Method and apparatus for outputting information

Abstract

The embodiments of the present disclosure disclose a method and device for outputting information. A specific implementation of the method includes: obtaining a set of operation order information to be sampled, wherein the operation order information includes an operator ID and an operation order ID; grouping operators according to the number of operation orders handled by each operator and setting a weight for each group of operators; calculating the number of sampled orders for each group of operators according to the predetermined sampling capacity and the weights of operators at each level; for each group of operators, extracting the number of sampled operation orders of the group of operators from the operation orders processed by the group of operators; and outputting the extracted operation order ID and operator ID. This implementation can solve the problem of low coverage when operators are sampled, and the problem of too many sampled inspections for individual operators.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and more particularly to a method and device for outputting information. Background Art

[0002] Sampling techniques is a branch of statistics that studies sampling methods in sampling surveys and methods of estimating total target quantities (including the accuracy of estimates). Generally speaking, sampling methods can be divided into two categories: probability sampling and non-probability sampling. They can also be divided into sequential sampling, simple random sampling, etc.

[0003] Sampling technology can be applied to a variety of scenarios, such as sampling of online doctor consultation forms and sampling of orders processed by customer service personnel, to implement spot checks on the quality of operators' work. In the application scenario of sampling online doctor consultation forms, it is hoped that the number of samples to be checked is certain, and it is necessary to cover doctors as evenly as possible, while ensuring that doctors with more consultation forms will have more orders to be checked, and avoiding excessive sampling of individual doctors.

[0004] The common practice at present is to use probability sampling, number all samples (i.e., the operator's operation order), generate several random values ​​within the number range through a random function, and obtain the sampling sample by matching the random value with the set number.

[0005] Existing technology can achieve randomness, but for sampling scenarios with small amounts of data, this random method cannot evenly cover the operators, resulting in insufficient coverage of the operators actually sampled.

[0006] The existing technology uses completely random sampling, which may result in individual operators being randomly sampled multiple times, which is not fair to the operators.

[0007] In real scenarios, there are many operators who handle hundreds of orders every day and many operators who handle only one or two orders every day. The existing technology randomly checks the operators according to their operation orders. Assuming a 10% probability, an operator who handles hundreds of orders every day will be inspected for 10 orders every day, while an operator who handles one order every day will only have one tenth of the orders inspected every day, which will also result in a large number of operators being unable to be covered. Summary of the invention

[0008] Embodiments of the present disclosure provide methods and devices for outputting information.

[0009] In a first aspect, an embodiment of the present disclosure provides a method for outputting information, comprising: obtaining a set of operation order information to be sampled, wherein the operation order information includes an operator identifier and an operation order identifier; grouping operators according to the number of operation orders processed by each operator and setting a weight for each group of operators; calculating the number of sampled orders for each group of operators according to a predetermined sampling capacity and the weights of operators at each level; for each group of operators, extracting the number of sampled operation orders of the group of operators from the operation orders processed by the group of operators; and outputting the extracted operation order identifier and operator identifier.

[0010] In some embodiments, a random inspection quantity of operation orders of the group of operators is extracted from the operation orders processed by the group of operators, including: grouping the group of operators according to operator identification; determining an average random inspection quantity of the group of operators based on the number of operators in the group and the number of random inspection orders; for each operator, extracting an average number of random inspection operation orders from the operation orders processed by the operator.

[0011] In some embodiments, a random inspection quantity of operation orders of the group of operators is extracted from the operation orders processed by the group of operators, including: grouping the group of operators according to operator identification; for each operator, randomly sorting the operation orders processed by the operator and generating a first sorting number for each operation order; grouping the operation orders processed by the group of operators according to the first sorting number, and grouping the operation orders with the same first sorting number; for each first sorting number, randomly sorting the operation orders corresponding to the first sorting number and generating a second sorting number for each operation order; after sorting the operation orders processed by the group of operators according to the first sorting number and the second sorting number, sampling quantity of operation orders with the highest ranking are extracted.

[0012] In some embodiments, the operation orders processed by the operator are randomly sorted, including: assigning a random number between 0 and 1 to each operation order processed by the operator; and sorting the operation orders processed by the operator in a predetermined manner according to the size of the random number.

[0013] In some embodiments, the method further includes: implementing operator identification grouping and intra-group sorting through a window function.

[0014] In a second aspect, an embodiment of the present disclosure provides a device for outputting information, comprising: an acquisition unit, configured to acquire a set of operation order information to be sampled, wherein the operation order information includes an operator identification and an operation order identification; a grouping unit, configured to group operators according to the number of operation orders handled by each operator and set weights for each group of operators; a calculation unit, configured to calculate the number of sampled orders for each group of operators according to a predetermined sampling capacity and the weights of operators at each level; an extraction unit, configured to extract, for each group of operators, a number of sampled operation orders from the operation orders handled by the group of operators; and an output unit, configured to output the extracted operation order identification and operator identification.

[0015] In some embodiments, the computing unit is further configured to: group the group of operators according to operator identification; determine the average number of spot check orders for the group of operators based on the number of operators in the group and the number of spot check orders; and for each operator, extract an average number of spot check orders, that is, operation orders processed by the operator.

[0016] In some embodiments, the computing unit is further configured to: group the group of operators according to operator identification; for each operator, randomly sort the operation orders processed by the operator and generate a first sorting number for each operation order; group the operation orders processed by the group of operators according to the first sorting number, and group the operation orders with the same first sorting number; for each first sorting number, randomly sort the operation orders corresponding to the first sorting number and generate a second sorting number for each operation order; after sorting the operation orders processed by the group of operators according to the first sorting number and the second sorting number, take the top-ranked operation orders for random inspection.

[0017] In some embodiments, the computing unit is further configured to: assign a random number between 0 and 1 to each operation order processed by the operator; and sort the operation orders processed by the operator in a predetermined manner according to the size of the random number.

[0018] In some embodiments, the computing unit is further configured to: implement operator identification grouping and intra-group sorting through a window function.

[0019] In a third aspect, an embodiment of the present disclosure provides an electronic device for outputting information, comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement any method as described in the first aspect.

[0020] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, any method in the first aspect is implemented.

[0021] The method and device for outputting information provided by the embodiments of the present disclosure maximize the coverage of operator spot checks and make the operator spot checks more uniform by performing double-group random sorting and taking the TOPN of the final double-field sorting. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Other features, objects and advantages of the present disclosure will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0023] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present disclosure may be applied;

[0024] Figure 2 is a flow chart of an embodiment of a method for outputting information according to the present disclosure;

[0025] Figure 3 is a schematic diagram of an application scenario of the method for outputting information according to the present disclosure;

[0026] Figure 4 is a flow chart of yet another embodiment of a method for outputting information according to the present disclosure;

[0027] Figure 5 is a structural schematic diagram of an embodiment of a device for outputting information according to the present disclosure;

[0028] Figure 6 It is a structural diagram of a computer system of an electronic device suitable for implementing an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] The present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0030] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0031] Figure 1 An exemplary system architecture 100 is shown to which embodiments of the method for outputting information or the apparatus for outputting information disclosed herein may be applied.

[0032] like Figure 1As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0033] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as online consultation applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0034] Terminal devices 101, 102, 103 can be hardware or software. When terminal devices 101, 102, 103 are hardware, they can be various electronic devices with display screens and supporting operation order information collection, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, Moving Picture Experts Compression Standard Audio Layer 3), MP4 (Moving Picture Experts Group Audio Layer IV, Moving Picture Experts Compression Standard Audio Layer 4) players, laptop computers and desktop computers, etc. When terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (for example, to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0035] The server 105 may be a server that provides various services, such as a background sampling server that samples the operation orders uploaded by the terminal devices 101, 102, and 103. The background sampling server may analyze and process the received sampling request and other data, and feed back the processing results (such as the extracted operation orders) to the terminal device of the sampling personnel.

[0036] It should be noted that the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, multiple software or software modules for providing distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0037] It should be noted that the method for outputting information provided in the embodiments of the present disclosure is generally executed by the server 105 , and accordingly, the device for outputting information is generally disposed in the server 105 .

[0038] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0039] Continue to refer Figure 2 , shows a process 200 of an embodiment of a method for outputting information according to the present disclosure. The method for outputting information comprises the following steps:

[0040] Step 201, obtaining a set of operation order information to be sampled.

[0041] In this embodiment, the execution subject of the method for outputting information (for example Figure 1 The server shown in the figure can receive operation order information from the terminal used by the user to perform business operations through a wired connection or a wireless connection, wherein the operation order information includes an operator identifier and an operation order identifier. The operator can be a doctor, a customer service staff, etc. The operation order can be a consultation form or an order.

[0042] Step 202: The operators are grouped according to the number of operation orders processed by each operator and a weight is set for each group of operators.

[0043] In this embodiment, the number of operation orders in each group is as uniform as possible during grouping. It can be set based on experience. The purpose of setting weights is to make operators with more operation orders be selected more often than operators with fewer operation orders, but the probability of being selected is lower than that of operators with fewer operation orders. For example, the full sample data shown in Table 1:

[0044] Doctor ID Consultation number Doctor A 123 Doctor A 124 Doctor B 125 Doctor B 126 Doctor B 127 Doctor C 128 …… ……

[0045] Table 1

[0046] In order to ensure that doctors with different order volumes can be covered to a certain extent during random inspection, doctors are grouped into the following four groups: doctors with 10 or more orders, doctors with 5 to 9 orders, doctors with 2 to 4 orders, and doctors with 1 order, and a random inspection order weight is set for each group of doctors. (Note: Although the doctors are grouped according to the number of medical consultation orders, the granularity of the actual data in each group is still the medical consultation order).

[0047] Step 203, the number of sampling orders for each group of operators is calculated according to the predetermined sampling capacity and the weights of operators at each level.

[0048] In this embodiment, as shown in Table 2 below, M is the number of medical consultation forms that are desired to be sampled (known sampling capacity), N1 to N4 are the actual number of doctors counted according to the grouping (calculated through the full sample), S1 to S4 are the set weights of each group (known), and the weights can be adjusted according to actual conditions, and M1 to M4 are the number of sample samples for each group, which can be obtained by calculation.

[0049]

[0050] Table 2

[0051] Example: Assume that there are 50 doctors with 10 or more orders, 80 doctors with 5 to 9 orders, 140 doctors with 2 to 4 orders, and 160 doctors with 1 order. If S1 to S4 are taken as the average number of orders per doctor, and S1 = 2, S2 = 1.2, S3 = 0.8, S4 = 0.5, the total number of orders to be sampled is: 50*2+80*1.2+140*0.8+160*0.5=388 orders. Since the target number of orders to be sampled is a certain number, (assuming it is 400 orders), then these 400 orders need to be redivided proportionally to clarify the number of orders that need to be extracted. For example, for doctors with more than 10 orders, the number of orders to be extracted is (50*2 / 388)*400=103 orders, and so on. The number of orders to be extracted in each category can be calculated (note that when calculating the number of the last category, the total number should be subtracted from the number of the first three categories, that is, M4=M-M1-M2-M3).

[0052] Step 204: for each group of operators, sampling a number of operation orders of the group of operators from the operation orders processed by the group of operators.

[0053] In this embodiment, as shown in the above example, for a doctor group with 10 orders or more, 103 orders need to be extracted. The same is true for other groups. A corresponding number of orders can be randomly extracted from each group.

[0054] In some optional implementations of this embodiment, sampling of the number of sampling orders of the group of operators from the operation orders processed by the group of operators includes: grouping the group of operators according to operator identification; determining the average number of sampling orders of the group of operators according to the number of operators in the group and the number of sampling orders; for each operator, sampling the average number of sampling orders of operation orders from the operation orders processed by the operator. As shown in the above example, for a doctor group with 10 orders or more, a total of 103 orders need to be sampled, of which there are 50 doctors. After each doctor samples 2 orders on average, three doctors are randomly selected to sample one order each.

[0055] Step 205: output the extracted operation order identifier and operator identifier.

[0056] In this embodiment, the extracted results can be output to the terminal of the quality inspector, who performs inspection according to the operation sheet identifier and then records the operation sheet identifier, operator identifier and inspection result.

[0057] Continue to see Figure 3 , Figure 3 FIG. 1 is a schematic diagram of an application scenario of the method for outputting information according to this embodiment. Figure 3 In the application scenario, the server performs the following steps after obtaining the doctor's consultation form:

[0058] 1. Group by doctor ID, count the medical records, and give the count field an alias of ord_cnt;

[0059] 2. Based on the data set in step 1, query the doctor id, ord_cnt, and classify according to the range to which ord_cnt belongs to form the cate field. When ord_cnt>=10, cate is assigned a value of "10 orders and above", when ord_cnt is between 5 and 9, cate is assigned a value of "5 to 9 orders", when ord_cnt is between 2 and 4, cate is assigned a value of "2 to 4 orders", and when ord_cnt is 1, cate is assigned a value of "1 order";

[0060] 3. Based on the data set in step 2, group by category, count the doctor IDs, and give the counting field an alias of doc_cnt. The doc_cnt under each category is the value of N1 to N4.

[0061] 4. According to the formula in the above table, the values ​​of M1 to M4, i.e. the number of samples to be inspected in each group, can be calculated by using the values ​​of M (known), N1 to N4 (calculated), and S1 to S4 (known). Note that M4 is calculated in the form of M-M1-M2-M3.

[0062] 5. Again, based on the data set in step 2, associate the full sample data, use the doctor ID to do the association, and query the doctor ID, consultation form ID, and cate field in the full sample data set in step 2;

[0063] 6. Based on the data set of this week 5, the full sample is split according to the cate field to obtain the split samples of each group.

[0064] 7. Conduct random sampling for each group;

[0065] 8. Combine the sampling results of each group and output the extracted doctor ID and consultation form ID.

[0066] The method provided by the above-mentioned embodiment of the present disclosure improves the coverage of random inspections and makes the number of random inspections more fair by grouping all samples and then performing sampling within the group.

[0067] Further references Figure 4 , which shows a process 400 of another embodiment of a method for outputting information. The process 400 of the method for outputting information includes the following steps:

[0068] Step 401, obtaining a set of operation order information to be sampled.

[0069] Step 402: group the operators according to the number of operation orders processed by each operator and set a weight for each group of operators.

[0070] Step 403, the number of sampling orders for each group of operators is calculated according to the predetermined sampling capacity and the weights of operators at each level.

[0071] Steps 401-403 are substantially the same as steps 201-203, and thus are not described in detail herein.

[0072] Step 404: for each group of operators, group the operators according to the operator identification.

[0073] In this embodiment, when the operator is a doctor, the doctor's consultation list with 10 or more, 5 to 9, 2 to 4, and only 1 in a period can be taken out and divided into four groups. For each group, the following steps 404-408 are performed:

[0074] The following is a detailed description of the group of doctors with 10 or more orders:

[0075] Query the doctor ID and medical consultation form ID, and group the medical consultation forms handled by the same doctor.

[0076] Step 405: For each operator, the operation sheets processed by the operator are randomly sorted and a first sorting sequence number is generated for each operation sheet.

[0077] In this embodiment, a random value r1 is created for each medical consultation form, and r1 is calculated using the rand() function. The rand() function returns a random decimal between 0 and 1, such as 0.36361513486289558. Group by doctor id, sort by r1 within the group, and create the first sorting sequence seq1. Grouping and sorting within the group can be achieved using window functions.

[0078] Step 406: group the operation orders processed by the group of operators according to the first sorting sequence number, and group the operation orders with the same first sorting sequence number.

[0079] In this embodiment, the random results of step 405 are rearranged and sorted.

[0080] The effect data is shown in the following table:

[0081] Doctor ID Medical consultation form ID seq1 Doctor A 123 1 Doctor A 124 2 Doctor B 125 1 Doctor B 126 2 Doctor B 127 3 Doctor C 128 1 Doctor C 129 2

[0082] Table 3

[0083] Step 407: for each first sorting sequence number, randomly sort the operation sheets corresponding to the first sorting sequence number and generate a second sorting sequence number for each operation sheet.

[0084] In this embodiment, based on the data set of step 406, the doctor id, the consultation form id, and the seq1 created in step 406 are queried, and a random value r2 is created for each consultation form, and r2 is calculated using the rand() function. Group by seq1, sort by r2 within the group, and create the second sorting sequence number seq2 of the sorting field, and the grouping and sorting within the group are implemented using window functions.

[0085] The effect data is shown in the following table:

[0086] seq1 Doctor ID Medical consultation form ID seq2 1 Doctor A 123 1 1 Doctor B 125 2 1 Doctor C 128 3 3 Doctor B 127 1 2 Doctor A 124 1 2 Doctor B 129 2 2 Doctor C 126 3

[0087] Table 4

[0088] Step 408: After the operation orders processed by the group of operators are sorted according to the first sorting sequence number and the second sorting sequence number, the number of operation orders with the highest ranking are selected for random inspection.

[0089] In this embodiment, based on the data set in step 407, seq1 and seq2 are sorted respectively;

[0090] The effect data is shown in the following table:

[0091]

[0092] Table 5

[0093] Based on the sorting results in Table 5, the topM1 (M1 is the number of data to be extracted for this group) data are intercepted to complete the sampling of this group of data. Similarly, the sampling processing of the other three groups can be completed.

[0094] Step 409: Output the extracted operation sheet ID and operator ID

[0095] In this embodiment, the extracted results can be output to the terminal of the quality inspector, who performs inspection according to the operation sheet identifier and then records the operation sheet identifier, operator identifier and inspection result.

[0096] from Figure 4 It can be seen that Figure 2Compared with the corresponding embodiment, the process 400 of the method for outputting information in this embodiment embodies the steps of performing double sorting. Therefore, the scheme described in this embodiment maximizes the coverage of operation sampling through double grouping random sorting and takes the TOP N of the final double field sorting, while making the operation sampling more uniform. The two-grouping random sorting is: grouping by operator, random sorting of operation within the group; grouping by the sorting value of the first result, and random sorting of operators within the group.

[0097] Further references Figure 5 As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a device for outputting information. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0098] like Figure 5 As shown, the device 500 for outputting information in this embodiment includes: an acquisition unit 501, a grouping unit 502, a calculation unit 503, an extraction unit 504 and an output unit 505. The acquisition unit 501 is configured to acquire a set of operation order information to be sampled, wherein the operation order information includes an operator identifier and an operation order identifier; the grouping unit 502 is configured to group operators according to the number of operation orders processed by each operator and set a weight for each group of operators; the calculation unit 503 is configured to calculate the number of sampled orders for each group of operators according to the predetermined sampling capacity and the weights of operators at all levels; the extraction unit 504 is configured to extract, for each group of operators, the number of sampled operation orders of the group of operators from the operation orders processed by the group of operators; and the output unit 505 is configured to output the extracted operation order identifier and operator identifier.

[0099] In this embodiment, the specific processing of the acquisition unit 501, the grouping unit 502, the calculation unit 503, the extraction unit 504 and the output unit 505 of the device 500 for outputting information can be referred to. Figure 2 Corresponding to step 201, step 202, step 203, step 204 and step 205 in the embodiment.

[0100] In some optional implementations of this embodiment, the computing unit 503 is further configured to: group the group of operators according to operator identification; determine the average number of spot check orders for the group of operators based on the number of operators in the group and the number of spot check orders; and for each operator, extract an average number of spot check orders, i.e., operation orders, from the operation orders processed by the operator.

[0101] In some optional implementations of the present embodiment, the computing unit 503 is further configured to: group the group of operators according to operator identification; for each operator, randomly sort the operation orders processed by the operator and generate a first sorting number for each operation order; group the operation orders processed by the group of operators according to the first sorting number, and group the operation orders with the same first sorting number as one group; for each first sorting number, randomly sort the operation orders corresponding to the first sorting number and generate a second sorting number for each operation order; after sorting the operation orders processed by the group of operators according to the first sorting number and the second sorting number, take the top-ranked operation orders for random inspection.

[0102] In some optional implementations of this embodiment, the calculation unit 503 is further configured to: assign a random number between 0 and 1 to each operation order processed by the operator; and sort the operation orders processed by the operator in a predetermined manner according to the size of the random number.

[0103] In some optional implementations of this embodiment, the calculation unit 503 is further configured to: implement operator identification grouping and intra-group sorting through a window function.

[0104] Reference below Figure 6 , which shows an electronic device (eg, Figure 1 The terminal device in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The terminal device / server shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0105] like Figure 6 As shown, the electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0106] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 6 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0107] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, the above functions defined in the method of the embodiment of the present disclosure are executed. It should be noted that the computer-readable medium described in the embodiment of the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In an embodiment of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus, or a device. In an embodiment of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus, or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wire, optical cable, RF (radio frequency), etc., or any suitable combination of the foregoing.

[0108] The computer-readable medium may be included in the electronic device; or it may exist independently without being assembled into the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains a set of operation order information to be sampled, wherein the operation order information includes an operator identifier and an operation order identifier; groups operators according to the number of operation orders processed by each operator and sets a weight for each group of operators; calculates the number of sample orders for each group of operators according to the predetermined sampling capacity and the weights of operators at each level; for each group of operators, extracts the number of sample orders of the group of operators from the operation orders processed by the group of operators; and outputs the extracted operation order identifier and operator identifier.

[0109] Computer program code for performing the operations of embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0110] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0111] The units involved in the embodiments described in the present disclosure may be implemented by software or by hardware. The units described may also be provided in a processor, for example, may be described as: a processor including an acquisition unit, a grouping unit, a calculation unit, an extraction unit, and an output unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the acquisition unit may also be described as a "unit for acquiring a set of operation order information to be sampled".

[0112] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present disclosure is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other.

Claims

1. A method for outputting information, comprising: Obtaining a set of operation order information to be sampled, wherein the operation order information includes an operator ID and an operation order ID; The operators are grouped according to the number of operation orders handled by each operator and a weight is set for each group of operators, wherein the weight is such that the operator with more operation orders is selected more often than the operator with fewer operation orders, but the probability of being selected is lower than that of the operator with fewer operation orders; The number of sampling orders for each group of operators is calculated based on the predetermined sampling capacity and the weights of operators at each level; For each group of operators, select the sampling inspection orders of the group of operators from the operation orders processed by the group of operators; Output the extracted operation order ID and operator ID; The step of extracting a number of sampling operation orders of the group of operators from the operation orders processed by the group of operators includes: The group of operators is grouped by operator ID; For each operator, the operation orders processed by the operator are randomly sorted and a first sorting sequence number is generated for each operation order; The operation orders processed by the group of operators are grouped according to the first sorting sequence number, and the operation orders with the same first sorting sequence number are grouped together; For each first sorting sequence number, randomly sort the operation orders corresponding to the first sorting sequence number and generate a second sorting sequence number for each operation order; After the operation orders handled by this group of operators are sorted according to the first sorting sequence number and the second sorting sequence number, the number of operation orders with the highest ranking are taken for random inspection.

2. The method according to claim 1, wherein: The step of extracting a number of sampling operation orders of the group of operators from the operation orders processed by the group of operators includes: The group of operators is grouped by operator ID; Determine the average number of sampling orders for the group of operators based on the number of operators in the group and the number of sampling orders; For each operator, an average number of sampling orders is extracted from the operation orders processed by the operator.

3. The method according to claim 1, wherein: The randomly sorting the operation orders processed by the operator comprises: Assign a random number between 0 and 1 to each operation order processed by the operator; The operation orders processed by the operator are sorted in a predetermined manner according to the size of the random number.

4. The method according to claim 1, wherein: The method further comprises: Operator ID grouping and intra-group sorting are implemented through window functions.

5. A device for outputting information, comprising: An acquisition unit is configured to acquire an operation order information set to be sampled, wherein the operation order information includes an operator identifier and an operation order identifier; a grouping unit configured to group the operators according to the number of operation orders processed by each operator and set a weight for each group of operators, wherein the weight is such that the operator with more operation orders is selected more often than the operator with less operation orders, but has a lower probability of being selected than the operator with less operation orders; A calculation unit, configured to calculate the number of sampling orders for each group of operators according to a predetermined sampling capacity and weights of operators at each level; The extraction unit is configured to extract, for each group of operators, a sampling number of operation orders of the group of operators from the operation orders processed by the group of operators; an output unit configured to output the extracted operation order identification and operator identification; Wherein, the computing unit is further configured to: The group of operators is grouped by operator ID; For each operator, the operation orders processed by the operator are randomly sorted and a first sorting sequence number is generated for each operation order; The operation orders processed by the group of operators are grouped according to the first sorting sequence number, and the operation orders with the same first sorting sequence number are grouped together; For each first sorting sequence number, randomly sort the operation orders corresponding to the first sorting sequence number and generate a second sorting sequence number for each operation order; After the operation orders handled by this group of operators are sorted according to the first sorting sequence number and the second sorting sequence number, the number of operation orders with the highest ranking are taken for random inspection.

6. The device according to claim 5, wherein: The computing unit is further configured to: The group of operators is grouped by operator ID; Determine the average number of sampling orders for the group of operators based on the number of operators in the group and the number of sampling orders; For each operator, an average number of sampling orders is extracted from the operation orders processed by the operator.

7. The device according to claim 5, wherein: The computing unit is further configured to: Assign a random number between 0 and 1 to each operation order processed by the operator; The operation orders processed by the operator are sorted in a predetermined manner according to the size of the random number.

8. The device according to claim 5, wherein: The computing unit is further configured to: Operator ID grouping and intra-group sorting are implemented through window functions.

9. An electronic device for outputting information, comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

10. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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