CN110738554B

CN110738554B - Task processing method and device, electronic equipment and computer readable storage medium

Info

Publication number: CN110738554B
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: 2023-01-24
Anticipated expiration: 2039-10-28
Also published as: CN110738554A

Abstract

The embodiment of the disclosure discloses a task processing method, a task processing device, electronic equipment and a computer-readable storage medium, wherein the task processing method comprises the steps of acquiring team task data; wherein the team task data comprises a first set of product types and a total number of members of a team member; generating a data collection problem according to the team task data; outputting the data collection question to a client of at least one team member so as to obtain team characteristic data of the team member from answers of the team member to the data collection question. According to the embodiment of the data collection method and the data collection system, the data collection problems are generated through the number of team members in the team tasks and team task data such as the superior types of products to be customized, and then the respective characteristic data are collected from the team members through the data collection problems in a question-and-answer mode.

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 a task processing method and apparatus, an electronic device, and a computer-readable storage medium.

Background

With the development of internet technology, more and more product providers provide products to users or teams through internet platforms. When a team customizes a product for a user through an internet platform, one or more product providers are generally determined in advance, and then the product is determined from among the one or more product providers. When a team determines a product provider, although the process is simple and the cost is easy to control, users in the team have personalized differences, so that all users are difficult to satisfy; when a team determines a plurality of product providers, although the preferences of most users in the team can be considered, the product needs to be customized for each product provider, the process is complex, and the cost is not easy to control.

Disclosure of Invention

In order to solve the problems in the related art, embodiments of the present disclosure provide a task processing method and apparatus, an electronic device, and a computer-readable storage medium.

In a first aspect, a task processing method is provided in an embodiment of the present disclosure.

Specifically, the task processing method includes:

acquiring team task data; wherein the team task data comprises a first set of product types and a total number of members of a team member;

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

outputting the data collection question to a client of at least one team member so as to obtain team characteristic data of the team member from answers of the team member to the data collection question; 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 team members; the second product type is a subordinate type of the first product type in the first product type set.

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

determining at least one second product type under a first product type according to the first product type 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 first implementation manner of the first aspect, in a second implementation manner of the first aspect, the present disclosure further includes:

receiving the candidate answers selected by at least one team member 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 first aspect, in a third implementation manner of the first aspect, the present disclosure further includes:

determining 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 first aspect, in a fourth implementation manner of the first aspect, the team task data further includes a product limitation condition; 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:

for the second product type in the second product type set, determining a second number of first candidate products according to the first number of the team members having the corresponding relation with the second product type to form a first candidate product set; wherein the second number is in direct proportion to the first number;

determining a plurality of target products from the first candidate product set according to the product limitation condition.

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

determining the first 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 by the team member when obtaining products of the second product type over a historical period of time.

With reference to the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the determining the first candidate product according to the historical data of the team member having a corresponding relationship 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 the first candidate product from the second candidate products according to the tendency feature value.

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

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

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

determining the first candidate product in one of the candidate product combinations as the target product according to the historical data of the team members.

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

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

In a second aspect, a task processing method is provided in an embodiment of the present disclosure.

Specifically, the task processing method includes:

acquiring team task data and team characteristic data of team members in a team task; the team task data comprises a first 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 the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of the first product type in the first product type set;

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

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

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

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

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

forming a plurality of different candidate product combinations according to the first candidate product selected from the first 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, according to the historical data of the team members, the first candidate product in one of the candidate product combinations as the target product includes:

In a third aspect, an embodiment of the present disclosure provides a task processing method.

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 creation user on the provided page; wherein the team task data comprises a first set of product types and a total number of members of a team member;

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 a first 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 first implementation manner of the third aspect, in a second implementation manner of the third aspect, the present disclosure further includes:

sending answers to the data collection questions to a server side, and receiving team characteristic data of team members and/or at least one target product combination from the server side; 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 team members; the second product type is a subordinate type of a first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity;

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 one of the target product combinations, and requesting a server side to generate an order corresponding to the target product combination.

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, a task processing device is provided in an embodiment of the present disclosure.

Specifically, the task processing device includes:

a first acquisition module configured to acquire team task data; wherein the team task data comprises a first set of product types and a total number of members of a team member;

a first generation module configured to generate a data collection question from the team task data;

a first output module configured to output the data collection question to a client of at least one team member to obtain team feature data of the team member from an answer to the data collection question by the team member; wherein the team characteristic 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 a team member; the second product type is a subordinate type of the first product type in the first product type set.

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

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

a first receiving module configured to receive the candidate answer selected by at least one team member for the data collection question;

a first determination module configured to determine team feature data of the team members from the candidate answers.

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 restrictions; 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 product type set, a second number of first candidate products according to the first number of team members having a corresponding relationship with the second product type to form a first 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 first candidate product according to the historical data of the team members 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,

the product constraints include a total cost of the product to be acquired by the team mission; the determining a plurality of target products from the first candidate product set according to the product limitation condition comprises:

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

In a fifth aspect, a task processing device is provided in the embodiments of the present disclosure.

Specifically, the task processing device includes:

the second acquisition module is configured to acquire team task data and team characteristic data of team members in a team task; the team task data comprises a first product type set, the total number of members of a team member and product limitation conditions, and the characteristic data comprises a second product type set and the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of the first product type in the first product type set;

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

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

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

determining the first candidate product according to historical data of the team members having a corresponding relationship with the second product type; wherein the historical data comprises data generated by the team member when obtaining products of the second product type over a historical period of time.

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

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

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

In a sixth aspect, a task processing device is provided in an embodiment 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, according to the content input by the creating user on the providing page, how to acquire team task data and team feature data; wherein the team task data comprises a first set of product types and a total number of members of a team member;

the first sending module is configured to send the 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 answers according to data collection questions pointed by the characteristic obtaining link.

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

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

With reference to the first 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 of the data collection questions to a server side, and receive team characteristic data and/or at least one target product combination of team members from the server side; 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 team members; the second product type is a subordinate type of the first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity;

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 one of the target product combinations, and request the server side to generate an order corresponding to the target product combination.

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 an electronic device, 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;

outputting the data collection question to a client of at least one team member so as to obtain team characteristic data of the team member from answers of the team member to the data collection question; wherein the team characteristic 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 a team member; the second product type is a subordinate type of the first product type in the first set of product types.

In an eighth aspect, the disclosed embodiments provide an 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 implement the following method steps:

In a ninth aspect, the disclosed embodiments provide an 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 implement the method steps of:

In a tenth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, on which computer instructions are stored, and when executed by a processor, the computer instructions implement the method according to any one of the first aspect, the first implementation manner to the eighth implementation manner of the first aspect.

In an eleventh aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, implement the method according to any one of the second aspect, the first implementation manner to the fourth implementation manner of the second aspect.

In a twelfth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, implement the method according to any one of the third aspect, the first implementation manner to the fourth implementation manner of the third aspect.

According to the technical scheme provided by the embodiment of the disclosure, after team task data are acquired, the team task data comprise a first product type set and the total number of members of a team, a data collection question is generated according to the team task data, the data collection question is output to a client of at least one team member, so that team characteristic data of the team member are acquired from answers to the data collection question by the team member, 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 member, and the second product type is a lower type of a first product type in the first product type set. According to the embodiment of the data collection method and the data collection system, the data collection problems are generated through the number of team members in the team tasks and team task data such as the superior types of products to be customized, and then the respective characteristic data are collected from the team members through the data collection problems in a question-and-answer mode.

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 combination to be captured by a team task based on the team task data and the team feature data, in accordance with an embodiment of the disclosure;

FIG. 5 illustrates a flow diagram for determining the first candidate product from 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 the first candidate product from 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, numerals, steps, actions, components, parts, or combinations thereof in the specification, and are not intended to preclude the possibility that one or more other features, numerals, steps, actions, components, parts, or combinations thereof are 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 embodiments of the present disclosure includes at least one first computer device and at least one second computer device, where the at least one first computer device and the at least one second computer device are connected through a network, for example, through a wired or wireless network connection, etc.; the first computer device may be an internet platform end device such as a server or a cloud computing platform, for example, a single server may be used, or a server cluster composed of a plurality of servers may be used; the second computer device may be a client device, such as a laptop, tablet, or smart phone. It should be understood that the number, type and specific connection manner of the first computer device and the second computer device are determined according to the specific application requirements, and the disclosure is not particularly limited.

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

FIG. 1 shows a task processing system schematic according to an embodiment of the present disclosure. As shown in fig. 1, the task processing system includes at least one server 101 and at least one mobile phone and/or computer client 102, wherein the at least one server 101 and the at least one mobile phone and/or computer client 102 are connected via a limited or wireless network, the at least one server 101 can be used to obtain team task data and perform team task processing, and the at least one mobile phone and/or computer client 102 can be used to interact with users such as a group leader (a creation user of a team task), team members, etc., obtain team task data from the group leader, obtain answers to data collection questions from the team members, etc., and output team task processing results to the group leader, the team members, etc.

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 is acquired; wherein the team task data comprises a first set of product types and a total number of members of a team member;

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

in step S203, outputting the data collection question to a client of at least one team member so as to obtain team feature data of the team member from an answer of the team member to the data collection question; wherein the team characteristic 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 a team member; the second product type is a subordinate type of the first product type in the first product type set.

According to the embodiment of the disclosure, a team can be a group consisting of two or more team members, a team task can be a task related to the team, for example, the team members in the team need to customize a product through the internet platform where the server 101 is located, wherein the product can include a service and/or an article, for example, a certain work team in an enterprise customizes a work meal for employees through the internet platform where the server 101 is located, or a certain team in the enterprise customizes activity props, prizes or subject meals for participating members through the internet platform where the server 101 is located when organizing activities. When a team has a demand for a customized product, one or more team tasks may be created by a creating user in the team, such as a team leader, through the client 102, it should be understood that the disclosed embodiments will be exemplified by creating a team task based on a new team, but the disclosure is not limited thereto.

According to embodiments of the disclosure, when a creating user creates a team task through the 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 at that time, such as a first set of product types and a total number of members of the team, wherein the first set of product types includes one or more first product types. The first product type may be a superior type of product to be customized for the team task, and the goal of the team task is to customize the product under the first product type for team members, while the total number of members may be the total number of team members in the team. The total number of team members can be determined by creating data provided by the user, or by counting the number of people actively joining the team. It should be understood that, in the embodiment of the present disclosure, the internet platform where the server 101 is located is taken as a meal ordering platform, and the team task is taken as a group activity meal, which is exemplified, but the present disclosure is not limited thereto, and the present disclosure may also be applied to other application scenarios where task processing can be performed by using the method proposed in the embodiment of the present disclosure. The total number of members may be the total number of members participating in the group campaign; the first product type may be a first category of meal items such as staple food, dishes, fruits, desserts, beverages, snacks, and the like; the first set of product types includes one or more first product types, e.g., the first set of product types is { staple food, dish, beverage }.

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 a first product type in the acquired team task data, wherein the data collection problem includes a problem for determining information of the requirement of the team members on the first product type, for example, a service requirement, a product requirement, a merchant requirement, a dish taste requirement, a preferential sensitivity, a price requirement, a resource requirement, and the like. The data collection questions may also include interest questions to increase the enthusiasm of team members to respond to the data collection questions and/or personality test data to learn about team member needs from a number of different perspectives. Because the first set of products includes one or more first product types, a different data collection problem may be generated for each first product type, respectively.

According to embodiments of the present disclosure, the server 101 may send the generated data collection problem to the team member's client. In some embodiments, the server 101 may send a link address where the data collection problem is located to the client 102 of the creating user, the creating user obtains part or all of the data collection problem from the link address through the client 102, and the creating user may further forward the link address to the client 102 of one or more other team members through the client 102, so as to implement outputting the data collection problem to the client 102 of at least one team member. The team member who acquires the data collection question may give corresponding answers to different data collection questions according to needs of the team member, and send the answers to the server 101, so that the server 101 may acquire team feature data of the team member according to the answers, where the team feature data is used to represent information on needs of the team member for a subordinate type of the first product type, for example, the team feature data may include a second product type set and a correspondence between the second product type in the second product type set and the team member, where the second product type set includes one or more second product types, the second product type is a subordinate type of the first product type, and after the second product type is determined, a corresponding candidate product may be obtained through the second product type. The correspondence of the second product type to the team members may include a mapping between the second product type and the team members who require the second product type.

According to the technical scheme, after team task data are obtained, the team task data comprise a first product type set and the total number of team members, a data collection question is generated according to the team task data, the data collection question is output to a client of at least one team member, so that team characteristic data of the team member are obtained from answers of the team member to the data collection question, 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 member, and the second product type is a subordinate type of a first product type in the first product type set. According to the embodiment of the data collection method and the data collection system, the data collection problems are generated through the number of team members in the team tasks and team task data such as the superior types of products to be customized, and then the respective characteristic data are collected from the team members through the data collection problems in a question-and-answer mode.

FIG. 3 illustrates a flow diagram for generating a data collection question from the team task data according to an embodiment of the 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 one second product type under a first product type according to the first product type in the team task data;

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

According to the embodiment of the disclosure, since the first product types are first-level categories of the products, and each first product type includes one or more second product types, in order to know more accurate demand information of different team members for the first product type, at least one second product type under the first product type may be determined first, and then a data collection problem may be generated for the second product type, so as to obtain the degree of inclination of different team members for each different second product type, and the higher the degree of inclination, the more the team members tend to customize the corresponding second product type. In order to improve convenience of team members in answering a data collection question, a plurality of candidate answers to the data collection question may be provided while the data collection question is provided, and in addition, team members may be allowed to freely supplement other candidate answers. The embodiments of the present disclosure will be described with respect to a team task as a group active meal, and a first set of product types including a staple food, a dish, and a beverage as an example, a second set of product types of a staple food may be determined, and then a data collection question and a plurality of corresponding candidate answers may be generated for the staple food, such as:

(1) Are 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 biscuits better eaten when put together? A will and B will not occur; \8230 \ 8230

The data collection question (4) is a funny question, bread and biscuits are not influenced mutually, but user attributes of team members can be determined according to the funny answer, for example, the team member selecting the answer A is a partial team member; while team members who select answer B are typically biased team members.

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:

in step S204, receiving the candidate answer selected by at least one team member for the data collection question;

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 the candidate answers of the team members, the feature data of each team member may be determined for the candidate answer of each team member, and then the team feature data may be determined according to the feature data of all team members who provide the candidate answers. 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) salad: 5 people prefer kaesar salads, 5 people prefer mediterranean salads; (2) beefsteak: 5 people like western cold steak, 2 people like phenanthrene steak, and 3 people like naked eye steak, and can determine team characteristic data, namely the second product type set is { Kaisashara, mediterranean salad, western cold steak, phenanthrene steak, naked eye steak }, and the corresponding relationship between the second product type and team members is as follows: 5 people prefer kaesar salad, 5 people prefer mediterranean salad, 5 people prefer western cold steak, 2 people prefer fiil steak, and 3 people prefer naked eye steak.

Fig. 2 shows 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 products 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 of determining a target product combination to be acquired by a 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 number of first candidate products according to the first number of the team members having a corresponding relationship with the second product type, forming a first candidate product set; wherein the second number is in direct proportion to the first number;

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

According to an embodiment of the disclosure, since the second product type set includes one or more second product types, and each second product type has a corresponding correspondence with the team members, that is, the number of team members preferring the second product type is a first number, a first candidate product of the second product type may be determined based on the first number, and first candidate products corresponding to all second product types may be determined as the first candidate product set, where the number of first candidate products is a second number, and there may be an association, such as a direct ratio, between the second number and the first number. The embodiment of the disclosure will be described by taking a team task as a group to build an active meal, and taking the second number 10 times as large as the first number as an example, for example, assuming that 5 people prefer hamburgers and 5 people prefer steaks, the first candidate product corresponding to hamburgers is 50 hamburgers, the first candidate product corresponding to steaks is 50 steaks, and the first candidate product set is {50 hamburgers and 50 steaks }.

According to an embodiment of the disclosure, the number of the first candidate products included in the first candidate product set is greater, and therefore, some first candidate products in the first candidate product set may be determined as target products according to product limitation conditions, and when determining the target products, the number of the target products belonging to the same second product type may be smaller than or equal to the first number corresponding to the second product type, and the number of the target products belonging to the same first product type may be smaller than or equal to the total number of team members. It can be understood that, ideally, the target products belonging to the same second product type correspond to the first quantity of the second product type, as in the group building ordering task described above, if the team feature data includes 5 team members corresponding to the second product type "hamburger", the final target products may include 5 hamburger products, and the main food type is the first product type, and of course, for cost control, the quantity of the target products belonging to the same second product type may be smaller than the first quantity corresponding to the second product type; furthermore, the first product type may be a product type under which each team member needs to customize a target product, for example, in a group meal ordering task, the staple food is the first product type, and each team member needs to customize a staple food, so the number of target products belonging to the same first product type may be equal to the total number of team members, although it is understood that if the number belonging to the same first product type is less than the total number of team members, for cost control, it may happen.

According to an embodiment of the present disclosure, the step S401 of determining, for the second product type in the second product type set, a second number of first candidate products according to the first number of team members having a corresponding relationship with the second product type to form a first candidate product set may be implemented as: determining the first candidate product according to historical data of the team members having a corresponding relationship with the second product type; wherein the historical data comprises data generated by the team member when obtaining the product of the second product type over a historical period of time.

The obtaining mode of the historical data is not specifically limited, for example, click data, browsing data, ordering data and/or transaction data and the like in an internet platform of a customized product within a historical time period by a team member can be used, and associated data of different team members and products of a second product type, which have corresponding relations with the second product type, are extracted from the click data, browsing data, ordering data and/or transaction data and the like as historical data. From the historical data, trend characteristics of the team members for products of the second product type may be obtained, and the first candidate product may be further determined.

FIG. 5 illustrates a flow diagram for determining the first candidate product from historical data of the team members having a correspondence with the second product type according to an embodiment of the disclosure. As shown in fig. 5, the determining the first candidate product according to the historical data of the team members having corresponding relation with the second product type includes 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 first 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, and 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 the first candidate products according to the tendency characteristic value.

The method for determining the tendency characteristic value is not particularly limited in the 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 the tendency characteristic value of the team member for the product, the prediction model is trained through historical data, and after the prediction model is trained, the historical data of the team member for a second candidate product is input into 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 eigenvalue = 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 the calculation formula of the trend eigenvalue, and may be set according to an actual application scenario, and the disclosure does not specifically limit the calculation formula.

According to the embodiment of the disclosure, after the tendency characteristic value of each team member and each second candidate product corresponding to the second product type is determined, the tendency characteristic values of all team members and each second candidate product corresponding to the second product type are determined, that is, all team members add up the tendency characteristic values of each second candidate product, so as to determine the first candidate product according to the tendency characteristic values. For example, assuming that the second product type is steak, the second candidate product may be western cold steak, philippine steak, french steak, unaided steak, american steak, saute steak, and korean steak, and the first candidate product may be determined by determining the tendency characteristic value of the team member for the corresponding steak using the prediction model or the calculation formula of the tendency characteristic value according to historical data, such as one or more of click data, browsing data, order placing data, or transaction data of the team member for the 7 steaks.

FIG. 6 illustrates a flow diagram for determining the first candidate product from historical data of the team members having a correspondence with the second product type, according to an embodiment of the disclosure. As shown in fig. 6, the product limitation includes a total cost of the products to be acquired by the team task, and the step S402 of determining a plurality of target products from the first candidate product set according to the product limitation includes the following steps S601-S603:

in step S601, a first number of the first candidate products are selected from the first candidate product set corresponding to the second product type;

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

in step S603, the first candidate product in one of the candidate product combinations is determined as the target product according to the historical data of the team members.

According to the embodiment of the disclosure, a first number of first candidate products may be selected from a first candidate product set corresponding to a second product type according to a preset rule, the preset rule is not specifically limited by the disclosure, and the first number of first candidate products may be determined according to actual needs, for example, a first number of first candidate products may be selected according to a product price, a product sales volume or a product score of the first candidate products, for example, 2 favorite steaks, and two philia steaks may be selected from the first candidate product set on the assumption that the price of the philia steak is the lowest; for another example, 3 people prefer salads, and assuming that the sales of the kaiser salads are best, 3 kaiser salads may be selected from the first set of candidate products.

According to an embodiment of the disclosure, when the product limitation condition includes a total cost of the products to be obtained by the team mission, where 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 corresponding selected first candidate product, all the first candidate products corresponding to all the second product types may be combined to form a plurality of different candidate product sets, and a total value of the first candidate products included in the candidate product set is less than or equal to the total cost, meanwhile, a number of the first candidate products included in the candidate product set may be less than or equal to a total number of members, and a number of the first candidate products included in the candidate product set and belonging to the same second product type may be less than or equal to the first number. And then determining a first candidate product in one candidate product combination as a target product according to the historical data of the team members, wherein the number of the first candidate products is determined as the corresponding number of the target product.

According to an embodiment of the present disclosure, the step S603 of determining the first candidate product in one of the candidate product combinations as the target product according to the historical data of the team members may be implemented as: determining the target product according to the tendency characteristic value of the team member to the first candidate product in the candidate product combination.

According to the embodiment of the disclosure, the target candidate product combination can be determined according to the tendency characteristic value of the team member to the first candidate product in the candidate product combination according to the search algorithm, and then the first candidate product in the target candidate product combination is determined as the target product. The search algorithm is not particularly limited in the present disclosure, and examples thereof include a genetic algorithm, an ant colony algorithm, a greedy algorithm, a bee colony algorithm, and a particle swarm algorithm. In the following, a genetic algorithm will be used as an example, but the present disclosure is not limited thereto, and first, a candidate product combination is determined from a plurality of different candidate product combinations; secondly, determining the tendency characteristic value of the candidate product combination, namely the sum of the tendency characteristic values of all first candidate products in the candidate product combination; thirdly, iteration is carried out by using a genetic algorithm, the candidate product combination is continuously optimized, in the iteration process, the constraint condition to be met is that the total value of the first candidate product in the candidate product set is less than or equal to the total cost, and the optimization target is to improve the sum of the tendency characteristic values of the candidate product combination; finally, in the preset iteration time, the candidate product combination with the largest sum of the tendency characteristic values of the candidate product combinations is determined as the target candidate product combination, and the number of the first candidate products, namely the number of the target products and the number of the target products, can be determined after the target candidate product combination is determined.

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 an order of the target product combination according to the target product combination and the feedback data.

According to the requirement of a team for proposing a customized product, a target product combination, namely a target product and a corresponding quantity, can be recommended to the team, one or more team members in the team can give feedback data to the target product and/or the corresponding quantity, and the feedback data comprises: replacing the target product and/or the corresponding quantity, deleting the target product and/or the corresponding quantity, adding the target product and/or the corresponding quantity, suggestions regarding the target product and/or the corresponding quantity, etc. The server 101 determines the order of the target product combination, that is, the product and quantity finally purchased by the team through the internet platform where the server 101 is located, according to the feedback data. If the team is very satisfied with the target product combination and there is no feedback data, the server 101 may determine the order of the target product combination directly according to the target product combination.

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; the team task data comprises a first 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 the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of a first product type in the first product type set;

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

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

According to the embodiment of the disclosure, a team can be a group consisting of two or more team members, and a team task can be a task related to the team, for example, the team members in the team need to customize a product through the internet platform where the server 101 is located, wherein the product can include a service and/or an article, for example, a certain work team in an enterprise customizes a work order for employees through the internet platform where the server 101 is located, or a certain team in the enterprise customizes activity props, prizes, or subject meals for participating members through the internet platform where the server 101 is located when organizing activities. When a team has a demand for a customized product, one or more team tasks may be created by a creating user in the team, such as a captain, through client 102, it being understood that the disclosed embodiments will be illustrated by way of example and not limitation of the present disclosure based on the creation of team tasks based on existing teams, including teams that have previously created similar team tasks, so that the creating user may directly determine team task data and team characteristic data for the team task from historical data.

According to embodiments of the disclosure, when a creating user creates a team task through the 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 at that time, such as a first set of product types and a total number of members of the team, wherein the first set of product types includes one or more first product types. The first product type may be a superior type of product to be customized for the team task, and the goal of the team task is to customize the product under the first product type for team members, while the total number of members may be the total number of team members in the team. The total number of team members can be determined by creating data provided by the user, or by counting the number of people actively joining the team. It should be understood that, in the embodiment of the present disclosure, the internet platform where the server 101 is located is taken as a meal ordering platform, and the team task is taken as a group activity meal, which is exemplified, but the present disclosure is not limited thereto, and the present disclosure may also be applied to other application scenarios where task processing can be performed by using the method proposed in the embodiment of the present disclosure. The total number of members may be the total number of members participating in the group campaign; the first product type may be a first category of meal items such as staple food, dishes, fruits, desserts, beverages, snacks, and the like; the first set of product types includes one or more first product types, such as a first set of product types { staple food, dish, beverage }.

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 a first 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 one or more second product types, and the second product type is a subordinate type of the first product type, and after the second product type is determined, a corresponding candidate product may be obtained through the second product type. The correspondence of the second product type to the team members may include a mapping between the second product type and the team members who require the second product type.

According to an embodiment of the present disclosure, since the second product type set includes one or more second product types, and each second product type has a corresponding correspondence with the team member, that is, the number of team members preferring the second product type is a first number, a first candidate product of the second product type may be determined based on the first number, and first candidate products corresponding to all second product types may be determined as the first candidate product set, wherein the number of first candidate products is a second number, and there may be an association, for example, a direct ratio, between the second number and the first number. The embodiment of the present disclosure will be described by taking a team task as a group to build an active meal, and taking an example that the second number is 10 times the first number, for example, assuming that 5 people prefer hamburgers and 5 people prefer steaks, the first candidate product corresponding to hamburgers is 50 salad hamburgers, the first candidate product corresponding to steaks is 50 steaks, and the first candidate product set is {50 hamburgers and 50 steaks }.

According to an embodiment of the disclosure, the number of the first candidate products included in the first candidate product set is greater, and therefore, some first candidate products in the first candidate product set may be determined as target products according to product limitation conditions, and when determining the target products, the number of the target products belonging to the same second product type may be smaller than or equal to the first number corresponding to the second product type, and the number of the target products belonging to the same first product type may be smaller than or equal to the total number of team members. It is understood that, ideally, the target products belonging to the same second product type correspond to the first quantity of the second product type, and in the group building ordering task as described above, if the team feature data includes 5 team members corresponding to the second product type of "hamburger", the final target product may include 5 hamburger products, and the main food may be a first product type, and of course, for cost control, the quantity of the target products belonging to the same second product type may be smaller than the first quantity corresponding to the second product type; furthermore, the first product type may be a product type under which each team member needs to customize a target product, for example, in a group meal ordering task, the staple food is the first product type, and each team member needs to customize a staple food, so the number of target products belonging to the same first product type may be equal to the total number of team members, although it is understood that if the number belonging to the same first product type is less than the total number of team members, for cost control, it may happen.

Similar to the implementation manner shown in step S401, according to the embodiment of the present disclosure, the step S702, that is, for the second product type in the second product type set, determining a second number of first candidate products according to the first number of team members having a corresponding relationship with the second product type to form a first candidate product set, may be implemented as: determining the first 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 by the team member when obtaining products of the second product type over a historical period of time.

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

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

For details of the foregoing implementation, reference may be made to the description of the implementation shown in fig. 5, and details 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 first candidate product set according to the product limitation condition may be implemented as:

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

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 manner shown in step S603, according to an embodiment of the present disclosure, the determining the first candidate product in one of the candidate product combinations as the target product according to the historical data of the team member may be implemented as: determining the target product according to the tendency characteristic value of the team member to the first candidate product in the candidate product combination.

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 of a creating user for creating a team task, 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 feature data according to the content input by the creating user on the providing page; wherein the team task data comprises a first set of product types and a total number of members of a team member;

in step S803, when the team characteristic data is obtained from a team member, the characteristic 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 characteristic obtaining link.

According to the embodiment of the disclosure, a team can be a group consisting of two or more team members, a team task can be a task related to the team, for example, the team members in the team need to customize a product through the internet platform where the server 101 is located, wherein the product can include a service and/or an article, for example, a certain work team in an enterprise customizes a work meal for a worker to the internet platform where the server 101 is located through the client 102, or customizes an activity prop, a prize, a subject meal, and the like for a participating member to the internet platform where the server 101 is located through the client 102 when a certain team organizes an activity in the enterprise. When a team has a demand for a customized product, one or more team tasks may be created by a creating user in the team, for example, a team leader through the client 102, 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 a request of the creating user for the creating team task, wherein the team task data includes data related to this team task.

According to the embodiment of the disclosure, the creating user can input corresponding content on a providing page of team task data through the client 102, the input content comprises the team task data, wherein the team task data comprises a first product type set and the total number of members of a team member, and the first product type set comprises one or more first product types. The first product type may be a superior type of product to be customized for the team task, and the goal of the team task is to customize the product under the first product type for team members, while the total number of members may be the total number of team members in the team. The total number of team members can be determined by creating data provided by the user, or by counting the number of people actively joining the team. It should be understood that the embodiment of the present disclosure will be exemplified by taking the internet platform where the server 102 is located as a meal ordering platform and taking team tasks as group activity meals, but the present disclosure is not limited thereto, and the present disclosure may also be applied to other application scenarios where task processing can be performed by using the method proposed by the embodiment of the present disclosure. The total number of the members is the total number of the members participating in the group building activity; the first product type may be a first category of meal items such as staple food, dishes, fruits, desserts, beverages, snacks, and the like; the first set of product types includes one or more first product types, e.g., the first set of product types is { staple food, dish, beverage }.

According to the embodiment of the 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 feature data is directly provided by the creating user (for example, the creating user may collect the team feature data from team members in advance) or needs to be acquired from the team members respectively, so as to determine the acquisition mode of the team feature data. When team feature data needs to be acquired from team members respectively, that is, the team feature data is acquired from the team members, the server 101 may generate a data collection problem according to a first product type in the acquired team task data, where the data collection problem includes a problem for determining information required by the team members for the first product type, for example, a service requirement, a product requirement, a merchant requirement, a dish taste requirement, a preferential sensitivity requirement, a price requirement, a resource requirement, and the like. The data collection questions may also include interestingness questions to increase the team member's aggressiveness in responding to the data collection questions and/or personality test data to learn about team member's preference information from a number of different perspectives. Because the first set of products includes one or more first product types, a different data collection problem may be generated for each first product type, respectively. The server 101 may send the generated data collection questions to the team member's client. In some embodiments, the server 101 may send the link address where the data collection problem is located to the client 102 of the creating user, and the form of the link address is not particularly limited in the present disclosure, and may be, for example, a Uniform Resource Locator (URL). The creating user can also send the link address to the client 102 of one or more other team members through the client 102, so that the team members provide answers according to the data collection questions pointed by the link address, and the server 101 can acquire team feature data of the team members according to the answers.

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 feature data are determined according to content input by the creating user on the providing page, wherein the team task data comprises a first product type set and the total number of members of a team member, and when the acquisition mode of the team feature data is acquired from the team member, a feature acquisition link is sent to the client of the team member, so that the team member can provide answers according to data collection questions pointed by the feature acquisition link. The embodiment of the disclosure generates the data collection problem through the number of team members in the team task and the task target data such as the superior type of the product to be customized, and then collects respective characteristic data from the team members through the data collection problem in a question-and-answer mode, so that the team task processing efficiency is improved, the characteristic data of the team members are considered, and the team task processing result tends to be most reasonable.

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 disclosure, after the creating user determines the team task data, the creating user may send the team task data to the server 101 through the creating user's client 102, the server 101 generates a data collection question based on a first product type in the team task data, and sends the generated data collection question to the creating user's client 102 through a link address, so that the creating user sends the link address to one 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 to the data collection question is sent to a server, and team feature data and/or at least one target product combination of team members are received from the server; 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 team members; the second product type is a subordinate type of the first product type in the first product type set; the target product combination comprises 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 obtains the candidate answers of the team members, characteristic data of each team member may be determined for the candidate answers of each team member, and then, according to the characteristic data of all team members who provide the candidate answers, team characteristic data may be determined, wherein the characteristic data is used to represent preference information of the team members for a second product type of a subordinate type of the first product type, for example, the characteristic data may include a second product type set and a corresponding relationship of the second product type to the team members in the second product type set, wherein the second product type set includes one or more second product types, and the corresponding relationship of the second product type to the team members may include the number of team members who prefer each second product type.

According to an embodiment of the disclosure, after determining the team task data and the team feature data, the server 101 may determine candidate products according to the team feature data, that is, determine candidate second product types and corresponding relations between each second product type and different team members, and then determine at least one target product combination to be obtained by the team task according to the team task data, that is, a target product of the second product type and corresponding relations between the target product and different team members, where the number of target products belonging to the same first product type may be less than or equal to the total number of team members, and the number of target products belonging to the same second product type may be greater than or equal to the first number of team members having corresponding relations with the second product type. The server may also send the determined team characteristic data and/or the at least one target product combination 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 the creating user for one of the target product combinations, an order corresponding to the target product combination is requested to be generated from a server.

According to an embodiment of the present disclosure, when the server 101 sends at least one target product combination to the client 102 of the creating user, the client 102 may also send at least one target product combination to the clients 102 of other team members, so that the team members give feedback data for at least one target product combination, the feedback data including: selecting one of the target product combinations, or for a target product in the target product combination, replacing the target product and/or the corresponding quantity, deleting the target product and/or the corresponding quantity, adding the target product and/or the corresponding quantity, advising about the target product and/or the corresponding quantity, and the like. 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 combination 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 illustrating 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 one server 901, one client 902A, and one client 902B are drawn in the application scenario of fig. 12, it should be understood that this example is only used as an example, and is not a limitation to the present disclosure, and the number, the types, and the connection manners of the server 901, the client 902A, and the client 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 the team mission based on the team mission data and the team feature data, wherein the target product combination comprises target products and corresponding numbers, 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. 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. 10, the data processing apparatus includes a first acquisition module 1001, a first generation module 1002, and a first output module 1003, wherein:

the first obtaining module 1001 configured to obtain team task data; wherein the team task data comprises a first set of product types and a total number of members of a team member;

the first generating module 1002 configured to generate a data collection question from the team mission data;

the first output module 1003 is configured to output the data collection question to a client of at least one team member so as to obtain team feature data of the team member from an answer of the team member to the data collection question; 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 team members; the second product type is a subordinate type of the first product type in the first 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:

a first receiving module 1004 configured to receive the candidate answer selected by at least one team member for the data collection question;

a first 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 first candidate products according to the first number of team members having a correspondence with the second product type, forming a first set of candidate products, includes:

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

According to an embodiment of the present disclosure, the product constraints include a total cost of the product to be acquired by the team mission; the determining a plurality of target products from the first candidate product set according to the product limitation condition comprises:

According to an embodiment of the present disclosure, said determining said first candidate product in one of said candidate product combinations as said target product according to historical data of said team members comprises:

The data updating apparatus in the embodiment of the present disclosure corresponds to the task processing method described in the embodiment shown in fig. 2 and the related embodiments, 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 feature data of team members in a team task; the team task data comprises a first product type set, the total number of members of a team member and product limitation conditions, and the characteristic data comprises a second product type set and the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of a first product type in the first product type set;

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

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

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

According to an embodiment of the present disclosure, the product limit condition includes a total cost of the product to be acquired by the team mission; determining a plurality of target products from the first candidate product set according to the product constraints, including:

The data updating apparatus in the embodiment of the present disclosure corresponds to the task processing method described 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. 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. 12, the data processing apparatus includes a second output module 1201, a fifth determination module 1202, and a first transmission 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 content input by the creating user on the providing page; wherein the team task data comprises a first set of product types and a total number of members of a team member;

the first sending module 1203 is configured to send the feature acquisition link to a client of a team member when the team feature data is acquired from the team member, so that the team member can provide an answer according to a data collection question pointed by the feature acquisition 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 the server side, and receive team feature data of team members and/or at least one target product combination from the server side; 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 team members; the second product type is a subordinate type of a first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity;

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, in response to the selected request of the creating user for one of the target product combinations, 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 the task processing method described 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 an electronic device, and fig. 13 shows a block diagram 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 one or more computer instructions, which are executed by the processor 1302 to implement the method steps of:

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

outputting the data collection question to a client of at least one team member so as to obtain team characteristic data of the team member from answers of the team member to the data collection question; wherein the team characteristic 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 a team member; the second product type is a subordinate type of the first product type in the first product type set.

An electronic device is disclosed that includes a memory and a processor; wherein the content of the first and second substances,

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

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

determining a second number of first candidate products according to the first number of the team members having the corresponding relation with the second product type aiming at the second product type in the second product type set to form a first candidate product set; wherein the second number is in direct proportion to the first number;

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 a first set of product types and a total number of members of a team member;

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 an answer according to a data collection question pointed by the characteristic acquisition link.

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 section 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.

In particular, according to embodiments of the present disclosure, all of the methods described above may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the above-described object class determination method. In such an embodiment, the computer program can be downloaded and installed from a network via the communication portion 1409 and/or installed from the removable medium 1411.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units 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 a computer-readable storage medium, which may be the computer-readable storage medium included in the electronic device or the computer system in the above embodiments; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.

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 the technical features disclosed in the present disclosure (but not limited to) 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;

outputting the data collection question to a client of a creation user in team members, and sending the data collection question to clients of other team members through the client of the creation user so as to obtain team characteristic data of the team members from answers of the team members to the data collection question; 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 team members; the second product type is a subordinate type of the first product type in the first product type set;

determining 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 under a second product type and corresponding quantity;

scheduling delivery resources to deliver the target products from different target product providers to delivery target locations designated by a team;

the team task further comprises product limiting conditions, and the target product combination to be acquired by the team task is determined according to the team task data and the team characteristic data, and the method comprises the following steps:

for a second product type in a second product type set, determining a second number of first candidate products according to a first number of team members having a corresponding relationship with the second product type to form a first candidate product set, wherein the second number is in a direct proportion relationship with the first number;

and determining a part of first candidate products in the first candidate product set as target products according to the product limitation condition, wherein the number of the target products belonging to the same second product type is less than or equal to the first number corresponding to the second product type, and the number of the target products belonging to the same first product type is less than or equal to the total number of team members.

2. The method of claim 1, wherein generating a data collection question from the team mission data comprises:

3. The method of claim 2, further comprising:

4. The method of claim 1, wherein said determining, for the second product type in the second set of product types, a second number of first candidate products from the first number of team members having correspondence to the second product type, forming a first set of candidate products, comprises:

determining the first 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 by the team member when obtaining the product of the second product type over a historical period of time.

5. The method of claim 4, wherein determining the first candidate product from historical data of the team members having a correspondence with the second product type comprises:

6. The method of claim 4, wherein the product constraints include a total cost of products to be acquired by the team mission; the determining a plurality of target products from the first candidate product set according to the product limitation condition comprises:

7. The method of claim 6, wherein determining the first candidate product in one of the candidate product combinations as the target product based on historical data of the team members comprises:

8. A task processing method, comprising:

acquiring team task data and team characteristic data of team members in a team task from a client of a creating user and clients of other team members; the team task data comprises a first product type set, the total number of members of a team member and product limitation conditions, and the characteristic data comprises a second product type set and the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of a first product type in the first product type set;

determining a second number of first candidate products according to the first number of the team members having the corresponding relation with the second product type aiming at the second product type in the second product type set to form a first candidate product set; wherein the second quantity is in direct proportion to the first quantity;

determining a plurality of target products from the first candidate product set according to the product limitation condition, wherein the number of the target products belonging to the same second product type is smaller than or equal to the first number corresponding to the second product type, and the number of the target products belonging to the same first product type is smaller than or equal to the total number of team members; and scheduling delivery resources to deliver the target products from different target product providers to delivery target locations designated by the team.

9. The method of claim 8, wherein determining, for the second product type in the second set of product types, a second number of first candidate products from the first number of team members having correspondence with the second product type, forming a first set of candidate products, comprises:

10. The method of claim 9, wherein determining the first candidate product from historical data of the team members having a correspondence with the second product type comprises:

11. The method of claim 9, wherein the product constraints include a total cost of products to be acquired by the team task; determining a plurality of target products from the first set of candidate products according to the product constraints, including:

12. The method of claim 11, wherein determining the first candidate product in one of the candidate product combinations as the target product based on the team member's historical data comprises:

13. A method for processing a task, comprising:

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 an answer according to a data collection question pointed by the characteristic acquisition link;

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

sending answers to the data collection questions to a server side, and receiving team characteristic data of team members and/or at least one target product combination from the server side; 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 team members; the second product type is a subordinate type of a first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity; the target product is a distribution resource distributed to a distribution target place appointed by a team from different target product providers;

the target product combination is obtained by the following steps:

acquiring product limiting conditions;

14. The method of claim 13, further comprising:

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

15. The method of claim 14, further comprising:

16. The method of claim 15, further comprising:

17. A task processing apparatus, comprising:

the first output module is configured to output the data collection question to a client of a creation user in team members and send the data collection question to clients of other team members through the client of the creation user so as to acquire 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 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 the first product type in the first product type set;

determining 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 in a second product type and corresponding quantity;

18. The apparatus of claim 17, wherein the generating a data collection question from the team task data comprises:

19. The apparatus of claim 18, further comprising:

20. The apparatus of claim 17, wherein said determining, for the second product type in the second set of product types, a second number of first candidate products from the first number of team members having correspondence to the second product type, forming a first set of candidate products, comprises:

21. The apparatus of claim 20, wherein said determining the first candidate product from historical data of the team member having a correspondence with the second product type comprises:

22. The apparatus of claim 20, wherein the product constraints include a total cost of products to be acquired by the team mission; the determining a plurality of target products from the first candidate product set according to the product limitation condition comprises:

23. The apparatus of claim 22, wherein said determining the first candidate product in one of the candidate product combinations as the target product based on the team member's historical data comprises:

24. A task processing apparatus, characterized by comprising:

the second acquisition module is configured to acquire team task data and team characteristic data of team members in the team task from the client of the creating user and the clients of other team members; the team task data comprises a first product type set, the total number of members of a team member and product limitation conditions, and the characteristic data comprises a second product type set and the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of the first product type in the first product type set;

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

a fourth determining module configured to determine a plurality of target products from the first candidate product set according to the product limitation condition, wherein the number of target products belonging to the same second product type is less than or equal to the first number corresponding to the second product type, and the number of target products belonging to the same first product type is less than or equal to the total number of team members; and scheduling delivery resources to deliver the target product from different target product providers to a delivery destination specified by a team.

25. The apparatus of claim 24, wherein said determining, for the second product type in the second set of product types, a second number of first candidate products from the first number of team members having correspondence with the second product type, forming a first set of candidate products, comprises:

26. The apparatus as claimed in claim 25, wherein said determining the first candidate product from historical data of the team member having correspondence with the second product type comprises:

27. The apparatus of claim 25, wherein the product constraints include a total cost of products to be acquired by the team mission; determining a plurality of target products from the first set of candidate products according to the product constraints, including:

28. The apparatus of claim 27, wherein said determining the first candidate product in one of the candidate product combinations as the target product based on the team member's historical data comprises:

29. A task processing apparatus, characterized by comprising:

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

the first sending module is configured to send the characteristic acquisition link to a client of a team member when the team characteristic data is acquired from the team member, so that the team member can provide an answer according to a data collection question pointed by the characteristic acquisition link;

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;

a second receiving module, configured to send answers to the data collection questions to a server side, and receive team characteristic data and/or at least one target product combination of team members from the server side; 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 team members; the second product type is a subordinate type of a first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity; the target products are distributed to a distribution target place designated by a team from different target product providers for distribution resources;

the target product combination is obtained by the following steps:

obtaining product limiting conditions;

30. The apparatus of claim 29, further comprising:

31. The apparatus of claim 30, further comprising:

32. The apparatus of claim 31, further comprising:

33. An electronic device comprising a memory and a processor; wherein the memory is 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:

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

34. An electronic device comprising a memory and a processor; wherein the memory is 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:

acquiring team task data and team characteristic data of team members in a team task from a client of a creating user and clients of other team members; the team task data comprises a first product type set, the total number of members of a team member and product limitation conditions, and the characteristic data comprises a second product type set and the corresponding relation between a second product type in the second product type set and the team member; the second product type is a subordinate type of the first product type in the first product type set;

determining a plurality of target products from the first candidate product set according to the product limitation condition, wherein the number of the target products belonging to the same second product type is smaller than or equal to the first number corresponding to the second product type, and the number of the target products belonging to the same first product type is smaller than or equal to the total number of team members;

and scheduling delivery resources to deliver the target products from different target product providers to delivery target locations designated by the team.

35. An electronic device comprising a memory and a processor; wherein the memory is 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:

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 data collection questions pointed by the characteristic acquisition link;

sending answers to the data collection questions to a server side, and receiving team characteristic data of team members and/or at least one target product combination from the server side; 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 team members; the second product type is a subordinate type of a first product type in the first product type set; the target product combination comprises target products under the second product type and corresponding quantity; the target products are distributed to a distribution target place designated by a team from different target product providers for distribution resources;

the target product combination is obtained by the following steps:

obtaining product limiting conditions;

36. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 1-7.

37. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 8-12.

38. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 13-16.