A method and device for processing information of multi-level role calling queue

Abstract

This invention discloses a method and apparatus for processing information in a multi-level role-based queuing system. The method includes: acquiring historical queuing information of users; the historical queuing information includes user history information and actual waiting time information; the historical queuing information includes user level information, queuing type information, and queuing content information; the user level information is set to a first priority, a second priority, or a third priority; performing time modeling processing on the historical queuing information to obtain a user waiting time prediction model; acquiring user queuing information and user queue information; the user queuing information includes user level information, queuing type information, and queuing content information; the user queue information records the queue number of each queued user; processing the user queuing information using the user waiting time prediction model to obtain a predicted user waiting time value; and performing queuing processing on the user queuing information, user queue information, and predicted user waiting time value to obtain user sorting information.

Description

Technical Field

[0001] The invention relates to the fields of computers and data processing, and in particular to an information processing method and device for multi-level role calling and queuing. Background Art

[0002] The queuing system is a product that uses computers, networks, multimedia, and communication control technology to replace the traditional way of customers standing in line at various service windows, and replaces the queuing system with a computer system. The queuing system is an indispensable part of the modern service industry. It improves service efficiency and optimizes customer experience. The queuing system is mainly based on queuing algorithms, prediction algorithms, and computer software to optimize window services. At present, the queuing system has been widely used in banking, hospitals, government service centers, tax halls, and restaurant operations.

[0003] At present, simple queuing systems, queue-jumping queuing systems, and simple predictive queuing systems have all improved service efficiency, reduced customer waiting time, and increased customer satisfaction to a certain extent, but in fact they all convert customer offline waiting time into online waiting time, and cannot further meet personalized needs. At the same time, in some specific scenarios, internal service industries need to meet the needs of appointment time and priority service for multi-level customers, queuing and appointment requirements for ordinary customers, and multi-point dynamic planning requirements for peer service industries in specific scenarios, and queuing methods need to provide further solutions on the original basis. Summary of the invention

[0004] The present invention mainly solves the problem of how to meet the needs of appointment time and priority service for multi-level customers, queuing and appointment requirements for ordinary customers, and multi-point dynamic planning requirements of peer service industries in specific scenarios, and improve the efficiency of calling and queuing and the accuracy of queuing prediction time. The present invention discloses an information processing method and device for multi-level role calling and queuing.

[0005] In a first aspect, an embodiment of the present application discloses a method for processing information of a multi-level role calling queue, comprising:

[0006] S1, obtaining the user's historical call information; the user's historical call information includes the user's historical information and the user's actual waiting time information; the user's historical information includes the user's level information, the call type information, and the call content information; the user's level information is set to the first priority, the second priority, or the third priority; the call type information is set to sequential call, appointment time call, or re-call; the value of the call content information is determined according to the call type information;

[0007] S2, performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model;

[0008] S3, obtaining user calling information and user queue information; the user calling information includes user level information, calling type information and calling content information; the user queue information records the queue number of each queued user;

[0009] S4, using a user waiting time prediction model to process the user calling information to obtain a user waiting time prediction value;

[0010] S5, performing queue processing on the user calling number information, user queue information and user waiting time prediction value to obtain user ranking information.

[0011] The performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model includes:

[0012] S21, digitally encode the user's historical call information to obtain a user history information matrix and a user's actual waiting time vector;

[0013] S22, calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model.

[0014] The digital coding process of the user's historical call information is performed to obtain a user's historical information matrix and a user's actual waiting time vector, including:

[0015] Performing digital coding processing on the user level information in the user historical call information to obtain the first row vector in the user historical information matrix;

[0016] Performing joint digital coding processing on the call type information and the call content information in the user's historical call information to obtain a second row vector in the user's historical information matrix;

[0017] The user history information matrix includes a first row vector and a second row vector;

[0018] The actual waiting time information of each user corresponding to the historical information of each user is used to construct the actual waiting time vector of the user.

[0019] The calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model includes:

[0020] The transposed matrix of the user history information matrix is ​​represented as Q, and the user actual waiting time vector is represented as v. The dimension of Q is m×n, and the dimension of v is m×1.

[0021] The user waiting time prediction model to be solved is established, and its expression is:

[0022] Qp=v,

[0023] Among them, p is the vector to be solved in the user waiting time prediction model, and the dimension of p is n×1;

[0024] The fusion solution matrix W is constructed using Q and v. The expression of the fusion solution matrix W is:

[0025] W=[-v,Q],

[0026] Among them, the dimension of the fusion solution matrix W is m×(n+1);

[0027] Perform singular value decomposition on the fusion solution matrix W to obtain:

[0028] W=UCY H ,

[0029] Among them, U is the left hierarchical matrix, C is the intermediate matrix, and Y is the right decomposition matrix;

[0030] Decompose the matrix Y to obtain a vector p; the expression of the decomposition process is:

[0031] p(i)=Y(i+1,n+1),

[0032] Where p(i) represents the i-th element of vector p, and Y(i+1,n+1) represents the element in the i+1-th row and n+1-th column of matrix Y;

[0033] Substitute the vector p into the user waiting time prediction model to be solved to obtain the user waiting time prediction model.

[0034] The calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model includes:

[0035] Based on the user level information, a corresponding waiting time distribution probability model is established; the expression of the waiting time distribution probability model is:

[0036]

[0037] Where P(k) represents the distribution probability of the waiting time when the number of people in the queue is k; the value of k is determined according to the elements of the second row of the user history information matrix, and λ is the parameter to be solved;

[0038] For each user level information, based on the user actual waiting time vector and the second row vector of the user history information matrix, establish the corresponding distribution probability of the user actual waiting time;

[0039] For each user level, based on the distribution probability of the actual waiting time of the user, the parameter λ in the waiting time distribution probability model is solved to obtain the value of the parameter λ;

[0040] For each user level, substitute the value of parameter λ into the corresponding waiting time distribution probability model to obtain the waiting time distribution probability model of the user level;

[0041] All user-level waiting time distribution probability models are combined to obtain a user waiting time prediction model.

[0042] The queuing process is performed on the user calling number information, the user queue information and the user waiting time prediction value to obtain the user sorting information, including:

[0043] Obtaining user level information of the user calling number information;

[0044] When the user level information is the first priority, according to the calling type information of the user calling information, the user number corresponding to the first priority is added to the first position of the user queued information to obtain updated user queued information;

[0045] When the user level information is of the second priority, the actual calling time of the user is determined according to the reservation time of the user and the predicted value of the user waiting time of the user; the user sequence number of the user is added to the user queuing information according to the value sorting of the actual calling time of the user in the user queuing time sequence in the user queuing information, and the updated user queuing information is obtained;

[0046] When the user level information is the third priority, the corresponding calling type information is obtained; when the calling type information is sequential calling, the user sequence number corresponding to the third priority is added to the last bit of the user queued information; when the calling type information is repeated calling, the user sequence number corresponding to the third priority is added to the Nth bit of the user queued information to obtain the updated user queued information;

[0047] Confirm the updated user queue information and sort the information for the user.

[0048] Determining the actual calling time of the user according to the reservation time of the user and the predicted value of the user's waiting time includes:

[0049] Determine whether the user waiting time prediction value of the user is greater than the set time threshold T1, and obtain a first determination result. When the first determination result is no, determine the user's reservation time as the user's actual call time;

[0050] When the first judgment result is yes, the actual calling time T0 of the user is determined to be TY-TC / 2, where TY is the reservation time of the user and TC is the predicted value of the user's waiting time.

[0051] In a second aspect of the embodiments of the present application, a multi-level role calling queue information processing device is disclosed, the device comprising:

[0052] A memory storing executable program code;

[0053] a processor coupled to the memory;

[0054] The processor calls the executable program code stored in the memory to execute the information processing method of the multi-level role calling queue.

[0055] In a third aspect of an embodiment of the present application, a computer storable medium is disclosed, wherein the computer storable medium stores computer instructions, and when the computer instructions are called, they are used to execute the information processing method of the multi-level role calling queue.

[0056] In a fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed, and the information data processing terminal is used to implement the information processing method of the multi-level role calling queue.

[0057] The beneficial effects of the present invention are:

[0058] In response to the requirements of multi-level customers for booking and appointment services in specific scenarios and the requirements for dynamic planning of queuing for peers of different priority levels, as well as the advantages and disadvantages of current number-calling queuing methods, the present invention establishes a set of online number-calling queuing methods that are suitable for use in specific scenarios based on a distribution prediction model, taking into account the requirements of hierarchical appointments and dynamic queuing, and ensuring that personalized queuing schemes for specific scenarios are established on the basis of maintaining the needs of normal queuing and calling, which is more in line with the usage patterns of customers in specific scenarios with different priority levels.

[0059] The present invention provides more accurate prediction capabilities, optimizes resource allocation, and improves service efficiency and customer satisfaction for queuing call service scenarios such as family areas with multiple service types concentrated, multiple service windows in parallel, and special sorting and appointment requirements. This method provides more accurate and timely call information to a certain extent, reduces customer waiting time, and strengthens personalized and intelligent services, which reduces service costs and improves overall operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flow chart for implementing the method of the present invention. DETAILED DESCRIPTION

[0061] In order to better understand the content of the present invention, an embodiment is given here.

[0062] Figure 1 It is a flow chart for implementing the method of the present invention.

[0063] In a first aspect, an embodiment of the present application discloses a method for processing information of a multi-level role calling queue, comprising:

[0064] S1, obtaining the user's historical call information; the user's historical call information includes the user's historical information and the user's actual waiting time information; the user's historical information includes the user's level information, the call type information, and the call content information; the user's level information is set to the first priority, the second priority, or the third priority; the call type information is set to sequential call, appointment time call, or re-call; the value of the call content information is determined according to the call type information;

[0065] When the user level information is the first priority, the corresponding calling type information is sequential calling, appointment time calling or repeated calling;

[0066] When the user level information is the second priority, the corresponding calling type information is the appointment time calling;

[0067] When the user level information is the first priority, the corresponding calling type information is sequential calling or repeated calling;

[0068] When the calling type information is sequential calling, the value of the calling content information is the number of people currently in the queue; when the calling type information is appointment time calling, the value of the calling content information is the number of people already in the queue at the appointment time; when the calling type information is repeated calling, the value of the calling content information is the number of people currently in the queue;

[0069] S2, performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model;

[0070] S3, obtaining user calling information and user queue information; the user calling information includes user level information, calling type information and calling content information; the user queue information records the queue number of each queued user;

[0071] S4, using a user waiting time prediction model to process the user calling information to obtain a user waiting time prediction value;

[0072] S5, performing queuing processing on the user calling number information, the user queue information and the user waiting time prediction value to obtain user ranking information;

[0073] The performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model includes:

[0074] S21, digitally encode the user's historical call information to obtain a user history information matrix and a user's actual waiting time vector;

[0075] S22, calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model.

[0076] The digital coding process of the user's historical call information is performed to obtain a user's historical information matrix and a user's actual waiting time vector, including:

[0077] Performing digital coding processing on the user level information in the user historical call information to obtain the first row vector in the user historical information matrix;

[0078] Performing joint digital coding processing on the call type information and the call content information in the user's historical call information to obtain a second row vector in the user's historical information matrix;

[0079] The actual waiting time information of each user corresponding to the historical information of each user is used to construct the actual waiting time vector of the user.

[0080] The user level information is digitally coded and may be a value of setting the first priority, the second priority or the third priority, which are 1, 2, and 3 respectively;

[0081] The joint digital coding processing of the call type information and the call content information in the historical call information of the user may be that when the call type information is set to sequential call, the value of the call content information is a code value corresponding to the number of people in the current queue, which is a number of people in the queue; when the call type information is set to appointment time call, the value of the call content information is a code value corresponding to the number of people in the queue at the appointment time, which is a number of people in the queue; when the call type information is set to repeated call, when the value of the call content information is the current number of people in the queue, the corresponding code value is the current number of people in the queue;

[0082] The calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model includes:

[0083] The transposed matrix of the user history information matrix is ​​represented as Q, and the user actual waiting time vector is represented as v. The dimension of Q is m×n, and the dimension of v is m×1; where n=2;

[0084] The user waiting time prediction model to be solved is established, and its expression is:

[0085] Qp=v,

[0086] Among them, p is the vector to be solved in the user waiting time prediction model, and the dimension of p is n×1;

[0087] In order to improve the time prediction accuracy, it is necessary to consider the noise factor in the user's historical call information and overcome it. The fusion solution matrix W is constructed using Q and v. The expression of the fusion solution matrix W is:

[0088] W=[-v,Q],

[0089] Among them, the dimension of the fusion solution matrix W is m×(n+1);

[0090] Perform singular value decomposition on the fusion solution matrix W to obtain:

[0091] W=UCY H ,

[0092] Among them, U is the left hierarchical matrix, C is the intermediate matrix, and Y is the right decomposition matrix;

[0093] Decompose the matrix Y to obtain a vector p; the expression of the decomposition process is:

[0094] p(i)=Y(i+1,n+1),

[0095] Among them, p(i) represents the i-th element of vector p, and Y(i+1,n+1) represents the element in the i+1-th row and n+1-th column of matrix Y.

[0096] Substitute the vector p into the user waiting time prediction model to be solved to obtain the user waiting time prediction model;

[0097] The user waiting time prediction model is expressed as Qp=v, where Q is the input of the model and v is the output of the model. The model is used to obtain the user queuing time prediction value based on the user calling number information.

[0098] After a set of vectors p is obtained according to a user history information matrix and a user actual waiting time vector, corresponding vectors p can be obtained by solving the user history information matrix and the user actual waiting time vector for multiple time periods respectively;

[0099] The matrix eigenvalue calculation process is performed on the user history information matrix of each time period to obtain the maximum eigenvalue H i ;

[0100] Using the maximum eigenvalue H of the user history information matrix of all time periods i , calculate the weighted vector Weight vector The calculation expression is:

[0101]

[0102] in, is the weight vector ith item of ;

[0103] The vector p obtained in each time period is weightedly summed using a weighted vector to obtain a final solution of p; the final solution of p is substituted into the user waiting time prediction model to be solved to obtain a user waiting time prediction model.

[0104] The calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model includes:

[0105] Based on the user level information, a corresponding waiting time distribution probability model is established; the expression of the waiting time distribution probability model is:

[0106]

[0107] Where P(k) represents the distribution probability of waiting time when the number of people in the queue is k. The value of k is determined by the elements in the second row of the user history information matrix, and λ is the parameter to be solved;

[0108] For each user level information, based on the vector of the user's actual waiting time and the vector formed by the second row elements of the user's historical information matrix, establish the distribution probability of the corresponding user's actual waiting time;

[0109] The distribution probability of the actual waiting time of the user is the probability value of the actual waiting time of the user under different values ​​of the number of people in the queue, which can be obtained by statistically analyzing the vector composed of the actual waiting time vector of the user and the second row elements of the user history information matrix.

[0110] For each user level, based on the distribution probability of the user's actual waiting time vector, the parameter λ in the waiting time distribution probability model is solved to obtain the value of the parameter λ;

[0111] The parameter λ in the waiting time distribution probability model is solved by taking the queued person value as the k value and the distribution probability of the user's actual waiting time vector as the P(k) value, substituting them into the waiting time distribution probability model to solve for the parameter λ.

[0112] For each user level, substituting the value of parameter λ into the waiting time distribution probability model to obtain the waiting time distribution probability model of the user level;

[0113] All user-level waiting time distribution probability models are combined to obtain a user waiting time prediction model.

[0114] Performing queuing processing on the user call number information, the user's queued information, and the predicted user waiting time value to obtain user sorting information, including:

[0115] Obtaining the user level information of the user call number information;

[0116] When the user level information is the first priority, according to the call number type information of the user call number information, add the user serial number corresponding to the first priority to the first position of the user's queued information, and the queuing serial numbers of other users in the user's queued information are postponed backward; adding to the first position of the user's queued information includes, if the call number type information is sequential call or re-call for missed number, adding the user to the first position of the current user's queued information, and when the call number type information is call at reserved time, adding the user to the first position of the user's queued information at the reserved time; obtaining the updated user's queued information;

[0117] When the user level information is the second priority, determine the actual call time of the user according to the reserved time of the user and the predicted user waiting time value of the user; sort according to the value taken by the actual call time of the user in the sequence of user queued times in the user's queued information, and add the user serial number of the user to the user's queued information; obtaining the updated user's queued information;

[0118] When the user level information is the third priority, obtain the corresponding call number type information; when the call number type information is sequential call, add the user serial number corresponding to the third priority to the last position of the user's queued information; when the call number type information is re-call for missed number, add the user serial number corresponding to the third priority to the Nth position of the user's queued information, and the queuing serial numbers of the users after the Nth position in the user's queued information are postponed backward; N satisfies 1 < N < 5; obtaining the updated user's queued information;

[0119] Confirm that the updated user's queued information is the user sorting information;

[0120] The determining the actual call time of the user according to the reserved time of the user and the predicted user waiting time value of the user includes:

[0121] Judge whether the predicted user waiting time value of the user is greater than the set time threshold T1 to obtain a first judgment result. When the first judgment result is no, determine the reserved time of the user as the actual call time of the user;

[0122] When the first judgment result is yes, determine the actual call time T0 of the user as TY - TC / 2, where TY is the reserved time of the user and TC is the predicted user waiting time value;

[0123] Sorting the values in the user queuing time sequence in the user queued information according to the actual queuing call time of the user, and adding the user serial number of the user to the user queued information. For example, the user queued information is expressed as [1, 2, 3, 5, 6]. According to the actual queuing call time T4 of the user and the user queuing time sequence [T1, T2, T3, T5, T6] in the user queued information, it is determined that T5 < T4 < T6, and the user serial number 4 is added to the user queued information, and the new user queued information is expressed as [1, 2, 3, 4, 5, 6].

[0124] When the queuing call type information is sequential queuing call, the value of the queuing call content information is the current number of people in the queue; when the queuing call type information is queuing call at reserved time, the value of the queuing call content information is the number of people queued at the reserved time; when the queuing call type information is re - call for missed call, the value of the queuing call content information is the current number of people in the queue;

[0125] In the second aspect of the embodiments of the present application, an information processing device for multi - level role queuing call is disclosed. The device includes:

[0126] A memory storing executable program code;

[0127] A processor coupled to the memory;

[0128] The processor calls the executable program code stored in the memory and executes the information processing method for multi - level role queuing call.

[0129] In the third aspect of the embodiments of the present application, a computer - storable medium is disclosed. The computer - storable medium stores computer instructions, and when the computer instructions are called, they are used to execute the information processing method for multi - level role queuing call.

[0130] In the fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed. The information data processing terminal is used to implement the information processing method for multi - level role queuing call.

[0131] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for processing information of multi-level role calling queues, characterized in that: include: S1, obtain the user's historical call information; The user's historical call information includes user history information and user's actual waiting time information; The user history information includes user level information, call type information, and call content information; The user level information is set to the first priority, the second priority or the third priority; the calling type information is set to sequential calling, appointment time calling or repeated calling; the calling content information is set to a value determined according to the calling type information; S2, performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model; S3, obtaining the user's calling number information and the user's queue information; The user calling information includes user level information, calling type information and calling content information; the user queue information records the queue number of each queued user; S4, using a user waiting time prediction model to process the user calling information to obtain a user waiting time prediction value; S5, performing queuing processing on the user calling number information, the user queue information and the user waiting time prediction value to obtain user ranking information; The performing time modeling processing on the user's historical call information to obtain a user waiting time prediction model includes: S21, digitally encode the user's historical call information to obtain a user history information matrix and a user's actual waiting time vector; S22, calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model; The digital coding process of the user's historical call information is performed to obtain a user's historical information matrix and a user's actual waiting time vector, including: Performing digital coding processing on the user level information in the user historical call information to obtain the first row vector in the user historical information matrix; Performing joint digital coding processing on the call type information and the call content information in the user's historical call information to obtain a second row vector in the user's historical information matrix; The user history information matrix includes a first row vector and a second row vector; Using the actual waiting time information of each user corresponding to the historical information of each user, a vector of the actual waiting time of the user is constructed; The calculating and processing the user history information matrix and the user actual waiting time vector to obtain a user waiting time prediction model includes: The transposed matrix of the user history information matrix is ​​represented as Q, and the user actual waiting time vector is represented as v. The dimension of Q is m×n, and the dimension of v is m×1. The user waiting time prediction model to be solved is established, and its expression is: Qp=v, Among them, p is the vector to be solved in the user waiting time prediction model, and the dimension of p is n×1; The fusion solution matrix W is constructed using Q and v. The expression of the fusion solution matrix W is: W=[-v,Q], Among them, the dimension of the fusion solution matrix W is m×(n+1); Perform singular value decomposition on the fusion solution matrix W to obtain: W=TUCY H , Among them, U is the left hierarchical matrix, C is the intermediate matrix, and Y is the right decomposition matrix; Decompose the matrix Y to obtain a vector p; the expression of the decomposition process is: p(i)=Y(i+1,n+1), Where p(i) represents the i-th element of vector p, and Y(i+1,n+1) represents the element in the i+1-th row and n+1-th column of matrix Y; Substitute the vector p into the user waiting time prediction model to be solved to obtain the user waiting time prediction model; Alternatively, the calculating and processing the user history information matrix and the user actual waiting time vector to obtain the user waiting time prediction model includes: Based on the user level information, a corresponding waiting time distribution probability model is established; the expression of the waiting time distribution probability model is: Where P(k) represents the distribution probability of the waiting time when the number of people in the queue is k; the value of k is determined according to the elements of the second row of the user history information matrix, and λ is the parameter to be solved; For each user level information, based on the user actual waiting time vector and the second row vector of the user history information matrix, establish the corresponding distribution probability of the user actual waiting time; For each user level, based on the distribution probability of the actual waiting time of the user, the parameter λ in the waiting time distribution probability model is solved to obtain the value of the parameter λ; For each user level, substitute the value of parameter λ into the corresponding waiting time distribution probability model to obtain the waiting time distribution probability model of the user level; All user-level waiting time distribution probability models are combined to obtain a user waiting time prediction model.

2. The information processing method for multi-level role calling queue as claimed in claim 1, characterized in that: The queuing process is performed on the user calling number information, the user queue information and the user waiting time prediction value to obtain the user sorting information, including: Obtaining user level information of the user calling number information; When the user level information is the first priority, according to the calling type information of the user calling information, the user number corresponding to the first priority is added to the first position of the user queued information to obtain updated user queued information; When the user level information is of the second priority, the actual calling time of the user is determined according to the reservation time of the user and the predicted value of the user waiting time of the user; the user sequence number of the user is added to the user queuing information according to the value sorting of the actual calling time of the user in the user queuing time sequence in the user queuing information, and the updated user queuing information is obtained; When the user level information is the third priority, the corresponding calling type information is obtained; when the calling type information is sequential calling, the user sequence number corresponding to the third priority is added to the last bit of the user queued information; when the calling type information is repeated calling, the user sequence number corresponding to the third priority is added to the Nth bit of the user queued information to obtain the updated user queued information; Confirm the updated user queue information and sort the information for the user.

3. The information processing method for multi-level role calling queue as claimed in claim 2, characterized in that: Determining the actual calling time of the user according to the reservation time of the user and the predicted value of the user waiting time includes: Determine whether the user waiting time prediction value of the user is greater than the set time threshold T1, and obtain a first determination result. When the first determination result is no, determine the user's reservation time as the user's actual call time; When the first judgment result is yes, the actual calling time T0 of the user is determined to be TY-TC / 2, where TY is the reservation time of the user and TC is the predicted value of the user's waiting time.

4. An information processing device for multi-level role calling and queuing, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the information processing method for multi-level role calling queue as described in any one of claims 1 to 3.

5. A computer storable medium, characterized in that: The computer storable medium stores computer instructions, which, when called, are used to execute the information processing method for multi-level role calling queues as described in any one of claims 1 to 3.

6. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the information processing method for multi-level role calling queue as described in any one of claims 1 to 3.

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