Information push method, device, mobile terminal and storage medium

Abstract

The disclosed embodiments disclose an information push method, device, mobile terminal and storage medium. The information push method includes: determining a model based on user capability characterization data corresponding to a user, determining theoretical user capability characterization data corresponding to a first pushed information that has been pushed to the user; determining actual user capability characterization data corresponding to the first pushed information based on the user's feedback on the first pushed information; adjusting the theoretical user capability characterization data based on the actual user capability characterization data; determining information to be pushed corresponding to the adjusted theoretical user capability characterization data; and pushing the information to be pushed to the user. The technical solution of the disclosed embodiments achieves the effect of pushing information that matches the user's capability to the user.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of computer data processing, and in particular to an information push method, device, mobile terminal, and storage medium. Background Art

[0002] With the rapid development of computer technology and the Internet, information push based on the Internet has been widely used. Users can obtain and process information through the information push system.

[0003] Existing information push systems usually push the same information to each user based on a fixed push mode when pushing information.

[0004] If the information pushed by this push method is difficult to process, it will dampen the enthusiasm of users with poor information processing capabilities. If the processing difficulty is easy, it will reduce the interest of users with higher information processing capabilities. In addition, this push method cannot well reflect the actual situation of the information processor's grasp of the information. Summary of the invention

[0005] The present disclosure provides an information push method, device, mobile terminal and storage medium to achieve the effect of pushing information matching the user's capabilities to the user.

[0006] In a first aspect, an embodiment of the present disclosure provides an information push method, including:

[0007] Determine a model based on the user capability characterization data corresponding to the user, and determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user;

[0008] Determining actual user capability representation data corresponding to the first pushed information according to the user's feedback on the first pushed information;

[0009] Adjusting the theoretical user capability characterization data according to the actual user capability characterization data;

[0010] Determining information to be pushed corresponding to the adjusted theoretical user capability representation data; and

[0011] Push the information to be pushed to the user.

[0012] In a second aspect, the embodiment of the present disclosure further provides an information push device, including:

[0013] a theoretical user capability characterization data determination module, configured to determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user according to a user capability characterization data determination model corresponding to the user;

[0014] an actual user capability characterization data determination module, configured to determine actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information;

[0015] A theoretical user capability characterization data adjustment module, used to adjust the theoretical user capability characterization data according to the actual user capability characterization data;

[0016] A module for determining and pushing information to be pushed, used for determining information to be pushed corresponding to the adjusted theoretical user capability representation data; and

[0017] Push the information to be pushed to the user.

[0018] In a third aspect, an embodiment of the present disclosure further provides a mobile terminal, including:

[0019] one or more processing devices;

[0020] A storage device for storing one or more programs;

[0021] When one or more programs are executed by one or more processing devices, the one or more processing devices implement the information push method as described in any embodiment of the present disclosure.

[0022] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the information push method as described in any embodiment of the present disclosure is implemented.

[0023] The disclosed embodiment determines a model based on user capability characterization data corresponding to a user, determines theoretical user capability characterization data corresponding to first pushed information that has been pushed to the user; determines actual user capability characterization data corresponding to the first pushed information based on the user's feedback on the first pushed information; adjusts the theoretical user capability characterization data based on the actual user capability characterization data; determines information to be pushed corresponding to the adjusted theoretical user capability characterization data, and pushes the information to be pushed to the user, thereby overcoming the problem in the prior art that it is difficult to match the information pushed with the user's current capability to process information, and achieves the effect of pushing information that matches the user's capability to the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0025] Figure 1 A flowchart of an information push method provided in Embodiment 1 of the present disclosure;

[0026] Figure 2 A flowchart of an information push method provided in Embodiment 2 of the present disclosure;

[0027] Figure 3 A schematic diagram of the structure of an information push device provided in Embodiment 3 of the present disclosure;

[0028] Figure 4 A structural diagram of a mobile terminal provided in Embodiment 4 of the present disclosure. DETAILED DESCRIPTION

[0029] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0030] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0031] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0032] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0033] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0034] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0035] Embodiment 1

[0036] Figure 1 This is a flow chart of an information push method provided by an embodiment of the present disclosure. This embodiment is applicable to the case of information push for users. The method can be executed by an information push device. The device can be implemented in software and / or hardware. The device can be configured in a mobile terminal. Figure 1 As shown, the method may include the following steps:

[0037] S110 . Determine a model according to the user capability characterization data corresponding to the user, and determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user.

[0038] The first pushed information is information that has been pushed to the user within a preset time period before the current pushed information. In this embodiment, the information may be data that the system pushes to the user and that the user needs to process. Preferably, the information may be various tasks with difficulty coefficients, wherein the tasks may be various questions with definite answers, etc.

[0039] The user capability characterization data reflects the corresponding information processing level when the user processes the corresponding information. Exemplarily, the user capability characterization data can be a score or a level, etc. Different users correspond to different user capability characterization data determination models. The user capability characterization data determination model is related to the information and the user capability characterization data. Once the user capability characterization data determination model is determined, each user capability characterization data corresponding to each information is also determined. The theoretical user capability characterization data can be determined using the user capability characterization data determination model and the first pushed information. Among them, the theoretical user capability characterization data reflects the information processing level that the user theoretically needs to have when processing the first pushed information. The theoretical user capability characterization data is related to the first pushed information. If the first pushed information is determined, the theoretical user capability characterization data is determined, and it will not change with the feedback of the first pushed information.

[0040] Exemplarily, if the information is a question, the user capability characterization data may be a theoretical score corresponding to the question, and accordingly, the user capability characterization data determination model may be related to the question and the theoretical score. The first pushed information may include one or more information, and one information corresponds to one user capability characterization data. If the first pushed information includes multiple information, the theoretical user capability characterization data may preferably be the average of multiple user capability characterization data, and it is understandable that it may also be the sum of multiple user capability characterization data.

[0041] Exemplarily, if the first pushed information is a plurality of topics, the user capability characterization data may be used to determine a model to determine a plurality of theoretical scores corresponding to the plurality of topics. Accordingly, the theoretical user capability characterization data is an average theoretical score of the plurality of theoretical scores.

[0042] S120: Determine actual user capability representation data corresponding to the first pushed information according to the user's feedback on the first pushed information.

[0043] Among them, the feedback can preferably be the processing result data of the user on the first pushed information, and the processing result data can include whether the processing result corresponding to each first pushed information is correct, and can also include the processing time corresponding to each first pushed information processed by the user. The actual user capability characterization data reflects the actual information processing level of the user when processing the first pushed information. Exemplarily, if the processing result corresponding to a message is an error, the actual user capability characterization data corresponding to the message can preferably be zero or user capability characterization data below a preset threshold; if the processing result corresponding to a message is correct, the actual user capability characterization data corresponding to the message can preferably be the user capability characterization data corresponding to the message in the user capability characterization data determination model; if the processing time corresponding to a message is very long (compared with the preset time length), the actual user capability characterization data corresponding to the message can preferably be user capability characterization data below the preset threshold; if the processing time corresponding to a message is very short (compared with the preset time length), the actual user capability characterization data corresponding to the message can preferably be user capability characterization data above the preset threshold.

[0044] S130: Adjust the theoretical user capability characterization data according to the actual user capability characterization data.

[0045] In this embodiment, in order to match the pushed information with the user's capabilities, preferably, the theoretical user capability characterization data can be adjusted according to the actual user capability characterization data, and the adjustment method can be to increase the theoretical user capability characterization data or to decrease the theoretical user capability characterization data.

[0046] S140, determining information to be pushed corresponding to the adjusted theoretical user capability representation data; and pushing the information to be pushed to the user.

[0047] Preferably, the user capability characterization data can be used to determine the model to determine the information to be pushed corresponding to the adjusted theoretical user capability characterization data, wherein the number of information to be pushed can be one or more. When the number of information to be pushed is multiple, the multiple information to be pushed can be information with the same difficulty coefficient or information with different difficulty coefficients.

[0048] The present embodiment provides an information push method, which determines a model according to user capability characterization data corresponding to the user, determines theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user; determines actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information; adjusts the theoretical user capability characterization data according to the actual user capability characterization data; determines information to be pushed corresponding to the adjusted theoretical user capability characterization data; and pushes the information to be pushed to the user, thereby overcoming the problem in the prior art that it is difficult for the information pushed to match the user's current ability to process information, and achieves the effect of pushing information that matches the user's ability to the user.

[0049] On the basis of the above embodiments, further, the user capability characterization data determination model includes:

[0050] A first relationship curve between the information difficulty characterization data and the first user ability characterization data and a second relationship curve between the information complexity characterization data and the second user ability characterization data.

[0051] Taking information as the topic and user capability characterization data as the score as an example, the user capability characterization data determination model is specifically described:

[0052] The information difficulty characterization data is the question correctness rate, and the question correctness rate corresponding to each question can preferably be determined based on the historical processing result data of all users corresponding to each question. For example, the number of all users corresponding to a question is 1000, among which the historical processing results of 100 users are correct and the historical processing results of 900 users are wrong, then the question correctness rate corresponding to the question is (100 / 1000)*100%=10%.

[0053] The first user capability characterization data is determined based on the user's historical processing result data, and corresponds to the first theoretical score one by one with the above-mentioned question correctness rate. Preferably, the first theoretical score ranges from 0 to 10. Exemplarily, the user's information processing level is relatively high, and for multiple questions with a question correctness rate of 10%, the historical processing results show that the correctness rate is 90%. At this time, if the first theoretical score corresponding to the question correctness rate of 10% determined by using the above-mentioned historical processing result data of all users is 1, then for this user, the first theoretical score corresponding to the question correctness rate of 10% is 9.

[0054] The data representing information complexity is processing time. The processing time corresponding to each question can preferably be determined based on the historical processing result data of all users corresponding to each question. For example, the number of all users corresponding to a question is 1000, among which the historical processing time of 100 users is 2 minutes, the historical processing time of 300 users is 3 minutes, the historical processing time of 400 users is 4 minutes, and the historical processing time of 200 users is 5 minutes. Then the processing time corresponding to the question is (100*2+300*3+400*4+200*5) / 1000=3.7 minutes.

[0055] The second user capability characterization data is a second theoretical score corresponding to the processing time determined based on the user's historical processing result data. Preferably, the second theoretical score may range from 1 to 10. Exemplarily, the user has a high level of information processing. For multiple questions with a processing time of 3.7 minutes, the historical processing results show that the processing time is 2 minutes. At this time, if the first theoretical score corresponding to the processing time of 3.7 minutes determined by using the historical processing result data of all users is 4, then for this user, the first theoretical score corresponding to the processing time of 3.7 minutes may be 7.4.

[0056] It should be noted that, for new users, the questions that the system pushes to new users for the first time are determined based on the standard user ability characterization data determination model. Among them, the first relationship curve and the second relationship curve in the standard user ability characterization data determination model are determined based on the historical processing result data of all users corresponding to each question. For example, the first theoretical score corresponding to a question accuracy rate of 10% is 1, and the first theoretical score corresponding to a processing time of 3.7 minutes is 4. Afterwards, as the number of questions processed by the user increases, the first user ability characterization data and the second user ability characterization data are adjusted on the basis of the standard user ability characterization data determination model to obtain a personalized user ability characterization data determination model corresponding to the user. The specific adjustment method is similar to the method for determining the first user ability characterization data and the second user ability characterization data described above, and will not be repeated here.

[0057] On the basis of the above embodiments, further, according to the user's feedback on the first pushed information, determining the actual user capability representation data corresponding to the first pushed information includes:

[0058] Determine the second pushed information, wherein the second pushed information is the first pushed information that is fed back as correct;

[0059] According to the information difficulty characterization data corresponding to the second pushed information, the user ability characterization data is used to determine the model to determine the first user ability characterization data corresponding to the second pushed information;

[0060] According to the information complexity characterization data corresponding to the first pushed information, the user capability characterization data is used to determine the model, and the second user capability characterization data corresponding to the first pushed information is determined;

[0061] The actual user capability characterization data corresponding to the first pushed information is determined using the first user capability characterization data, the first preset weight corresponding to the first user capability characterization data, the second user capability characterization data, and the second preset weight corresponding to the second user capability characterization data.

[0062] Still taking information as the topic and user capability representation data as the score as an example, the above steps are explained in detail:

[0063] Determine each second question that is fed back as correct, determine the model using the user capability characterization data, determine the first theoretical score of each second question based on the correctness of each second question, and determine the second theoretical score of each first question based on the processing time of each first question. It can be understood that for each first question that is fed back as incorrect, the corresponding first theoretical score is 0.

[0064] Preferably, the actual user capability characterization data can be determined according to w1*a+w2*b, wherein w1 is the first preset weight corresponding to the first theoretical score, w2 is the second preset weight corresponding to the second theoretical score, a is the first theoretical score, and b is the second theoretical score. The values ​​of w1 and w2 are not specifically limited here, and the best values ​​are the values ​​corresponding to the best actual user capability characterization data obtained.

[0065] On the basis of the above embodiments, further, if it is determined that the number of historical information pushed is higher than the preset number, the first user ability characterization data determination model is determined according to the user's feedback on the historical information and the information difficulty characterization data corresponding to the historical information, and the first user ability characterization data determination model is used as the user ability characterization data determination model.

[0066] The method for determining the first user capability characterization data determination model is similar to the method for determining the user capability characterization data determination model based on the standard user capability characterization data determination model, and will not be described in detail herein.

[0067] Embodiment 2

[0068] Figure 2 This is a flow chart of an information push method provided in Embodiment 2 of the present disclosure. This embodiment can be combined with various optional solutions in one or more of the above embodiments. In this embodiment,

[0069] The adjusting the theoretical user capability characterization data according to the actual user capability characterization data includes:

[0070] Determining a first absolute value of a difference between the actual user capability characterization data and the theoretical user capability characterization data;

[0071] According to a preset transfer function, adjusting the first absolute value to obtain a second absolute value;

[0072] If the actual user capability characterization data is greater than the theoretical user capability characterization data, performing a subtraction operation on the second absolute value using the theoretical user capability characterization data;

[0073] If the actual user capability characterization data is smaller than the theoretical user capability characterization data, the second absolute value is added using the theoretical user capability characterization data.

[0074] like Figure 2 As shown, the method may include the following steps:

[0075] S210: Determine a model according to the user capability characterization data corresponding to the user, and determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user.

[0076] S220: Determine actual user capability representation data corresponding to the first pushed information according to the user's feedback on the first pushed information.

[0077] S230: Determine a first absolute value of a difference between actual user capability characterization data and theoretical user capability characterization data.

[0078] S240: Adjust the first absolute value according to a preset transfer function to obtain a second absolute value.

[0079] S250: If the actual user capability characterization data is greater than the theoretical user capability characterization data, perform a subtraction operation on the second absolute value using the theoretical user capability characterization data.

[0080] S260: If the actual user capability characterization data is smaller than the theoretical user capability characterization data, perform an addition operation on the second absolute value using the theoretical user capability characterization data.

[0081] The above steps S230-S260 are based on the feedback principle and use the actual user capability characterization data to adjust the theoretical user capability characterization data. The preset transfer function may preferably be a PID (proportional, integral, differential) transfer function.

[0082] If the actual user capability characterization data is greater than the theoretical user capability characterization data, it means that the first push information is relatively simple for the current user, and the difficulty of the first push information needs to be increased. Therefore, the second absolute value is subtracted using the theoretical user capability characterization data.

[0083] If the actual user capability characterization data is less than the theoretical user capability characterization data, it means that the first push information is relatively difficult for the current user, and the difficulty of the first push information needs to be reduced. Therefore, the second absolute value is added using the theoretical user capability characterization data.

[0084] S270, determining the information to be pushed corresponding to the adjusted theoretical user capability representation data; and pushing the information to be pushed to the user.

[0085] The present embodiment provides an information push method, which determines a model according to user capability characterization data corresponding to a user, determines theoretical user capability characterization data corresponding to first pushed information that has been pushed to the user; determines actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information; determines a first absolute value of the difference between the actual user capability characterization data and the theoretical user capability characterization data; adjusts the first absolute value according to a preset transfer function to obtain a second absolute value; if the actual user capability characterization data is greater than the theoretical user capability characterization data, subtracts the second absolute value using the theoretical user capability characterization data; if the actual user capability characterization data is less than the theoretical user capability characterization data, adds the second absolute value using the theoretical user capability characterization data; determines information to be pushed corresponding to the adjusted theoretical user capability characterization data; and pushes the information to be pushed to the user, which overcomes the problem in the prior art that it is difficult for the pushed information to match the user's current ability to process information, and achieves the effect of pushing information that matches the user's ability to the user.

[0086] On the basis of the above embodiments, further determining the information to be pushed corresponding to the adjusted theoretical user capability representation data includes:

[0087] If the number of information to be pushed is one, determining the first information difficulty representation data corresponding to the adjusted theoretical user ability representation data by using the user ability representation data determination model according to the adjusted theoretical user ability representation data;

[0088] According to the first information difficulty characterization data, information to be pushed corresponding to the first information difficulty characterization data is determined.

[0089] Still taking information as the topic and user capability representation data as the score as an example, the above steps are explained in detail:

[0090] If the number of questions to be pushed is one, then according to the adjusted theoretical score, the model is determined using the user ability representation data to determine the accuracy of the first question corresponding to the adjusted theoretical score, and based on the accuracy of the first question, the question to be pushed corresponding to the accuracy of the question is determined.

[0091] On the basis of the above embodiments, further determining the information to be pushed corresponding to the adjusted theoretical user capability representation data also includes:

[0092] If the number of information to be pushed is at least two, and the information difficulty representation data corresponding to each information to be pushed is different, determining the first user ability representation data corresponding to each information to be pushed according to the adjusted theoretical user ability representation data and the preset user ability representation data allocation ratio;

[0093] According to the first user capability characterization data corresponding to each piece of information to be pushed, a model is determined using the user capability characterization data to determine the second information difficulty characterization data corresponding to each adjusted theoretical user capability characterization data;

[0094] According to each second information difficulty representation data, the to-be-pushed information corresponding to each second information difficulty representation data is determined.

[0095] Still taking information as the topic and user capability representation data as the score as an example, the above steps are explained in detail:

[0096] If there are three questions to be pushed, and the correctness rate of each question to be pushed is different, the first theoretical score corresponding to each question to be pushed is determined according to the adjusted theoretical score and the preset score allocation ratio. For example, the adjusted theoretical score is 7, and the preset score allocation ratio is 1:2:3, then the first theoretical scores corresponding to the three questions to be pushed are 3.5, 7 and 10.5 respectively.

[0097] According to the first theoretical score corresponding to each to-be-pushed topic, the user capability characterization data is used to determine the model, and the accuracy rate of the second topic corresponding to each first theoretical score is determined. According to the accuracy rate of each second topic, the to-be-pushed topic corresponding to each second topic accuracy rate is determined.

[0098] Embodiment 3

[0099] Figure 3 This is a schematic diagram of the structure of an information push device provided in the third embodiment of the present disclosure. This embodiment is applicable to the case of pushing information to users. The device can be implemented in software and / or hardware, and the device can be configured in a mobile terminal. Figure 3As shown, the device may include: a theoretical user capability characterization data determination module 310 , an actual user capability characterization data determination module 320 , a theoretical user capability characterization data adjustment module 330 , and a to-be-pushed information determination and push module 340 .

[0100] The theoretical user capability characterization data determination module 310 is used to determine the theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user according to the user capability characterization data determination model corresponding to the user;

[0101] The actual user capability characterization data determination module 320 is used to determine the actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information;

[0102] Theoretical user capability characterization data adjustment module 330, used to adjust the theoretical user capability characterization data according to the actual user capability characterization data;

[0103] The module 340 for determining and pushing information to be pushed is used to determine the information to be pushed corresponding to the adjusted theoretical user capability representation data; and push the information to be pushed to the user.

[0104] The present embodiment provides an information pushing device, which determines theoretical user capability characterization data corresponding to first pushed information that has been pushed to the user according to a user capability characterization data determination model corresponding to the user through a theoretical user capability characterization data determination module; determines actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information through an actual user capability characterization data determination module; adjusts the theoretical user capability characterization data according to the actual user capability characterization data through a theoretical user capability characterization data adjustment module; determines information to be pushed corresponding to the adjusted theoretical user capability characterization data through a module for determining and pushing information to be pushed; and pushes the information to be pushed to the user, thereby overcoming the problem in the prior art that it is difficult for the information pushed to match the user's current ability to process information, and achieving the effect of pushing information that matches the user's ability to the user.

[0105] Based on the above technical solution, optionally, the user capability characterization data determination model includes:

[0106] A first relationship curve between the information difficulty characterization data and the first user ability characterization data and a second relationship curve between the information complexity characterization data and the second user ability characterization data.

[0107] Based on the above technical solution, optionally, the actual user capability characterization data determination module 320 may specifically include:

[0108] A second pushed information determining unit, configured to determine second pushed information, wherein the second pushed information is the first pushed information that is fed back as correct;

[0109] a first user capability characterization data determining unit, configured to determine the first user capability characterization data corresponding to the second pushed information by using a user capability characterization data determination model according to the information difficulty characterization data corresponding to the second pushed information;

[0110] A second user capability characterization data determination unit, configured to determine the second user capability characterization data corresponding to the first pushed information by using a user capability characterization data determination model according to the information complexity characterization data corresponding to the first pushed information;

[0111] The actual user capability characterization data determination unit is used to determine the actual user capability characterization data corresponding to the first pushed information by using the first user capability characterization data, the first preset weight corresponding to the first user capability characterization data, the second user capability characterization data and the second preset weight corresponding to the second user capability characterization data.

[0112] Based on the above technical solution, optionally, the theoretical user capability representation data adjustment module 330 may specifically include:

[0113] A first absolute value determining unit, used to determine a first absolute value of a difference between actual user capability characterization data and theoretical user capability characterization data;

[0114] a second absolute value determining unit, configured to adjust the first absolute value according to a preset transfer function to obtain a second absolute value;

[0115] a subtraction unit, configured to perform a subtraction operation on the second absolute value using the theoretical user capability characterization data if the actual user capability characterization data is greater than the theoretical user capability characterization data;

[0116] The adding unit is used to perform an adding operation on the second absolute value by using the theoretical user capability characterization data if the actual user capability characterization data is smaller than the theoretical user capability characterization data.

[0117] Based on the above technical solution, optionally, the module 440 for determining and pushing information to be pushed may specifically include:

[0118] a first information difficulty characterization data determining unit, configured to determine, if the number of information to be pushed is one, first information difficulty characterization data corresponding to the adjusted theoretical user ability characterization data by using a user ability characterization data determination model according to the adjusted theoretical user ability characterization data;

[0119] The first information to be pushed determining unit is used to determine the information to be pushed corresponding to the first information difficulty representation data according to the first information difficulty representation data.

[0120] Based on the above technical solution, optionally, the module 440 for determining and pushing information to be pushed may specifically include:

[0121] a first user capability characterization data determining unit corresponding to the information to be pushed, configured to determine the first user capability characterization data corresponding to each information to be pushed according to the adjusted theoretical user capability characterization data and the preset user capability characterization data allocation ratio if the number of the information to be pushed is at least two and the information difficulty characterization data corresponding to each information to be pushed is different;

[0122] A second information difficulty characterization data determination unit, configured to determine, based on the first user ability characterization data corresponding to each piece of information to be pushed, second information difficulty characterization data corresponding to each adjusted theoretical user ability characterization data by using a user ability characterization data determination model;

[0123] The second to-be-pushed information determining unit is configured to determine, according to each second information difficulty representation data, the to-be-pushed information corresponding to each second information difficulty representation data.

[0124] On the basis of the above technical solution, optionally, the information push device may further include:

[0125] The user capability characterization data determination model adjustment module is used to determine the first user capability characterization data determination model based on the user's feedback on the historical information and the information difficulty characterization data corresponding to the historical information if it is determined that the number of historical information pushed is higher than the preset number, and use the first user capability characterization data determination model as the user capability characterization data determination model.

[0126] The information push device provided in the embodiment of the present disclosure can execute the information push method provided in the embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] Embodiment 4

[0128] Reference below Figure 4 , which shows a schematic diagram of the structure of a mobile terminal 400 suitable for implementing the embodiments of the present disclosure. The mobile terminal in the embodiments of the present disclosure may include, but is not limited to, a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (such as a vehicle navigation terminal), and the like. Figure 4 The mobile terminal 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.

[0129] like Figure 4 As shown, the mobile terminal 400 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 406 to a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the mobile terminal 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0130] Typically, the following devices may be connected to the I / O interface 405: an input device 406 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 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 406 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the mobile terminal 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The mobile terminal 400 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0131] 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 non-transitory computer-readable medium, and the computer program contains 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 the communication device 409, or installed from the storage device 406, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0132] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may 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 wires, 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 the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In 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. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The 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 conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0133] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0134] The computer-readable medium may be included in the mobile terminal, or may exist independently without being installed in the mobile terminal.

[0135] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the mobile terminal, the mobile terminal: determines a model based on the user capability characterization data corresponding to the user, and determines the theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user; determines the actual user capability characterization data corresponding to the first pushed information based on the user's feedback on the first pushed information; adjusts the theoretical user capability characterization data based on the actual user capability characterization data; determines the information to be pushed corresponding to the adjusted theoretical user capability characterization data; and pushes the information to be pushed to the user.

[0136] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, 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 the user's computer, partially on the user's computer, as a separate software package, partially on the 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 through 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., through the Internet using an Internet service provider).

[0137] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the methods, devices, mobile terminals and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of a code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two 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 box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart 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.

[0138] The modules, units and sub-units involved in the embodiments described in the present disclosure may be implemented by software or by hardware. The name of a module, unit or sub-unit does not, in some cases, constitute a limitation on the module, unit or sub-unit itself. For example, the actual user capability characterization data determination module may also be described as "a module that determines the actual user capability characterization data corresponding to the first pushed information based on the user's feedback on the first pushed information", and the second pushed information determination unit may also be described as "a unit that determines the second pushed information, wherein the second pushed information is the first pushed information that is fed back as correct".

[0139] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0140] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0141] According to one or more embodiments of the present disclosure, Example 1 provides an information push method, including:

[0142] Determine a model based on the user capability characterization data corresponding to the user, and determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user;

[0143] Determining actual user capability representation data corresponding to the first pushed information according to user feedback on the first pushed information;

[0144] Adjust the theoretical user capability representation data according to the actual user capability representation data;

[0145] Determining information to be pushed corresponding to the adjusted theoretical user capability representation data; and

[0146] Push the information to be pushed to the user.

[0147] According to one or more embodiments of the present disclosure, Example 2 provides an information push method. Based on the information push method of Example 1, the user capability characterization data determination model includes:

[0148] A first relationship curve between the information difficulty characterization data and the first user ability characterization data and a second relationship curve between the information complexity characterization data and the second user ability characterization data.

[0149] According to one or more embodiments of the present disclosure, Example 3 provides an information push method, which, based on the information push method of Example 2, determines actual user capability characterization data corresponding to the first pushed information according to user feedback on the first pushed information, including:

[0150] Determine the second pushed information, wherein the second pushed information is the first pushed information that is fed back as correct;

[0151] According to the information difficulty characterization data corresponding to the second pushed information, the user ability characterization data is used to determine the model to determine the first user ability characterization data corresponding to the second pushed information;

[0152] According to the information complexity characterization data corresponding to the first pushed information, the user capability characterization data is used to determine the model, and the second user capability characterization data corresponding to the first pushed information is determined;

[0153] The actual user capability characterization data corresponding to the first pushed information is determined using the first user capability characterization data, the first preset weight corresponding to the first user capability characterization data, the second user capability characterization data, and the second preset weight corresponding to the second user capability characterization data.

[0154] According to one or more embodiments of the present disclosure, Example 4 provides an information push method, which, based on the information push method of Example 1 or Example 2, adjusts theoretical user capability characterization data according to actual user capability characterization data, including:

[0155] Determine a first absolute value of a difference between actual user capability characterization data and theoretical user capability characterization data;

[0156] According to a preset transfer function, the first absolute value is adjusted to obtain a second absolute value;

[0157] If the actual user capability characterization data is greater than the theoretical user capability characterization data, performing a subtraction operation on the second absolute value using the theoretical user capability characterization data;

[0158] If the actual user capability characterization data is smaller than the theoretical user capability characterization data, the theoretical user capability characterization data is used to perform an addition operation on the second absolute value.

[0159] According to one or more embodiments of the present disclosure, Example 5 provides an information push method, which, based on the information push method of Example 1 or Example 2, determines information to be pushed corresponding to the adjusted theoretical user capability representation data, including:

[0160] If the number of information to be pushed is one, determining the first information difficulty representation data corresponding to the adjusted theoretical user ability representation data by using the user ability representation data determination model according to the adjusted theoretical user ability representation data;

[0161] According to the first information difficulty characterization data, information to be pushed corresponding to the first information difficulty characterization data is determined.

[0162] According to one or more embodiments of the present disclosure, Example 6 provides an information push method, which, based on the information push method of Example 1 or Example 2, determines information to be pushed corresponding to the adjusted theoretical user capability representation data, and further includes:

[0163] If the number of information to be pushed is at least two, and the information difficulty representation data corresponding to each information to be pushed is different, determining the first user ability representation data corresponding to each information to be pushed according to the adjusted theoretical user ability representation data and the preset user ability representation data allocation ratio;

[0164] According to the first user capability characterization data corresponding to each piece of information to be pushed, a model is determined using the user capability characterization data to determine the second information difficulty characterization data corresponding to each adjusted theoretical user capability characterization data;

[0165] According to each second information difficulty representation data, the to-be-pushed information corresponding to each second information difficulty representation data is determined.

[0166] According to one or more embodiments of the present disclosure, Example 7 provides an information push method, which, based on the information push method of Example 1 or Example 2, further includes:

[0167] If it is determined that the number of pushed historical information is higher than the preset number, a first user capability characterization data determination model is determined based on the user's feedback on the historical information and the information difficulty characterization data corresponding to the historical information, and the first user capability characterization data determination model is used as the user capability characterization data determination model.

[0168] According to one or more embodiments of the present disclosure, Example 8 provides an information push device, including:

[0169] A theoretical user capability characterization data determination module, configured to determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user according to a user capability characterization data determination model corresponding to the user;

[0170] An actual user capability characterization data determination module, configured to determine actual user capability characterization data corresponding to the first pushed information according to user feedback on the first pushed information;

[0171] Theoretical user capability characterization data adjustment module, used for adjusting the theoretical user capability characterization data according to the actual user capability characterization data;

[0172] A module for determining and pushing information to be pushed, used to determine information to be pushed corresponding to the adjusted theoretical user capability representation data; and

[0173] Push the information to be pushed to the user.

[0174] According to one or more embodiments of the present disclosure, Example 9 provides a mobile terminal, including:

[0175] one or more processing devices;

[0176] A storage device for storing one or more programs;

[0177] When one or more programs are executed by one or more processing devices, the one or more processing devices implement any information push method as described in Examples 1 to 7.

[0178] According to one or more embodiments of the present disclosure, Example 10 provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an information push method as described in any one of Examples 1 to 7.

[0179] 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 disclosure involved in the present disclosure is not limited to the technical solutions 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 above disclosed 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 to form a technical solution.

[0180] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0181] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A method for pushing information, It is characterized in that include: Determine a model based on the user capability characterization data corresponding to the user, and determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user; Determining actual user capability representation data corresponding to the first pushed information according to the user's feedback on the first pushed information; Adjusting the theoretical user capability characterization data according to the actual user capability characterization data; Determining information to be pushed corresponding to the adjusted theoretical user capability representation data; as well as Pushing the information to be pushed to the user; The user capability characterization data determination model includes: A first relationship curve between information difficulty characterization data and first user ability characterization data, and a second relationship curve between information complexity characterization data and second user ability characterization data, wherein the information difficulty characterization data is a question accuracy rate, and the question accuracy rate is determined based on the historical processing result data of all users corresponding to each question; the first user ability characterization data is a first theoretical score corresponding to the user's question accuracy rate determined based on the user's historical processing result data; the information complexity characterization data is a processing time determined based on the historical processing result data of all users corresponding to the question; the second user ability characterization data is a second theoretical score corresponding to the user's question processing time determined based on the user's historical processing result data; The determining, according to the user's feedback on the first pushed information, actual user capability representation data corresponding to the first pushed information includes: Determine second pushed information, wherein the second pushed information is the first pushed information for which the feedback is correct; According to the information difficulty characterization data corresponding to the second pushed information, the user ability characterization data is used to determine the model to determine the first user ability characterization data corresponding to the second pushed information; According to the information complexity characterization data corresponding to the first pushed information, the user capability characterization data is used to determine the model to determine the second user capability characterization data corresponding to the first pushed information; The actual user capability characterization data corresponding to the first pushed information is determined by using the first user capability characterization data, the first preset weight corresponding to the first user capability characterization data, the second user capability characterization data, and the second preset weight corresponding to the second user capability characterization data.

2. The method according to claim 1, It is characterized in that The adjusting the theoretical user capability characterization data according to the actual user capability characterization data includes: Determining a first absolute value of a difference between the actual user capability characterization data and the theoretical user capability characterization data; According to a preset transfer function, adjusting the first absolute value to obtain a second absolute value; If the actual user capability characterization data is greater than the theoretical user capability characterization data, performing a subtraction operation on the second absolute value using the theoretical user capability characterization data; If the actual user capability characterization data is smaller than the theoretical user capability characterization data, the second absolute value is added using the theoretical user capability characterization data.

3. The method according to claim 1, It is characterized in that The determining of the information to be pushed corresponding to the adjusted theoretical user capability representation data includes: If the number of the information to be pushed is one, determining the first information difficulty representation data corresponding to the adjusted theoretical user ability representation data using the user ability representation data determination model according to the adjusted theoretical user ability representation data; According to the first information difficulty representation data, the to-be-pushed information corresponding to the first information difficulty representation data is determined.

4. The method according to claim 1, It is characterized in that The determining of the information to be pushed corresponding to the adjusted theoretical user capability representation data also includes: If the number of the information to be pushed is at least two, and the information difficulty representation data corresponding to each of the information to be pushed is different, then determining the first user ability representation data corresponding to each of the information to be pushed according to the adjusted distribution ratio of the theoretical user ability representation data and the preset user ability representation data; According to the first user capability characterization data corresponding to each piece of information to be pushed, using the user capability characterization data determination model, determine the second information difficulty characterization data corresponding to each piece of the adjusted theoretical user capability characterization data; According to each second information difficulty representation data, the to-be-pushed information corresponding to each second information difficulty representation data is determined.

5. The method according to claim 1, It is characterized in that Also includes: If it is determined that the number of historical information pushed is higher than the preset number, a first user ability characterization data determination model is determined based on the user's feedback on the historical information and the information difficulty characterization data corresponding to the historical information, and the first user ability characterization data determination model is used as the user ability characterization data determination model.

6. An information push device, It is characterized in that include: a theoretical user capability characterization data determination module, configured to determine theoretical user capability characterization data corresponding to the first pushed information that has been pushed to the user according to a user capability characterization data determination model corresponding to the user; an actual user capability characterization data determination module, configured to determine actual user capability characterization data corresponding to the first pushed information according to the user's feedback on the first pushed information; A theoretical user capability characterization data adjustment module, used to adjust the theoretical user capability characterization data according to the actual user capability characterization data; A module for determining and pushing information to be pushed, used for determining information to be pushed corresponding to the adjusted theoretical user capability representation data; as well as Pushing the information to be pushed to the user; The user capability characterization data determination model includes: A first relationship curve between information difficulty characterization data and first user ability characterization data, and a second relationship curve between information complexity characterization data and second user ability characterization data, wherein the information difficulty characterization data is a question accuracy rate, and the question accuracy rate is determined based on the historical processing result data of all users corresponding to each question; the first user ability characterization data is a first theoretical score corresponding to the user's question accuracy rate determined based on the user's historical processing result data; the information complexity characterization data is a processing time determined based on the historical processing result data of all users corresponding to the question; the second user ability characterization data is a second theoretical score corresponding to the user's question processing time determined based on the user's historical processing result data; The actual user capability characterization data determination module specifically includes: A second pushed information determining unit, configured to determine second pushed information, wherein the second pushed information is the first pushed information for which the feedback is correct; a first user capability characterization data determining unit, configured to determine the first user capability characterization data corresponding to the second pushed information by using the user capability characterization data determination model according to the information difficulty characterization data corresponding to the second pushed information; a second user capability characterization data determining unit, configured to determine the second user capability characterization data corresponding to the first pushed information by using the user capability characterization data determination model according to the information complexity characterization data corresponding to the first pushed information; The actual user capability characterization data determination unit is used to determine the actual user capability characterization data corresponding to the first pushed information by using the first user capability characterization data, the first preset weight corresponding to the first user capability characterization data, the second user capability characterization data and the second preset weight corresponding to the second user capability characterization data.

7. A mobile terminal, It is characterized in that The mobile terminal comprises: one or more processing devices; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the information push method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the information pushing method as described in any one of claims 1 to 5 is implemented.

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