to the th number;

the fourth determining module 1103 is configured to determine a plurality of target products from the th candidate product set according to the product limitation condition.

Determining a plurality of target products from the th candidate product set according to the product constraints, including:

The data updating apparatus in the embodiment of the present disclosure corresponds to of the task processing method in the embodiment shown in fig. 7 and the related embodiments, and for specific details, reference is made to the task processing method shown in fig. 7, which is not described herein again.

Fig. 12 shows a block diagram of a task processing device 1200 according to an embodiment of the present disclosure, wherein the device may be implemented as part or all of an electronic device by software, hardware, or a combination of both, as shown in fig. 12, the data processing device includes a second output module 1201, a fifth determination module 1202, and an sending module 1203, wherein:

the second output module 1201 configured to output a providing page of team task data to a client of a creating user in response to a request of the creating user for creating a team task;

the fifth determining module 1202 is configured to determine team task data and an acquisition mode of team feature data according to the content input by the creating user on the providing page, wherein the team task data comprises th product type sets and the total number of team members;

the sending module 1203 is configured to send a characteristic obtaining link to a client of a team member when the team characteristic data is obtained from the team member, so that the team member can provide an answer according to a data collection question pointed by the characteristic obtaining link.

According to an embodiment of the present disclosure, further comprising:

a second sending module 1204, configured to send the team task data to a server, and receive the feature acquisition link from the server.

According to an embodiment of the present disclosure, further comprising:

a second receiving module 1205 configured to send the answer to the data collection question to a server, and receive team member feature data and/or at least target product combinations from the server, where the feature data includes a second set of product types and a corresponding relationship between a second product type in the second set of product types and a team member, the second product type is a subordinate type of a product type in the product type set, and the target product combinations include target products under the second product type and corresponding quantities;

a third output module 1206 configured to output the team characteristic data and/or the target product combination to the client of the creating user.

According to an embodiment of the present disclosure, further comprising:

a second generating module 1207, configured to respond to the selected request of the creating user for target product combinations, and request a server side to generate an order corresponding to the target product combination.

According to an embodiment of the present disclosure, further comprising:

a return module 1208 configured to, in response to a request to join a created team task, return status data for the team task to the client that sent the request.

The data updating apparatus in the embodiment of the present disclosure corresponds to of the task processing method in the embodiment shown in fig. 8 and the related embodiments, and for specific details, reference is made to the task processing method shown in fig. 8, which is not described herein again.

The present disclosure discloses kinds of electronic devices, and fig. 13 shows a block diagram of a structure of an electronic device 1300 according to an embodiment of the present disclosure.

As shown in fig. 13, the electronic device 1300 includes a memory 1301 and a processor 1302; wherein the content of the first and second substances,

the memory 1301 is used to store or more computer instructions, wherein the or more computer instructions are executed by the processor 1302 to implement the method steps of:

generating a data collection problem according to the team task data;

The present disclosure discloses electronic devices comprising a memory and a processor, wherein,

the memory for storing or more computer instructions, wherein the or more computer instructions are executed by the processor to implement the method steps of:

As shown in fig. 14, the computer system 1400 includes a Central Processing Unit (CPU)1401 which can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM)1402 or a program loaded from a storage portion 1408 into a Random Access Memory (RAM) 1403. In the RAM1403, various programs and data necessary for the operation of the system 1400 are also stored. The CPU1401, ROM1402, and RAM1403 are connected to each other via a bus 1404. An input/output (I/O) interface 1405 is also connected to bus 1404.

The following components are connected to the I/O interface 1405: an input portion 1406 including a keyboard, a mouse, and the like; an output portion 1407 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker and the like; a storage portion 1408 including a hard disk and the like; and a communication portion 1409 including a network interface card such as a LAN card, a modem, or the like. The communication section 1409 performs communication processing via a network such as the internet. The driver 1410 is also connected to the I/O interface 1405 as necessary. A removable medium 1411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1410 as necessary, so that a computer program read out therefrom is installed into the storage section 1408 as necessary.

For example, embodiments of the present disclosure include computer program products comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for performing the above-described object class determination method.

It should also be noted that, in some alternative implementations, the functions noted in the blocks 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, and it may also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, may be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or by programmable hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, the present disclosure also provides kinds of computer readable storage media, which may be computer readable storage media included in an electronic device or a computer system in the above-described embodiments, or computer readable storage media separately existing and not assembled into a device.

The foregoing description is only exemplary of the preferred embodiments of the disclosure 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 in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims

1, A task processing method, comprising:

generating a data collection problem according to the team task data;

2, task processing methods, which are characterized by comprising:

The task processing method of , comprising:

The task processing device of , comprising:

5, electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to perform the method steps of:

generating a data collection problem according to the team task data;

An electronic device of comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to perform the method steps of:

An electronic device of 7, , comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to perform the method steps of:

A computer readable storage medium , having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, perform the method steps of claim 1.

A computer readable storage medium , having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, perform the method steps of claim 2.

10, computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, implement the method steps of claim 3.