Cross-device interaction method and device, device, storage medium and product

Abstract

The invention relates to a cross-device interaction method and device, equipment, a storage medium and a product, and the method comprises the steps: responding to the obtained use scene data of learning equipment in a current time period, and generating current card data based on the use scene data; determining an evaluation score of the current card data based on a preset evaluation strategy; selecting a preset number of target card data from the plurality of alternative card data based on the respective evaluation scores of the plurality of alternative card data; and recommending the target card data to parent equipment associated with the learning equipment, wherein the target card data is used for interaction between the parent equipment and the learning equipment. According to the method, the quality of the recommended target card data can be improved, and then the interaction effect between the subsequent parent equipment and learning equipment can be improved, so that the equipment use emotion of a learner can be improved, and the parent-child relationship between the learner and parents can be promoted.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a cross-device interaction method, apparatus, device, storage medium and product. Background Art

[0002] With the rapid development of science and technology and the increasing attention paid by parents to their children's education, learning machines and other equipment for children (hereinafter referred to as "learning equipment") are becoming increasingly popular.

[0003] There are many brands of learning devices on the market, and most of them provide children with functions such as course learning, homework correction, and explanation of wrong questions. However, in actual use, parents are unable to give their children enough attention and support due to various reasons (such as busy work, lack of professional knowledge, etc.), which can easily lead to a decrease in children's enthusiasm for using the device and even affect the parent-child relationship. Summary of the invention

[0004] In view of this, the present disclosure proposes a cross-device interaction method, apparatus, device, storage medium and product to solve the above-mentioned technical problems.

[0005] In order to achieve the above objectives, the technical solution adopted by the present disclosure is:

[0006] According to a first aspect of an embodiment of the present disclosure, a cross-device interaction method is proposed, which is applied to a server, and the method includes:

[0007] In response to acquiring usage scenario data of the learning device in a current time period, generating current card data based on the usage scenario data;

[0008] Determine the evaluation score of the current card data based on a preset evaluation strategy;

[0009] Based on the evaluation scores of the plurality of candidate card data, a preset number of target card data are selected from the plurality of candidate card data, wherein the plurality of candidate card data at least includes the current card data;

[0010] The target card data is recommended to a parent device associated with the learning device, and the target card data is used for the parent device to interact with the learning device.

[0011] In some embodiments, the usage scenario data includes at least one of the following:

[0012] Data on device usage, learning time, and learning content.

[0013] In some embodiments, the data of the device usage dimension includes, but is not limited to, the time interval between each activation of the learning device;

[0014] The data of the learning time dimension include but are not limited to at least one of the following: completion of the plan, the correctness of answering questions higher than a preset threshold, and the time for correcting wrong questions meeting the timely determination condition;

[0015] The data of the learning content dimension includes but is not limited to at least one of the following: course learning, practice, and test.

[0016] In some embodiments, generating current card data based on the usage scenario data includes:

[0017] Setting a recommendation influencing variable for the usage scenario data, wherein the recommendation influencing variable includes at least one of timeliness, number of courses, and number of days to complete;

[0018] Based on the recommendation influencing variable, classifying the usage scenario data into one of a plurality of preset recommendation priority categories;

[0019] Current card data is generated based on the usage scenario data and the preset recommendation priority category to which it belongs.

[0020] In some embodiments, determining the evaluation score of the current card data based on a preset evaluation strategy includes:

[0021] Determine a first partial score of the current card data based on a preset recommendation priority category corresponding to the current card data;

[0022] Determine a second part of the score of the current card data according to whether the current card data has timeliness that satisfies the condition;

[0023] An evaluation score of the current card data is determined based on the second partial score and the first partial score.

[0024] In some embodiments, the step of selecting a preset number of target card data from the plurality of candidate card data based on their respective evaluation scores includes:

[0025] Sorting the plurality of candidate card data in descending order of the evaluation scores;

[0026] According to the sorting result, top N card data are selected from the plurality of candidate card data as target card data, and the value of N is equal to the preset number.

[0027] In some embodiments, the plurality of candidate card data further include a number of historical card data generated in a historical time period before the current time period, the historical card data have not been recommended to the parent device, or have been recommended to the parent device but have not been interactively operated with the learning device;

[0028] The method further comprises:

[0029] Before generating current card data based on the usage scenario data, selecting a preset number of preliminary screening card data from the plurality of historical card data based on the evaluation scores of the plurality of historical card data;

[0030] The step of selecting a preset number of target card data from the plurality of candidate card data based on their respective evaluation scores comprises:

[0031] Based on the evaluation scores of the preliminary screening card data and the evaluation scores of the current card data, a preset number of target card data are selected from the preliminary screening card data and the current card data.

[0032] In some embodiments, when the preset number is greater than or equal to 2, recommending the target card data to a parent device associated with the learning device includes:

[0033] The preset number of target card data are recommended to the parent device once or multiple times according to the set time.

[0034] In some embodiments, the method further comprises:

[0035] In response to detecting an interactive operation triggered by the parent device based on the target card data, generating interactive card data, wherein the interactive card data includes an interactive reason and / or encouraging words;

[0036] Pushing the interactive card data to the learning device.

[0037] In some embodiments, the interaction reason is determined based on usage scenario data corresponding to the target card data;

[0038] The encouraging words are presented in the form of the parent's title, tone and / or intonation.

[0039] In some embodiments, the method further comprises:

[0040] generating interactive reward data in response to detecting that the learning device triggers an operation for receiving the interactive card data;

[0041] The interactive reward data is accumulated into reward data statistics of the learning device, and the reward data statistics are called based on a preset interface in the learning device.

[0042] According to a second aspect of an embodiment of the present disclosure, a cross-device interaction method is proposed, which is applied to a parent device. The method includes:

[0043] Receive target card data recommended by the server;

[0044] The target card data is recommended to the parent device by the server based on the method described in any one of the first aspects;

[0045] In response to detecting that a display condition of the target card data is met, the target card data is displayed, and the target card data is used for the parent device to interact with the learning device.

[0046] In some embodiments, the method further comprises:

[0047] In response to detecting an interactive operation triggered by displayed target card data, a first notification message is sent to the server, wherein the first notification message is used to trigger the server to generate interactive card data and push the interactive card data to the learning device, wherein the interactive card data includes reasons for interaction and / or encouraging words.

[0048] According to a third aspect of an embodiment of the present disclosure, a cross-device interaction method is proposed, which is applied to a learning device. The method includes:

[0049] Receiving interactive card data pushed by a server, wherein the interactive card data includes an interactive reason and / or encouraging words, and the interactive card data is generated by the server after detecting an interactive operation triggered by a parent device based on target card data, wherein the target card data is recommended to the parent device by the server based on any one of the methods described in the first aspect;

[0050] In response to detecting that a display condition of the interactive card data is met, the interactive card data is displayed.

[0051] In some embodiments, the method further comprises:

[0052] In response to detecting a receiving operation triggered by displayed interactive card data, a second notification message is sent to the server, and the second notification message is used to trigger the server to generate interactive reward data, and accumulate the interactive reward data into the reward data statistics of the learning device, and the reward data statistics are called based on a preset interface in the learning device.

[0053] According to a fourth aspect of an embodiment of the present disclosure, a cross-device interaction apparatus is proposed, which is applied to a server, and the apparatus includes:

[0054] A current card generation module, configured to generate current card data based on the usage scenario data of the learning device in a current time period in response to obtaining the usage scenario data;

[0055] An evaluation score determination module, used to determine the evaluation score of the current card data based on a preset evaluation strategy;

[0056] A target card selection module, configured to select a preset number of target card data from a plurality of candidate card data based on respective evaluation scores of the plurality of candidate card data, wherein the plurality of candidate card data at least includes the current card data;

[0057] The target card recommendation module is used to recommend the target card data to a parent device associated with the learning device, and the target card data is used for the parent device to interact with the learning device.

[0058] In some embodiments, the usage scenario data includes at least one of the following:

[0059] Data on device usage, learning time, and learning content.

[0060] In some embodiments, the data of the device usage dimension includes, but is not limited to, the time interval between each activation of the learning device;

[0061] The data of the learning time dimension include but are not limited to at least one of the following: completion of the plan, the correctness of answering questions higher than a preset threshold, and the time for correcting wrong questions meeting the timely determination condition;

[0062] The data of the learning content dimension includes but is not limited to at least one of the following: course learning, practice, and test.

[0063] In some embodiments, the current card generation module includes:

[0064] An influencing variable setting unit, configured to set a recommended influencing variable for the usage scenario data, wherein the recommended influencing variable includes at least one of timeliness, number of courses, and number of days to complete;

[0065] a data category classification unit, configured to classify the usage scenario data into one of a plurality of preset recommendation priority categories based on the recommendation influencing variables;

[0066] The current card generating unit is used to generate current card data based on the usage scenario data and the preset recommendation priority category to which it belongs.

[0067] In some embodiments, the evaluation score determination module includes:

[0068] A first score determination unit, configured to determine a first partial score of the current card data based on a preset recommendation priority category corresponding to the current card data;

[0069] A second score determination unit, configured to determine a second partial score of the current card data according to whether the current card data has timeliness that satisfies a condition;

[0070] An evaluation score determining unit is used to determine the evaluation score of the current card data based on the second partial score and the first partial score.

[0071] In some embodiments, the target card selection module includes:

[0072] A candidate card sorting unit, used to sort the plurality of candidate card data in descending order of the evaluation scores;

[0073] The target card selection unit is used to select top N card data from the multiple candidate card data as target card data according to the sorting result, and the value of N is equal to the preset number.

[0074] In some embodiments, the plurality of candidate card data further include a number of historical card data generated in a historical time period before the current time period, the historical card data have not been recommended to the parent device, or have been recommended to the parent device but have not been interactively operated with the learning device;

[0075] The device also includes:

[0076] A card data preliminary screening module, used for selecting a preset number of preliminary screening card data from the plurality of historical card data based on the evaluation scores of the plurality of historical card data before generating current card data based on the usage scenario data;

[0077] The target card selection module is also used to select a preset number of target card data from the preliminary screening card data and the current card data based on the evaluation score of the preliminary screening card data and the evaluation score of the current card data.

[0078] In some embodiments, when the preset number is greater than or equal to 2, the target card recommendation module is further used to recommend the preset number of target card data to the parent device once or multiple times according to a set time.

[0079] In some embodiments, the device further comprises an interactive card push module;

[0080] The interactive card push module includes:

[0081] An interactive card generating unit, configured to generate interactive card data in response to detecting an interactive operation triggered by the parent device based on the target card data, wherein the interactive card data includes an interactive reason and / or encouraging words;

[0082] An interactive card pushing unit is used to push the interactive card data to the learning device.

[0083] In some embodiments, the interaction reason is determined based on usage scenario data corresponding to the target card data;

[0084] The encouraging words are presented in the form of the parent's title, tone and / or intonation.

[0085] In some embodiments, the device further comprises an interactive reward accumulation module;

[0086] The interactive reward accumulation module includes:

[0087] an interactive reward generating unit, for generating interactive reward data in response to detecting that the learning device triggers an operation for receiving the interactive card data;

[0088] An interactive reward accumulation unit is used to accumulate the interactive reward data into the reward data statistical information of the learning device, and the reward data statistical information is called based on a preset interface in the learning device.

[0089] According to a fifth aspect of the embodiments of the present disclosure, a cross-device interaction apparatus is provided, which is applied to a parent device, and the apparatus includes:

[0090] The target card receiving module is used to receive the target card data recommended by the server;

[0091] Wherein, the target card data is recommended by the server to the parent device based on the device described in any one of the fourth aspects above;

[0092] The target card display module is used to display the target card data in response to detecting that the display condition of the target card data is met, and the target card data is used for the parent device to interact with the learning device.

[0093] In some embodiments, the apparatus further comprises:

[0094] The first notification sending module is used to send a first notification message to the server in response to detecting an interactive operation triggered by displayed target card data, wherein the first notification message is used to trigger the server to generate interactive card data and push the interactive card data to the learning device, wherein the interactive card data includes reasons for interaction and / or encouraging words.

[0095] According to a sixth aspect of an embodiment of the present disclosure, a cross-device interaction apparatus is provided, which is applied to a learning device, and the apparatus includes:

[0096] An interactive card receiving module, configured to receive interactive card data pushed by a server, wherein the interactive card data includes reasons for interaction and / or encouraging words, and the interactive card data is generated by the server after detecting an interactive operation triggered by a parent device based on target card data, wherein the target card data is recommended to the parent device by the server based on the apparatus described in any one of the fourth aspects above;

[0097] The interactive card display module is used to display the interactive card data in response to detecting that the display condition of the interactive card data is met.

[0098] In some embodiments, the apparatus further comprises:

[0099] A second notification sending module is used to send a second notification message to the server in response to detecting a receiving operation triggered by displayed interactive card data, wherein the second notification message is used to trigger the server to generate interactive reward data and accumulate the interactive reward data into the reward data statistical information of the learning device, and the reward data statistical information is called based on a preset interface in the learning device.

[0100] According to a seventh aspect of an embodiment of the present disclosure, an electronic device is provided, the electronic device comprising:

[0101] processor;

[0102] memory for storing computer programs;

[0103] Wherein, the processor is configured to implement any of the above-mentioned cross-device interaction methods when executing the computer program.

[0104] According to an eighth aspect of an embodiment of the present disclosure, a computer-readable storage medium is proposed, on which a computer program is stored, and when the program is processed by a processor, the cross-device interaction method described in any one of the above items is implemented.

[0105] According to a ninth aspect of an embodiment of the present disclosure, a computer program product is proposed, on which a computer program is stored, and when the program is processed by a processor, the cross-device interaction method described in any one of the above items is implemented.

[0106] Compared with the prior art, the present invention generates current card data based on the usage scenario data obtained during the current time period in response to the usage scenario data of the learning device, determines the evaluation score of the current card data based on a preset evaluation strategy, and then selects a preset number of target card data from the multiple candidate card data based on the evaluation scores of each of the multiple candidate card data, wherein the multiple candidate card data at least include the current card data, and then recommends the target card data to the parent device associated with the learning device. Since the evaluation score of the current card data is determined based on the preset evaluation strategy, and a preset number of target card data are selected from the multiple candidate card data based on the evaluation score, the quality of the recommended target card data can be improved, and the subsequent interaction effect between the parent device and the learning device can be improved, thereby improving the learner's mood for using the device, which is conducive to promoting the parent-child relationship between the learner and the parent. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] Figure 1 A flow chart of a cross-device interaction method according to an exemplary embodiment of the present disclosure is shown;

[0108] Figure 2 A flowchart showing how to generate current card data based on the usage scenario data according to an exemplary embodiment of the present disclosure is shown;

[0109] Figure 3 A schematic diagram showing how to select a preset number of target card data from the plurality of candidate card data according to an exemplary embodiment of the present disclosure;

[0110] Figure 4 A schematic diagram showing how to push interactive card data according to an exemplary embodiment of the present disclosure;

[0111] Figure 5 A flowchart of a cross-device interaction method according to another exemplary embodiment of the present disclosure is shown;

[0112] Figure 6 A flowchart of a cross-device interaction method according to another exemplary embodiment of the present disclosure is shown;

[0113] Fig. 7A A schematic diagram showing steps of a cross-device interaction method according to an exemplary embodiment of the present disclosure is shown;

[0114] Figure 7B A schematic diagram of a framework for cross-device multi-terminal push according to another exemplary embodiment of the present disclosure is shown;

[0115] Figure 8 A structural block diagram of a cross-device interaction apparatus according to an exemplary embodiment of the present disclosure is shown;

[0116] Fig. 9 A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown;

[0117] Fig.10 A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown;

[0118] Fig.11 A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown;

[0119] Fig.12 A structural block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0120] The present disclosure will be described in detail below in conjunction with the specific embodiments shown in the accompanying drawings. However, these embodiments do not limit the present disclosure, and any structural, methodological, or functional changes made by a person of ordinary skill in the art based on these embodiments are included in the protection scope of the present disclosure. In addition, the technical features involved in the different embodiments of the present disclosure described below can be combined with each other as long as they do not conflict with each other.

[0121] Figure 1 The flowchart of a cross-device interaction method according to an exemplary embodiment of the present disclosure is shown. The method of this embodiment can be executed by a cross-device interaction apparatus, and the cross-device interaction apparatus can be configured in an electronic device as a server, such as a server, a workstation, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.). Figure 1 As shown, the method includes the following steps S101-S104:

[0122] In step S101, in response to acquiring usage scenario data of the learning device in a current time period, current card data is generated based on the usage scenario data.

[0123] In this embodiment, the server may generate current card data based on the usage scenario data in response to obtaining the usage scenario data of the learning device in the current time period.

[0124] For example, the server may obtain usage scenario data of the learning device in the current time period (eg, a preset time period such as the day), and generate current card data based on the usage scenario data.

[0125] In some embodiments, the usage scenario data includes at least one of the following (a) to (c):

[0126] (a) Data on device usage, (b) data on learning time, and (c) data on learning content.

[0127] Exemplarily, the data of the above-mentioned device usage dimension may include, but is not limited to, the time interval between each activation of the learning device (e.g., information such as how long it takes for the user to activate the learning device).

[0128] The data of the learning time dimension may include, but is not limited to, at least one of the following: completion of the plan, correct answer rate higher than a preset threshold, and timely correction of wrong questions (e.g., the time for correcting wrong questions meets preset judgment conditions, etc.).

[0129] The data in the learning content dimension may include, but is not limited to, at least one of the following: course learning, exercises, and tests.

[0130] In some embodiments, after obtaining the usage scenario data of the learning device in the current time period, the server can generate the current card data based on the existing card data generation method in the related technology. This embodiment does not limit the specific method of generating the current card data.

[0131] In some other embodiments, the above method of generating current card data based on the usage scenario data can also refer to the following Figure 2 The illustrated embodiment will not be described in detail here.

[0132] In step S102, the evaluation score of the current card data is determined based on a preset evaluation strategy.

[0133] In this embodiment, after the current card data is generated based on the usage scenario data, the server may determine the evaluation score of the current card data based on a preset evaluation strategy.

[0134] For example, corresponding evaluation criteria can be formulated in advance based on various types of data features that may be contained in different card data, and then after the current card data is generated, the data features contained in the card data can be analyzed, and the evaluation score of the card data can be determined according to the above evaluation criteria.

[0135] It is worth noting that the above evaluation criteria can be freely set based on actual business needs, and this embodiment does not limit this.

[0136] It is understandable that the higher the evaluation score, the greater the probability that the corresponding card data will be recommended to the parent's device in the future.

[0137] In some other embodiments, the above method of determining the evaluation score of the current card data can also refer to the following Figure 2 The illustrated embodiment will not be described in detail here.

[0138] In step S103, based on the evaluation scores of the plurality of candidate card data, a preset number of target card data are selected from the plurality of candidate card data.

[0139] In this embodiment, after the evaluation score of the current card data is determined based on a preset evaluation strategy, a preset number of target card data may be selected from the multiple candidate card data based on their respective evaluation scores.

[0140] It is worth noting that the specific value of the above preset number can be set based on actual scenario requirements, such as being set to 1-3, etc., and this embodiment does not limit this.

[0141] The plurality of candidate card data at least include the current card data. For example, the plurality of candidate card data may only include the current card data, or may also include a number of historical card data generated in a historical time period before the current time period.

[0142] It is worth noting that, in order to improve the quality of the target card data determined subsequently and ensure the effect of cross-device interaction, the historical card data may refer to card data that has not been recommended to the parent device, or has been recommended to the parent device but has not been interactively operated with the learning device (e.g., historical card data that has not been "consumed" by the parent device). For example, the above-mentioned interactive operation is, for example, a "like" operation, etc., which is not limited in this embodiment.

[0143] In some embodiments, the above method of selecting a preset number of target card data from the plurality of candidate card data can also refer to the following Figure 3 The illustrated embodiment will not be described in detail here.

[0144] In step S104, the target card data is recommended to a parent device associated with the learning device.

[0145] In this embodiment, after a preset number of target card data are selected from a plurality of candidate card data based on their respective evaluation scores, the target card data may be recommended to a parent device associated with the learning device.

[0146] The target card data may be used for the parent device to interact with the learning device.

[0147] In some embodiments, when the number of determined target card data (ie, the above-mentioned preset number) is greater than or equal to 2, the server may recommend the preset number of target card data to the parent device once or multiple times according to a set time.

[0148] For example, the server can sort the determined multiple target card data according to the sorting rules, and then push new card data to the parent device at regular intervals (such as 9:30 PM every day).

[0149] In this way, parents can trigger the interactive operation button in the target card data in the parent device (for example, click the "Like" button provided in the card data, etc.), and give reasons and encouragement for likes from the learner's perspective through the relevant functional modules in the parent device (such as the "Express Love Module", etc.), and trigger the server to generate interactive card data (such as like cards, etc.) to be checked by the learning device.

[0150] Then, learners can receive interactive card data from different family members on the learning device, and can click to check and receive the corresponding interactive rewards; or, they can temporarily not receive the interactive rewards, and then enter and check from the preset interface when they want to receive them later.

[0151] For example, the form of the above reward data can be set based on actual scenario requirements, such as tokens and / or medals, etc., which are not limited in this embodiment. For example, the above tokens can be consumed in the mall or the future treasure box; and the medals are achievements given to learners, which can make learners intuitively feel the love and encouragement of different family members.

[0152] It can be seen from the above description that the method of this embodiment generates current card data based on the usage scenario data in response to obtaining the usage scenario data of the learning device in the current time period, and determines the evaluation score of the current card data based on a preset evaluation strategy, and then selects a preset number of target card data from the multiple candidate card data based on the evaluation scores of each of the multiple candidate card data, and the multiple candidate card data at least include the current card data, and then recommends the target card data to the parent device associated with the learning device. Since the evaluation score of the current card data is determined based on the preset evaluation strategy, and a preset number of target card data are selected from the multiple candidate card data based on the evaluation score, the quality of the recommended target card data can be improved, and then the subsequent interaction effect between the parent device and the learning device can be improved, thereby improving the learner's device usage mood, which is conducive to promoting the parent-child relationship between the learner and the parent.

[0153] Figure 2 A flowchart of how to generate current card data based on the usage scenario data according to an exemplary embodiment of the present disclosure is shown; based on the above embodiment, this embodiment uses an example of how to generate current card data based on the usage scenario data as an example to exemplify.

[0154] like Figure 2As shown, the generation of current card data based on the usage scenario data in the above step S101 may include the following steps S201-S203:

[0155] In step S201, a recommendation influencing variable is set for the usage scenario data.

[0156] In this embodiment, when the current card data is generated based on the usage scenario data, a recommendation influencing variable may be set for the usage scenario data first.

[0157] The recommendation influencing variables include at least one of timeliness, number of courses and number of days to completion.

[0158] In step S202, based on the recommendation influencing variable, the usage scenario data is classified into one of a plurality of preset recommendation priority categories.

[0159] In this embodiment, after setting the recommendation influence variable for the usage scenario data, the usage scenario data may be classified into one of a plurality of preset recommendation priority categories based on the recommendation influence variable.

[0160] It is worth noting that the above-mentioned multiple preset recommendation priority categories can be set according to scenario requirements.

[0161] Exemplarily, the above-mentioned multiple preset recommendation priority categories may include an “unconditional love” category, a “willing to learn” category, a “learn well” category, and a “continue to learn” category.

[0162] It is understandable that the recommendation priorities of the four categories are arranged in order from low to high:

[0163] “Unconditional love” category < “willing to learn” category < “learn well” category < “continue to learn” category.

[0164] Different recommendation priority categories correspond to different recommendation weights (scores), which will not be described in detail here.

[0165] In step S203, current card data is generated based on the usage scenario data and the preset recommendation priority category to which it belongs.

[0166] In this embodiment, after the usage scenario data is classified into one of a plurality of preset recommendation priority categories based on the recommendation influencing variables, the current card data may be generated based on the usage scenario data and the preset recommendation priority category to which it belongs.

[0167] That is to say, after the usage scenario data is divided into one of multiple preset recommendation priority categories, the usage scenario data can be stored as card data in the preset recommendation priority category to which it belongs (stored in the corresponding category in the form of card material), that is, the current card data.

[0168] From the above description, it can be seen that this embodiment sets recommendation influence variables for the usage scenario data, and based on the recommendation influence variables, divides the usage scenario data into one of a plurality of preset recommendation priority categories, and then generates current card data based on the usage scenario data and the preset recommendation priority category to which it belongs. This can achieve accurate and efficient generation of current card data based on the usage scenario data, and thus lay a foundation for the subsequent determination of target card data and recommendation of the target card data to the parent device associated with the learning device, and thus improve the quality of the recommended target card data, and thus improve the subsequent interaction effect between the parent device and the learning device, thereby improving the learner's mood for device usage, and is conducive to promoting the parent-child relationship between the learner and the parent.

[0169] Based on the above embodiment, the step S102 of determining the evaluation score of the current card data based on a preset evaluation strategy may include the following (1) to (3):

[0170] (1) Determine a first partial score of the current card data (for example, recorded as “score1”) based on a preset recommendation priority category corresponding to the current card data.

[0171] It is understandable that the preset priority categories corresponding to the card data are different, and the corresponding first part scores are also different. For example, the scores 1 corresponding to different categories can be shown in the following table 1:

[0172] Table 1

[0173] category Continuing Learning Learn well Willing to learn Unconditional Love score1 4 3 2 1

[0174] (2) Determine a second partial score of the current card data (for example, recorded as "score2") according to whether the current card data has timeliness that satisfies a condition.

[0175] It is understandable that not every card data has time validity, and further, not every card data with time validity meets the time validity condition. In other words, assuming that the time validity condition of card data is "time validity is today", the time validity of card data that has no time validity, or has time validity but the time validity is not today, does not meet the condition.

[0176] Exemplarily, the score2 of the card data whose timeliness meets the condition is 1; the score2 of the card data whose timeliness meets the condition is 0.

[0177] (3) Determine the evaluation score of the current card data based on the second partial score and the first partial score (for example, recorded as “Score_final”).

[0178] After obtaining the score1 and score2 of the current card data, the evaluation score of the current card data (for example, recorded as "Score_final") can be determined according to these two scores.

[0179] For example, a comprehensive score can be determined by adding the weights of score1 and score2. For example, the weight corresponding to score1 can be k1, and the weight corresponding to score2 can be k2, and k1 is much smaller than k2. For example, k2 = 10k1. In this way, it can be ensured that the card data that meets the timeliness conditions can be given priority in subsequent recommendations.

[0180] For another example, score1 and score2 can be directly combined into an evaluation score, that is, the evaluation score Score_final of the current card data is [score1, score2]. In this way, in subsequent screening, the card data with score2=1 can be given priority, and then the score value of score1 can be considered.

[0181] Figure 3 A schematic diagram is shown of how to select a preset number of target card data from the multiple candidate card data according to an exemplary embodiment of the present disclosure; this embodiment, based on the above embodiment, uses an example of how to select a preset number of target card data from the multiple candidate card data to exemplify.

[0182] like Figure 3 As shown, the step S103 described above, based on the evaluation scores of the plurality of candidate card data, selecting a preset number of target card data from the plurality of candidate card data may include the following steps S301-S302:

[0183] In step S301, the plurality of candidate card data are sorted in descending order of the evaluation scores.

[0184] In this embodiment, after obtaining the evaluation scores of the plurality of candidate card data, the plurality of candidate card data may be sorted in descending order of the evaluation scores to obtain a sorting result.

[0185] In step S302, according to the sorting result, top N card data are selected from the plurality of candidate card data as target card data.

[0186] In this embodiment, after the sorting results of multiple candidate card data are obtained, the top N card data can be selected from the multiple candidate card data as the target card data according to the sorting results. The value of N is equal to the preset number. That is, if the preset number is 3, the top 3 current card data are selected from the multiple candidate card data as the target card data.

[0187] By sorting the multiple candidate card data in descending order according to the evaluation scores, and selecting top N card data from the multiple candidate card data as target card data based on the sorting results, it is possible to reasonably and accurately select a preset number of target card data from the multiple candidate card data, and then subsequently recommend the target card data to the parent device associated with the learning device, which can improve the quality of the recommended target card data and improve the interaction effect between the parent device and the learning device, thereby improving the learner's device usage mood and promoting the parent-child relationship between the learner and the parent.

[0188] In some embodiments, the plurality of candidate card data may further include a number of historical card data generated in a historical time period before the current time period, wherein the historical card data has not been recommended to the parent device, or has been recommended to the parent device but has not been interactively operated with the learning device.

[0189] Furthermore, before generating the current card data based on the usage scenario data, the server may also select a preset number of preliminary screening card data from the plurality of historical card data based on the evaluation scores of the plurality of historical card data. Then, after generating the current card data and determining the evaluation score of the current card data, a preset number of target card data may be selected from the preliminary screening card data and the current card data based on the evaluation score of the preliminary screening card data and the evaluation score of the current card data.

[0190] In other words, the present embodiment can first screen the historical card data in the preparation stage (for example, before the day) to obtain preliminary card data; after obtaining the new card data of the day, the score of the preliminary card data is compared with the score of the new card data of the day to determine the target card data. This can reduce the calculation time, improve the calculation efficiency, and thus improve the effect of subsequent data recommendation.

[0191] Figure 4A schematic diagram of how to push interactive card data according to an exemplary embodiment of the present disclosure is shown; based on the above embodiment, this embodiment uses how to push interactive card data as an example to exemplify the above embodiment.

[0192] like Figure 4 As shown, based on the above embodiments, the cross-device interaction method of this embodiment may further include pushing the interaction card data based on the following steps S401-S402:

[0193] In step S401, in response to detecting an interactive operation triggered by the parent device based on the target card data, interactive card data is generated.

[0194] In this embodiment, after the server recommends the target card data to the parent device associated with the learning device, if an interactive operation triggered by the parent device based on the target card data is detected, interactive card data may be generated.

[0195] The interactive card data may include reasons for interaction and / or encouraging words.

[0196] It can be understood that the interaction reason may include summary information of the learner's learning or device usage behavior, so the above interaction reason may be determined based on the usage scenario data corresponding to the target card data;

[0197] Words of encouragement may include the emotions expressed by parents through parent devices regarding the learner's learning or device usage. Therefore, words of encouragement may be presented in the parent's title, tone and / or voice to better simulate the scenario of parents encouraging their children and enhance the immersion of parent-child interaction.

[0198] In step S402, the interactive card data is pushed to the learning device

[0199] In this embodiment, when the server generates interactive card data in response to detecting an interactive operation triggered by the parent device based on the target card data, the interactive card data can be pushed to the learning device.

[0200] On this basis, the server may also generate interactive reward data in response to detecting that the learning device triggers an operation for receiving the interactive card data, and accumulate the interactive reward data into the reward data statistics of the learning device.

[0201] The reward data statistical information is called based on a preset interface in the learning device.

[0202] It is understandable that the learner can also trigger an operation on the learning device to indicate that the above interactive card data is not received temporarily, and then access and receive it from the relevant query interface in the learning device at a convenient time later.

[0203] In general, by analyzing the use of learning devices, learning time, and learning content, Same Dimension The data can be collected to achieve Find reasons to interact and encourage learners in their daily behaviors on learning devices.

[0204] Then, by calculating, classifying and sorting the data of the above-mentioned different dimensions, the learners' daily behaviors can be stored in the form of card data, and then the target card data (data that can be used to characterize the learners' relative worthiness of parents' interactive behaviors) can be calculated through preset evaluation strategies (such as weight calculation and sorting rules). From the perspective of positive psychology, specific and sincere praise can be achieved, thereby enhancing the learners' positive emotions, helping them to better recognize their own strengths and thus enhance their self-confidence.

[0205] Furthermore, by pushing target card data to parent devices to inform parents of content that is worthy of interaction with learners, and then responding to interactive operations triggered by the parent device based on the target card data, generating interactive card data containing reasons for interaction and / or encouraging words, and pushing the interactive card data to the learning device, the love and encouragement from parents can be better expressed to the children, thereby strengthening the children's positive emotions and improving the parent-child relationship.

[0206] Figure 5 A flow chart of a cross-device interaction method according to another exemplary embodiment of the present disclosure is shown; the method of this embodiment can be executed by a cross-device interaction apparatus, and the cross-device interaction apparatus can be configured in an electronic device serving as a parent device, such as a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), etc.

[0207] like Figure 5 As shown, the method includes the following steps S501-S502:

[0208] In step S501, target card data recommended by the server is received.

[0209] The target card data can be obtained by the server based on the above Figures 1 to 4 The method of the illustrated embodiment is recommended to the parent device.

[0210] In step S502, in response to detecting that the display condition of the target card data is met, the target card data is displayed.

[0211] The target card data may be used for the parent device to interact with the learning device.

[0212] On this basis, the above method may further include: in response to detecting an interactive operation triggered based on the displayed target card data, sending a first notification message to the server.

[0213] The first notification information may be used to trigger the server to generate interactive card data and push the interactive card data to the learning device.

[0214] Exemplarily, the interactive card data may include reasons for interaction and / or encouraging words. For example, the reasons for interaction may be determined based on the usage scenario data corresponding to the target card data. The encouraging words may be presented in the form of a parent's title, tone and / or voice.

[0215] From the above description, it can be seen that the method of this embodiment receives the target card data recommended by the server, and in response to detecting that the display conditions of the target card data are met, displays the target card data. Based on the target card data, the parent device can be provided with a tool for interacting with the learning device, and a good interaction effect between the parent device and the learning device can be achieved, thereby enhancing the learner's mood for using the device and promoting the parent-child relationship between the learner and the parents.

[0216] Figure 6 A flowchart of a cross-device interaction method according to another exemplary embodiment of the present disclosure is shown; the method of this embodiment can be executed by a cross-device interaction apparatus, which can be configured in an electronic device as a learning device, such as a learning machine, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.). Figure 6 As shown, the method includes the following steps S601-S602:

[0217] In step S601, the interactive card data pushed by the server is received.

[0218] The interactive card data may include reasons for interaction and / or encouraging words.

[0219] The interactive card data is generated by the server after detecting an interactive operation triggered by the parent device based on the target card data, wherein the target card data is generated by the server based on the above Figures 1 to 4 The method of the illustrated embodiment is recommended to the parent device.

[0220] In step S601, in response to detecting that a display condition of the interactive card data is met, the interactive card data is displayed.

[0221] On this basis, the above method may further include: in response to detecting a receiving operation triggered by the displayed interactive card data, sending a second notification message to the server.

[0222] Among them, the above-mentioned second notification information can be used to trigger the server to generate interactive reward data, and accumulate the interactive reward data into the reward data statistical information of the learning device.

[0223] In some embodiments, the above-mentioned reward data statistics can be called based on a preset interface in the learning device. For example, learners can view the above-mentioned reward data statistics from a preset "view reward" interface in the learning device, thereby increasing the sense of accomplishment and enthusiasm of learners and parents in interacting, which is conducive to improving the enthusiasm for using the device and improving the parent-child relationship.

[0224] From the above description, it can be seen that the method of this embodiment receives interactive card data pushed by the server, wherein the interactive card data contains reasons for interaction and / or encouraging words, and in response to detecting that the display conditions of the interactive card data are met, displays the interactive card data, thereby achieving a good interactive effect between the parent device and the learning device, thereby enhancing the learner's mood for using the device and promoting the parent-child relationship between the learner and the parent.

[0225] The following is a specific embodiment to introduce the steps of the cross-device interaction method of the present disclosure and the framework for implementing cross-device multi-terminal push in the server, but it is not intended to limit the scope of the present disclosure.

[0226] Fig. 7A FIG. 4 shows a schematic diagram of steps of a cross-device interaction method according to an exemplary embodiment of the present disclosure; Fig. 7A As shown, the method includes the following steps 1-5:

[0227] In step 1: the server collects usage scenario data of the learning device in the current time period, including scenario data 1, scenario data 2, scenario data 3, and so on.

[0228] Among them, the above usage scenario data is collected according to three dimensions: learning time, learning content, and equipment usage.

[0229] For example, the above-mentioned detailed learning data and behavior data obtained may include: (1) device usage dimension: how long it has been since the learner turned on the device (learning device), etc.; (2) learning content dimension: course learning, practice and testing; (3) learning time dimension: completion of the plan, high accuracy of answering questions, timely correction of wrong questions, etc.

[0230] In step 2: by calculation, the detailed learning data and behavior data obtained above are converted into card data of different weights and / or different types, which may specifically include the following sub-steps (2-1) to (2-3):

[0231] (2-1) Set influencing variables for each collected usage scenario data, including timeliness, number of courses, completion days, etc.;

[0232] (2-2) Divide the data into different categories, such as "unconditional love", "willing to learn", "learn well", and "continue to learn". Then, based on each piece of data, data in the form of card (post) materials is generated and stored;

[0233] (2-3) Screening of target card data;

[0234] Taking the current time period as "every day" as an example, when new card data is produced every day, the server can select target card data from historical time periods (such as the past 13 days, etc.) and new card data produced on that day based on different strategies for subsequent recommendation to the parent device.

[0235] Furthermore, in order to improve the efficiency of card data screening, the top 3 card data can be preliminarily selected from the historical card data as initial material before new card data is produced every day (for example, at 01:30 every day when the pressure on the server is relatively low); after the new card data is produced every day, it is compared with the initial material to obtain the final top 3 card data, that is, the target card data.

[0236] The exemplary strategy for selecting the top 3 card data is as follows:

[0237] Each card data may have two evaluation scores, namely score1 and score2: first, score1 is set according to the data category (i.e., the aforementioned four categories of unconditional love, willingness to learn, good learning, and continuous learning). For example, score1 = 4 for continuous learning, score1 = 3 for good learning, score1 = 2 for willingness to learn, and score1 = 1 for unconditional love.

[0238] Then, score2 is set according to the timeliness of the data. For example, if the timeliness is today, score2=1, and if the timeliness is not today, score2=0.

[0239] Card priority sorting: first search for card data with score2=1. If card data with score2=1 is found, read the score1 of the card data. For card data with the same score1 value, if they belong to the same category, they can be deduplicated according to different learning scenarios (such as learning content) to select the latest time, and then select the top3 card data from score1 in descending order; if the top3 card data cannot be obtained, it means that there is no timeliness for today; then take the card data with score2=0 to read the score1 value, and also need to deduplicate according to the sub-scenario, take the latest time, and select the card data in descending order until the top3 card data can be selected as the target card data.

[0240] In step 3: push target card data;

[0241] After the server obtains the target card data, it can recommend the preset number of target card data to the parent device once or multiple times according to the set time, such as pushing 1-3 data at regular intervals every day, and pushing the latest target card data to the parent device at 9:30 every day.

[0242] After the server pushes the target card data to the parent's device, the parent can display the target card data to be liked; then when the parent likes the card data (such as clicking on the like button set on the card data), the card data will be changed to the liked state.

[0243] In step 4: interactive card data output;

[0244] When the target card data on the parent side is changed to the "liked" state, the "love expression" module on the parent device side can give the learner's perspective on the reason for the like and words of encouragement, and then the server side can generate an interactive card for the learning device side to check and push it to the learning device side. Among them, interactive cards include but are not limited to cards in the form of "like" cards.

[0245] On this basis, the learner can receive the interactive card data of the family members corresponding to the parent device on the learning device, and then choose to receive the reward immediately or not. If the learner chooses not to receive the reward at present, he can also check the reward from the relevant query entrance later.

[0246] In step 5: reward data issuance;

[0247] The forms of the above interactive rewards may include but are not limited to tokens and medals. Tokens can be consumed in the mall or the future treasure box; while medals are given to learners for their achievements, allowing learners to more intuitively feel the love and encouragement of family members.

[0248] It is understandable that by setting up an interactive reward mechanism, learners' enthusiasm for interaction can be further promoted, which is conducive to improving parent-child relationships.

[0249] Based on the above embodiments, Figure 7B FIG. 2 shows a schematic diagram of a framework for cross-device multi-terminal push according to another exemplary embodiment of the present disclosure. Figure 7B As shown, the framework of this embodiment mainly involves post material sources, social service-interaction module, upstream business application program interface API, and users on the parent side or learning device side. Various types of data in the post material source can be transmitted to the production module to generate card data when the conditions are met, and then enter the interactive function adapted and developed in the social service-interaction module, and finally can be consumed by users on the parent side or learning device side based on the upstream business API. It is worth noting that this framework is only used for exemplary description, and can be adjusted based on the needs of the scene in actual application, and this embodiment does not limit this.

[0250] Figure 8 The structure block diagram of a cross-device interaction apparatus according to an exemplary embodiment of the present disclosure is shown. The apparatus of this embodiment can be configured in an electronic device as a server, such as a server, a workstation, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), etc.

[0251] like Figure 8 As shown, the device includes: a current card generation module 110, an evaluation score determination module 120, a target card selection module 130 and a target card recommendation module 140, wherein:

[0252] A current card generation module 110, configured to generate current card data based on the usage scenario data of the learning device in the current time period in response to obtaining the usage scenario data;

[0253] An evaluation score determination module 120, configured to determine the evaluation score of the current card data based on a preset evaluation strategy;

[0254] A target card selection module 130, configured to select a preset number of target card data from a plurality of candidate card data based on respective evaluation scores of the plurality of candidate card data, wherein the plurality of candidate card data at least includes the current card data;

[0255] The target card recommendation module 140 is used to recommend the target card data to a parent device associated with the learning device, and the target card data is used for the parent device to interact with the learning device.

[0256] It can be seen from the above description that the device of this embodiment generates current card data based on the usage scenario data in response to obtaining the usage scenario data of the learning device in the current time period, and determines the evaluation score of the current card data based on a preset evaluation strategy, and then selects a preset number of target card data from the multiple candidate card data based on the evaluation scores of each of the multiple candidate card data, and the multiple candidate card data at least include the current card data, and then recommends the target card data to the parent device associated with the learning device. Since the evaluation score of the current card data is determined based on the preset evaluation strategy, and a preset number of target card data are selected from the multiple candidate card data based on the evaluation score, the quality of the recommended target card data can be improved, and then the subsequent interaction effect between the parent device and the learning device can be improved, thereby improving the learner's device usage mood, which is conducive to promoting the parent-child relationship between the learner and the parent.

[0257] Fig. 9 A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown. The apparatus of this embodiment can be configured in an electronic device as a server, such as a server, a workstation, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), etc.

[0258] Among them, the current card generation module 210, the evaluation score determination module 220, the target card selection module 230 and the target card recommendation module 240 are the same as the aforementioned Figure 8 The functions of the current card generation module 110, the evaluation score determination module 120, the target card selection module 130 and the target card recommendation module 140 in the illustrated embodiment are the same and will not be described in detail herein.

[0259] In this embodiment, the above-mentioned usage scenario data may include at least one of the following:

[0260] Data on device usage, learning time, and learning content.

[0261] Exemplarily, the data of the device usage dimension may include but is not limited to the time interval for each time the learning device is turned on;

[0262] The data of the learning time dimension include but are not limited to at least one of the following: completion of the plan, the correctness of answering questions higher than a preset threshold, and the time for correcting wrong questions meeting the timely determination condition;

[0263] The data of the learning content dimension includes but is not limited to at least one of the following: course learning, practice, and test.

[0264] like Fig. 9 As shown, the current card generation module 210 may include:

[0265] An influencing variable setting unit 211, configured to set a recommended influencing variable for the usage scenario data, wherein the recommended influencing variable includes at least one of timeliness, number of courses, and number of days to complete;

[0266] A data category classification unit 212, configured to classify the usage scenario data into one of a plurality of preset recommendation priority categories based on the recommendation influencing variables;

[0267] The current card generating unit 213 is used to generate current card data based on the usage scenario data and the preset recommendation priority category to which it belongs.

[0268] In some embodiments, the evaluation score determination module 220 may include:

[0269] A first score determination unit 221, configured to determine a first partial score of the current card data based on a preset recommendation priority category corresponding to the current card data;

[0270] A second score determination unit 222, configured to determine a second partial score of the current card data according to whether the current card data has timeliness that satisfies a condition;

[0271] The evaluation score determining unit 223 is used to determine the evaluation score of the current card data based on the second partial score and the first partial score.

[0272] In some embodiments, the target card selection module 230 may include:

[0273] A candidate card sorting unit 231 is used to sort the plurality of candidate card data in descending order of the evaluation scores;

[0274] The target card selection unit 232 is used to select topN card data from the multiple candidate card data as target card data according to the sorting result, and the value of N is equal to the preset number.

[0275] In some embodiments, the plurality of candidate card data may further include a number of historical card data generated in a historical time period before the current time period, wherein the historical card data has not been recommended to the parent device, or has been recommended to the parent device but has not been used for interactive operation with the learning device;

[0276] On this basis, the above device may further include:

[0277] A card data preliminary screening module 250, configured to select a preset number of preliminary screening card data from the plurality of historical card data based on the evaluation scores of the plurality of historical card data before generating the current card data based on the usage scenario data;

[0278] Furthermore, the target card selection module 230 can also be used to select a preset number of target card data from the preliminary screening card data and the current card data based on the evaluation score of the preliminary screening card data and the evaluation score of the current card data.

[0279] In some embodiments, when the preset number is greater than or equal to 2, the target card recommendation module 240 can also be used to recommend the preset number of target card data to the parent device once or multiple times according to a set time.

[0280] In some embodiments, the above device may further include an interactive card push module 260;

[0281] The interactive card push module 260 may include:

[0282] An interactive card generating unit 261, configured to generate interactive card data in response to detecting an interactive operation triggered by the parent device based on the target card data, wherein the interactive card data includes an interactive reason and / or encouraging words;

[0283] The interactive card pushing unit 262 is used to push the interactive card data to the learning device.

[0284] In some embodiments, the above-mentioned interaction reason can be determined based on the usage scenario data corresponding to the target card data;

[0285] The above words of encouragement may be presented in the form of the parent's title, tone and / or manner.

[0286] In some embodiments, the above apparatus may further include an interactive reward accumulation module 270;

[0287] The interactive reward accumulation module 270 may include:

[0288] An interactive reward generating unit 271, for generating interactive reward data in response to detecting that the learning device triggers an operation for receiving the interactive card data;

[0289] The interactive reward accumulation unit 272 is used to accumulate the interactive reward data into the reward data statistical information of the learning device, and the reward data statistical information is called based on a preset interface in the learning device.

[0290] Fig.10A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown. The apparatus of this embodiment can be configured in an electronic device as a parent device, such as a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), etc.

[0291] like Fig.10 As shown, the device includes: a target card receiving module 310 and a target card display module 320, wherein:

[0292] The target card receiving module 310 is used to receive the target card data recommended by the server;

[0293] The target card data is obtained by the server based on Figure 8 or Fig. 9 The apparatus shown in the illustrated embodiment is recommended to the parent device;

[0294] The target card display module 320 is used to display the target card data in response to detecting that the display condition of the target card data is met, and the target card data is used for the parent device to interact with the learning device.

[0295] In some embodiments, the above apparatus may further include:

[0296] The first notification sending module 330 is used to send a first notification message to the server in response to detecting an interactive operation triggered by displayed target card data. The first notification message is used to trigger the server to generate interactive card data and push the interactive card data to the learning device. The interactive card data may include reasons for interaction and / or encouraging words.

[0297] From the above description, it can be seen that the device of this embodiment receives the target card data recommended by the server, and in response to detecting that the display conditions of the target card data are met, displays the target card data. Based on the target card data, the parent device can be provided with a tool for interacting with the learning device, and a good interaction effect between the parent device and the learning device can be achieved, thereby enhancing the learner's mood for using the device and promoting the parent-child relationship between the learner and the parents.

[0298] Fig.11 A structural block diagram of a cross-device interaction apparatus according to another exemplary embodiment of the present disclosure is shown. The apparatus of this embodiment can be configured in an electronic device as a learning device, such as a learning machine, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), etc.

[0299] like Fig.11 As shown, the device includes: an interactive card receiving module 410 and an interactive card display module 420, wherein:

[0300] The interactive card receiving module 410 is used to receive the interactive card data pushed by the server, wherein the interactive card data includes the interactive reason and / or encouragement words, and the interactive card data is generated by the server after detecting the interactive operation triggered by the parent device based on the target card data, wherein the target card data is generated by the server based on Figure 8 or Fig. 9 The apparatus described in the illustrated embodiment is recommended to the parent device;

[0301] The interactive card display module 420 is used to display the interactive card data in response to detecting that the display condition of the interactive card data is met.

[0302] On this basis, the above device may further include:

[0303] The second notification sending module 430 is used to send a second notification message to the server in response to detecting a receiving operation triggered by displayed interactive card data, and the second notification message is used to trigger the server to generate interactive reward data and accumulate the interactive reward data into the reward data statistics of the learning device, and the reward data statistics are called based on a preset interface in the learning device.

[0304] From the above description, it can be seen that the device of this embodiment receives interactive card data pushed by the server, wherein the interactive card data contains reasons for interaction and / or encouraging words, and in response to detecting that the display conditions of the interactive card data are met, displays the interactive card data, thereby achieving a good interactive effect between the parent device and the learning device, thereby enhancing the learner's mood for using the device and promoting the parent-child relationship between the learner and the parent.

[0305] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial description of the method embodiments. The device embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0306] Fig.121 is a schematic diagram of a structure of an electronic device according to an exemplary embodiment of the present disclosure. The electronic device may be, for example, a mobile phone, a computer, a digital broadcast terminal, a message transceiver device, a game console, a tablet device, a personal digital assistant, a server, a smart home appliance, etc. Fig.12 At the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and of course may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming an inspection device for the grayscale environment at the logical level. Of course, in addition to the software implementation, the present disclosure does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0307] The embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored, and when the program is processed by a processor, the above-mentioned cross-device interaction method is implemented.

[0308] The computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc., and the present disclosure is not limited thereto.

[0309] The embodiments of the present disclosure also provide a computer program product on which a computer program is stored, and when the program is processed by a processor, the above-mentioned cross-device interaction method is implemented.

[0310] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims of the present disclosure.

[0311] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A cross-device interaction method, characterized in that: Applied to the server, the method includes: In response to acquiring usage scenario data of the learning device in a current time period, generating current card data based on the usage scenario data; Determine the evaluation score of the current card data based on a preset evaluation strategy; Based on the evaluation scores of the plurality of candidate card data, a preset number of target card data are selected from the plurality of candidate card data, wherein the plurality of candidate card data at least includes the current card data; The target card data is recommended to a parent device associated with the learning device, and the target card data is used for the parent device to interact with the learning device.

2. The method according to claim 1, characterized in that The usage scenario data includes at least one of the following: Data on device usage, learning time, and learning content.

3. The method according to claim 2, characterized in that The data of the device usage dimension includes but is not limited to the time interval between each activation of the learning device; The data of the learning time dimension include but are not limited to at least one of the following: completion of the plan, the correctness of answering questions higher than a preset threshold, and the time for correcting wrong questions meeting the timely determination condition; The data of the learning content dimension includes but is not limited to at least one of the following: course learning, practice, and test.

4. The method according to claim 1, characterized in that: The generating current card data based on the usage scenario data includes: Setting a recommendation influencing variable for the usage scenario data, wherein the recommendation influencing variable includes at least one of timeliness, number of courses, and number of days to complete; Based on the recommendation influencing variable, classifying the usage scenario data into one of a plurality of preset recommendation priority categories; Current card data is generated based on the usage scenario data and the preset recommendation priority category to which it belongs.

5. The method according to claim 4, characterized in that The determining the evaluation score of the current card data based on a preset evaluation strategy includes: Determine a first partial score of the current card data based on a preset recommendation priority category corresponding to the current card data; Determine a second part of the score of the current card data according to whether the current card data has timeliness that satisfies the condition; An evaluation score of the current card data is determined based on the second partial score and the first partial score.

6. The method according to claim 1, characterized in that The step of selecting a preset number of target card data from the plurality of candidate card data based on their respective evaluation scores comprises: Sorting the plurality of candidate card data in descending order of the evaluation scores; According to the sorting result, top N card data are selected from the plurality of candidate card data as target card data, and the value of N is equal to the preset number.

7. The method according to claim 6, characterized in that The plurality of candidate card data further include a number of historical card data generated in a historical time period before the current time period, the historical card data have not been recommended to the parent device, or have been recommended to the parent device but have not been interactively operated with the learning device; The method further comprises: Before generating current card data based on the usage scenario data, selecting a preset number of preliminary screening card data from the plurality of historical card data based on the evaluation scores of the plurality of historical card data; The step of selecting a preset number of target card data from the plurality of candidate card data based on their respective evaluation scores comprises: Based on the evaluation scores of the preliminary screening card data and the evaluation scores of the current card data, a preset number of target card data are selected from the preliminary screening card data and the current card data.

8. The method according to claim 1, characterized in that In the case where the preset number is greater than or equal to 2, the recommending the target card data to a parent device associated with the learning device includes: The preset number of target card data are recommended to the parent device once or multiple times according to the set time.

9. The method according to claim 1, characterized in that: The method further comprises: In response to detecting an interactive operation triggered by the parent device based on the target card data, generating interactive card data, wherein the interactive card data includes an interactive reason and / or encouraging words; Pushing the interactive card data to the learning device.

10. The method according to claim 9, characterized in that The interaction reason is determined based on the usage scenario data corresponding to the target card data; The encouraging words are presented in the form of the parent's title, tone and / or intonation.

11. The method according to claim 9, characterized in that The method further comprises: generating interactive reward data in response to detecting that the learning device triggers an operation for receiving the interactive card data; The interactive reward data is accumulated into reward data statistics of the learning device, and the reward data statistics are called based on a preset interface in the learning device.

12. A cross-device interaction method, characterized in that: Applied to a parent device, the method includes: Receive target card data recommended by the server; Wherein, the target card data is recommended to the parent device by the server based on the method described in any one of claims 1 to 11; In response to detecting that a display condition of the target card data is met, the target card data is displayed, and the target card data is used for the parent device to interact with the learning device.

13. The method according to claim 12, characterized in that The method further comprises: In response to detecting an interactive operation triggered by displayed target card data, a first notification message is sent to the server, wherein the first notification message is used to trigger the server to generate interactive card data and push the interactive card data to the learning device, wherein the interactive card data includes reasons for interaction and / or encouraging words.

14. A cross-device interaction method, characterized in that: Applied to a learning device, the method comprises: Receiving interactive card data pushed by a server, wherein the interactive card data includes reasons for interaction and / or encouraging words, and the interactive card data is generated by the server after detecting an interactive operation triggered by a parent device based on target card data, wherein the target card data is recommended to the parent device by the server based on the method described in any one of claims 1 to 11; In response to detecting that a display condition of the interactive card data is met, the interactive card data is displayed.

15. The method according to claim 14, characterized in that The method further comprises: In response to detecting a receiving operation triggered by displayed interactive card data, a second notification message is sent to the server, and the second notification message is used to trigger the server to generate interactive reward data, and accumulate the interactive reward data into the reward data statistics of the learning device, and the reward data statistics are called based on a preset interface in the learning device.

16. A cross-device interactive device, characterized in that: Applied to the server, the device comprises: A current card generation module, configured to generate current card data based on the usage scenario data of the learning device in a current time period in response to obtaining the usage scenario data; An evaluation score determination module, used to determine the evaluation score of the current card data based on a preset evaluation strategy; A target card selection module, configured to select a preset number of target card data from a plurality of candidate card data based on respective evaluation scores of the plurality of candidate card data, wherein the plurality of candidate card data at least includes the current card data; The target card recommendation module is used to recommend the target card data to a parent device associated with the learning device, and the target card data is used for the parent device to interact with the learning device.

17. A cross-device interactive device, characterized in that: Applied to parent equipment, the device comprises: The target card receiving module is used to receive the target card data recommended by the server; wherein the target card data is recommended by the server to the parent device based on the apparatus of claim 16; The target card display module is used to display the target card data in response to detecting that the display condition of the target card data is met, and the target card data is used for the parent device to interact with the learning device.

18. A cross-device interactive device, characterized in that: Applied to a learning device, the device comprises: An interactive card receiving module, configured to receive interactive card data pushed by a server, wherein the interactive card data includes reasons for interaction and / or encouraging words, and the interactive card data is generated by the server after detecting an interactive operation triggered by a parent device based on target card data, wherein the target card data is recommended by the server to the parent device based on the apparatus according to claim 16; The interactive card display module is used to display the interactive card data in response to detecting that the display condition of the interactive card data is met.

19. An electronic device, characterized in that: The electronic device comprises: processor; memory for storing computer programs; Wherein, the processor is configured to implement the cross-device interaction method described in any one of claims 1 to 15 when executing the computer program.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is processed by the processor, the cross-device interaction method described in any one of claims 1 to 15 is implemented.

21. A computer program product having a computer program stored thereon, characterized in that: When the computer program is processed by a processor, the cross-device interaction method according to any one of claims 1 to 15 is implemented.

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