CN106126880A - Target user selection method, system and equipment - Google Patents
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Abstract
The invention relates to a method, a system and equipment for selecting a target user, wherein the method comprises the following steps: acquiring a selection instruction sent by a control device, and reading attribute information representing the association relation between each user and a preset constraint condition in response to the selection instruction; selecting a target user from all users according to the attribute information; acquiring a unique identifier corresponding to a receiving device of a target user, and sending a notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user. The method, the system and the equipment for selecting the target user can reduce the subjective influence of the selected main body and improve the accuracy of target selection.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, a system, and a device for selecting a target user.
Background
In practical applications, it is often necessary to select one or more target objects with certain target attributes from a series of candidate sets, and then to estimate the characteristics of the objects in the entire set according to the characteristics of the selected target objects. The existing selection methods are generally selected manually. For example, when a product quality spot check is performed, especially when the number of products is large, it is impossible to check the quality of each product, and generally quality check personnel randomly select some products to perform the quality spot check. For another example, in a classroom, a teacher often draws students to answer questions. However, the existing target selection method is greatly influenced by the subjectivity of the selected subject, so that the selection result is difficult to objectively reflect the characteristics of the to-be-selected set. For example, in the above-described product quality spot check example, products that are generally located near the outside are easier to spot, and products that are located inside or in corners are less likely to spot. For example, in the above example of the teacher asking questions, the teacher may prefer to select students near the lecture station. Since there is a bias in selecting the target itself, accuracy is inevitably poor when estimating the characteristics of the population from the target selected in such a biased manner. In addition, the accuracy of the selection may be poor due to the different comprehension of the target attributes by different selection subjects.
As can be seen from the two examples, the existing target selection method has poor target selection effect.
Disclosure of Invention
Therefore, it is necessary to provide a method, a system and a device for selecting a target user, aiming at the problem that the existing target selection method has a poor effect of selecting a target.
A method of target user selection comprising the steps of:
acquiring a selection instruction sent by a control device, and reading attribute information representing the association relation between each user and a preset constraint condition in response to the selection instruction;
selecting a target user from all users according to the attribute information;
acquiring a unique identifier corresponding to a receiving device of a target user, and sending a notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
A target user selection system comprising:
the reading device is used for acquiring the selection instruction sent by the control device and responding to the selection instruction to read attribute information representing the association relation between each user and a preset constraint condition;
a selecting device for selecting a target user from the users according to the attribute information;
the sending device is used for acquiring a unique identifier corresponding to the receiving device of the target user and sending the notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
A target user selection device comprising:
the system comprises a control device, a background server and a receiving device; the receiving devices are provided with unique identifiers which are distinguished from one another, and each identifier corresponds to a unique user;
the control device receives an input selection instruction and sends the selection instruction to the background server; wherein, the selection instruction carries the constraint condition of the selection target user;
and the background server responds to the selection instruction to read attribute information representing the incidence relation between each user and a preset constraint condition, selects a target user from each user according to the attribute information, acquires a unique identifier corresponding to a receiving device of the target user, and sends a notification message to the receiving device of the target user according to the unique identifier.
According to the target user selection method, the target user selection system and the target user selection equipment, the target object is selected from the multiple objects to be selected according to the attribute information by acquiring the pre-stored user attribute information, the subjective influence of the selected main body can be reduced, meanwhile, the selection condition is set during selection, the target with the maximum association degree with the constraint condition can be accurately selected, and the selection accuracy is improved.
Drawings
FIG. 1 is a flow chart of a target user selection method of the present invention;
FIG. 2 is a schematic diagram of a target user selection system according to the present invention;
fig. 3 is a schematic structural diagram of a selection device of a target user according to the present invention.
Detailed Description
Embodiments of a target user selection method, system and apparatus according to the present invention are described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a target user selection method of the present invention. As shown in fig. 1, the method for selecting the target user may include the following steps:
s1, acquiring a selection instruction sent by the control device, and reading attribute information representing the association relation between each user and a preset constraint condition in response to the selection instruction;
s2, selecting target users from each user according to the attribute information;
s3, acquiring a unique identifier corresponding to the receiving device of the target user, and sending a notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
For ease of understanding, the following description will be given with an example in which a teacher selects a student to answer a question in a teaching system. It will be appreciated by those skilled in the art that the invention is not limited to this example.
In step S1, constraints may be set as needed. For example, the constraint may be a fairness related constraint even if the average number of times each student answers the question is as equal as possible; or a constraint condition that maximizes or minimizes the value corresponding to a certain feature, for example, the number of times that a student with poor performance answers a question is as large as possible; other constraints are also possible and will not be described in detail here. Taking the fairness constraint condition as an example, attribute information of each student associated with the constraint condition may be stored in advance. The attribute information can be the full class ranking of each student, the number of answers of each student, the correct rate of the answers, the proportion of the homework completed on time and the like.
In step S2, a probability value that each user is selected is calculated based on the attribute information; and selecting a target user from the users according to the probability value. Weights may be assigned to the attributes in the attribute information in advance, and the weights may be set according to the influence degrees of the respective data. The probability of each user being selected may be calculated according to the attribute information and a preset weight. The attributes in the attribute information may include the number of the user, the number of times the user has been selected historically, the number of times the user has responded to the selection instruction correctly, and the like, and may further include other attributes. The probability that the ith user is selected may be calculated as follows:
wherein,
in the formula, AijIs the jth attribute of the ith user, WijIs AijWeight of (1), PiIs the probability that the ith user is selected.
In the teaching system, the attributes may include the ranking of the students, the number of times the students answer and the correct rate of the answers, and may further include the proportion of the students who complete the homework on time. Assuming that there are n students in total, the ranking of the ith student is Ai1(i is more than or equal to 1 and less than or equal to n), and the number of answers of the ith student is Ai2(1. ltoreq. i. ltoreq. n) and the accuracy of the answer is Ai3(i is more than or equal to 1 and less than or equal to n), and the proportion of completing the operation on time is Ai4(i is more than or equal to 1 and less than or equal to n). Respectively allocating weight W to the 4 datai1、Wi2、Wi3And Wi4。
A maximum probability may be selected from the probabilities; if the number of the maximum probabilities is 1, setting the user corresponding to the maximum probabilities as a selected target; and if the number of the maximum probabilities is more than 1, randomly selecting one from the maximum probabilities, and setting the corresponding user as a target user.
For example, assuming that there are 2 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student is 60%, then the second student may be targeted for selection. Assuming that there are 3 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student and the third student is P3 is 60%, then one of the second student and the third student may be randomly selected as a selection target.
In order to make each selection more accurate, the attribute information of the user can be updated regularly. For example, the attribute information may be updated according to the result (correct or incorrect) of the student answering the question. Other attribute information, such as the name, the job completion and the like, can be updated into the system. An update command, which may carry update information, may be set as a condition for triggering an update, and the update command may be transmitted by the control device. When the update instruction is received, the corresponding attribute information can be updated according to the update instruction.
Corresponding to the selection method of the target user, the present invention further provides a selection system of the target user, as shown in fig. 2, which may include:
the reading device 110 is configured to obtain a selection instruction sent by the control device, and read attribute information representing an association relationship between each user and a preset constraint condition in response to the selection instruction;
a selecting device 120, configured to select a target user from the users according to the attribute information;
the sending device 130 is configured to obtain a unique identifier corresponding to a receiving device of a target user, and send a notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
For ease of understanding, the following description will be given with an example in which a teacher selects a student to answer a question in a teaching system. It will be appreciated by those skilled in the art that the invention is not limited to this example.
The reading device 110 can set the constraint conditions according to actual needs. For example, the constraint may be a fairness related constraint even if the average number of times each student answers the question is as equal as possible; or a constraint condition that maximizes or minimizes the value corresponding to a certain feature, for example, the number of times that a student with poor performance answers a question is as large as possible; other constraints are also possible and will not be described in detail here. Taking the fairness constraint condition as an example, attribute information of each student associated with the constraint condition may be stored in advance. The attribute information can be the full class ranking of each student, the number of answers of each student, the correct rate of the answers, the proportion of the homework completed on time and the like.
The selecting device 120 may calculate probability values of the respective users being selected according to the attribute information; and selecting a target user from the users according to the probability value. Weights may be assigned to the attributes in the attribute information in advance, and the weights may be set according to the influence degrees of the respective data. The probability of each user being selected may be calculated according to the attribute information and a preset weight. The attributes in the attribute information may include the number of the user, the number of times the user has been selected historically, the number of times the user has responded to the selection instruction correctly, and the like, and may further include other attributes. The probability that the ith user is selected may be calculated as follows:
wherein,
in the formula, AijIs the jth attribute of the ith user, WijIs AijWeight of (1), PiIs the probability that the ith user is selected.
In the teaching system, the attributes may include the ranking of the students, the number of times the students answer and the correct rate of the answers, and may further include the proportion of the students who complete the homework on time. Assuming that there are n students in total, the ranking of the ith student is Ai1(i is more than or equal to 1 and less than or equal to n), and the number of answers of the ith student is Ai2(1. ltoreq. i. ltoreq. n) and the accuracy of the answer is Ai3(i is more than or equal to 1 and less than or equal to n), and the proportion of completing the operation on time is Ai4(i is more than or equal to 1 and less than or equal to n). Respectively allocating weight W to the 4 datai1、Wi2、Wi3And Wi4。
A maximum probability may be selected from the probabilities; if the number of the maximum probabilities is 1, setting the user corresponding to the maximum probabilities as a selected target; and if the number of the maximum probabilities is more than 1, randomly selecting one from the maximum probabilities, and setting the corresponding user as a target user.
For example, assuming that there are 2 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student is 60%, then the second student may be targeted for selection. Assuming that there are 3 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student and the third student is P3 is 60%, then one of the second student and the third student may be randomly selected as a selection target.
In order to make each selection more accurate, the attribute information of the user can be updated regularly. For example, the attribute information may be updated according to the result (correct or incorrect) of the student answering the question. Other attribute information, such as the name, the job completion and the like, can be updated into the system. An update command, which may carry update information, may be set as a condition for triggering an update, and the update command may be transmitted by the control device. When the update instruction is received, the corresponding attribute information can be updated according to the update instruction.
Compared with the above method and system for selecting a target user, the present invention further provides a device for selecting a target user, as shown in fig. 3, which may include:
control device 210, background server 220 and receiving device 230; each receiving device 230 is provided with unique identifiers distinguished from each other, and each identifier corresponds to one unique user;
the control device 210 receives an input selection instruction and sends the selection instruction to the background server 220; wherein, the selection instruction carries the constraint condition of the selection target user;
the background server 220 reads attribute information representing an association relationship between each user and a preset constraint condition in response to the selection instruction, selects a target user from each user according to the attribute information, obtains a unique identifier corresponding to the receiving device 230 of the target user, and sends a notification message to the receiving device 230 of the target user according to the unique identifier.
The control device and/or the receiving device in the above embodiments may be a wearable device (e.g., a smart band or smart glasses), or may be a terminal device (e.g., a mobile phone, a tablet computer, a notebook computer, etc.) installed with a corresponding application program.
The control device and the receiving device can be connected to the background server through WIFI.
In order to enable the selected target to visually check the selection result, a plurality of signal indicator lamps can be arranged, each signal indicator lamp corresponds to each receiving device, and when the receiving devices receive the notification message sent by the background server, the corresponding signal indicator lamps are turned on.
For ease of understanding, the following description will be given with an example in which a teacher selects a student to answer a question in a teaching system. It will be appreciated by those skilled in the art that the invention is not limited to this example.
In one embodiment, backend server 220 may set constraints according to actual needs. For example, the constraint may be a fairness related constraint even if the average number of times each student answers the question is as equal as possible; or a constraint condition that maximizes or minimizes the value corresponding to a certain feature, for example, the number of times that a student with poor performance answers a question is as large as possible; other constraints are also possible and will not be described in detail here. Taking the fairness constraint condition as an example, attribute information of each student associated with the constraint condition may be stored in advance. The attribute information can be the full class ranking of each student, the number of answers of each student, the correct rate of the answers, the proportion of the homework completed on time and the like.
After receiving the selection instruction sent by the control device 210, the backend server 220 may calculate a probability value selected by each user according to the attribute information; and selecting a target user from the users according to the probability value. Weights may be assigned to the attributes in the attribute information in advance, and the weights may be set according to the influence degrees of the respective data. The probability of each user being selected may be calculated according to the attribute information and a preset weight. The attributes in the attribute information may include the number of the user, the number of times the user has been selected historically, the number of times the user has responded to the selection instruction correctly, and the like, and may further include other attributes. The probability that the ith user is selected may be calculated as follows:
wherein,
in the formula, AijIs the jth attribute of the ith user, WijIs AijWeight of (1), PiIs the probability that the ith user is selected.
In the teaching system, the attributes may include the ranking of the students, the number of times the students answer and the correct rate of the answers, and may further include the proportion of the students who complete the homework on time. Assuming that there are n students in total, the ranking of the ith student is Ai1(i is more than or equal to 1 and less than or equal to n), and the number of answers of the ith student is Ai2(1. ltoreq. i. ltoreq. n) and the accuracy of the answer is Ai3(i is more than or equal to 1 and less than or equal to n), and the proportion of completing the operation on time is Ai4(i is more than or equal to 1 and less than or equal to n). Respectively allocating weight W to the 4 datai1、Wi2、Wi3And Wi4。
Backend server 220 may choose the maximum probability from the probabilities; if the number of the maximum probabilities is 1, setting the user corresponding to the maximum probabilities as a selected target; and if the number of the maximum probabilities is more than 1, randomly selecting one from the maximum probabilities, and setting the corresponding user as a target user. Backend server 220 may send a notification message to receiving device 230 of the target user.
For example, assuming that there are 2 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student is 60%, then the second student may be targeted for selection. Assuming that there are 3 students in total, the probability P1 of being selected by the first student is 40%, and the probability P2 of being selected by the second student and the third student is P3 is 60%, then one of the second student and the third student may be randomly selected as a selection target.
In order to make each selection more accurate, the backend server 220 may update the attribute information of the user periodically. For example, the attribute information may be updated according to the result (correct or incorrect) of the student answering the question. Other attribute information, such as the name, the job completion and the like, can be updated into the system. An update command, which may carry update information, may be set as a condition for triggering an update, and the update command may be transmitted by the control device. When the update instruction is received, the corresponding attribute information can be updated according to the update instruction.
The target user selection method, the target user selection system and the target user selection equipment have the following advantages:
(1) the subjective influence of the selected main body can be reduced, and the selection is more objective.
(2) The selected constraint condition is set during selection, the target with the maximum degree of association with the constraint condition can be accurately selected, and the accuracy of selection is improved.
(3) The selection method is integrated into the wearable device, and the operation is convenient.
(4) The indicator light is arranged, so that the selection result can be observed visually.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for selecting a target user, comprising the steps of:
acquiring a selection instruction sent by a control device, and reading attribute information representing the association relation between each user and a preset constraint condition in response to the selection instruction;
selecting a target user from all users according to the attribute information;
acquiring a unique identifier corresponding to a receiving device of a target user, and sending a notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
2. The method of claim 1, wherein the step of selecting the target user from the users according to the attribute information comprises:
calculating a probability value selected by each user according to the attribute information;
and selecting a target user from the users according to the probability value.
3. The method of claim 2, wherein the step of calculating a probability value of each user being selected based on the attribute information comprises:
reading the weight values of each attribute of the attribute information;
and calculating the probability value of each user selected according to each attribute and the weight value.
4. The method of claim 3, wherein the probability of each user being selected is calculated according to:
wherein,
in the formula, AijIs the jth attribute of the ith user, WijIs AijWeight of (1), PiIs the probability that the ith user is selected.
5. The method of selecting a target user of claim 1, further comprising the steps of:
receiving an updating instruction sent by a control device;
and updating the attribute information of the user according to the updating instruction.
6. The method of claim 2, wherein the step of selecting the target user from the respective users according to the probability selection comprises:
selecting a maximum probability value from the probability values;
if the number of the maximum probability value is 1, setting the user corresponding to the maximum probability value as a selected target;
and if the number of the maximum probability values is larger than 1, randomly selecting one of the maximum probability values, and setting the corresponding user as a target user.
7. A target user selection system, comprising:
the reading device is used for acquiring the selection instruction sent by the control device and responding to the selection instruction to read attribute information representing the association relation between each user and a preset constraint condition;
a selecting device for selecting a target user from the users according to the attribute information;
the sending device is used for acquiring a unique identifier corresponding to the receiving device of the target user and sending the notification message to the receiving device of the target user according to the unique identifier; the receiving devices are provided with unique identifiers which are distinguished from each other, and each identifier corresponds to a unique user.
8. A target user selection device, comprising:
the system comprises a control device, a background server and a receiving device; the receiving devices are provided with unique identifiers which are distinguished from one another, and each identifier corresponds to a unique user;
the control device receives an input selection instruction and sends the selection instruction to the background server; wherein, the selection instruction carries the constraint condition of the selection target user;
and the background server responds to the selection instruction to read attribute information representing the incidence relation between each user and a preset constraint condition, selects a target user from each user according to the attribute information, acquires a unique identifier corresponding to a receiving device of the target user, and sends a notification message to the receiving device of the target user according to the unique identifier.
9. The target user selection device of claim 8, further comprising:
and when the receiving device receives the notification message sent by the background server, the corresponding signal indicator lamps are on.
10. The selection device of the target user according to claim 8, characterized in that the control means and/or the receiving means are wearable devices.
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| CN201610421062.9A CN106126880A (en) | 2016-06-14 | 2016-06-14 | Target user selection method, system and equipment |
| PCT/CN2016/113225 WO2017215248A1 (en) | 2016-06-14 | 2016-12-29 | Method, system and device for selecting target user |
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| CN105512256A (en) * | 2015-12-01 | 2016-04-20 | 深圳拼课邦科技有限公司 | Method and device for pushing lecturer information |
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| CN104715285A (en) * | 2015-03-31 | 2015-06-17 | 北京嘀嘀无限科技发展有限公司 | Method and equipment for processing orders |
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| CN111161441A (en) * | 2019-12-19 | 2020-05-15 | 广东鉴面智能科技有限公司 | Intelligent teaching roll calling method, device and system |
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