Application recommendation method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of teaching equipment, and provides an application recommendation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a current page image of a book read by a user; determining a target tool application according to page features of the current page image; and recommending the target tool application to the user. Through the setting, the electronic equipment can deduce the current learning demand of the user according to the page characteristics of the current book page, so that the tool application related to the current book page is recommended, and the accuracy of application recommendation is improved.

Description

Technical Field

[0001] The present application relates to the technical field of teaching equipment, and in particular to an application recommendation method, device, electronic device and storage medium. Background Art

[0002] Electronic devices such as learning machines or learning tablets usually have a large number of tool applications, such as dictation, recitation, translation, question search and point reading, etc. When users encounter learning problems, they can use these tool applications to help solve them. However, currently, such electronic devices generally recommend tool applications to users randomly, which is difficult to meet the current learning needs of users, resulting in low accuracy of application recommendations. Summary of the invention

[0003] In view of this, embodiments of the present application provide an application recommendation method, device, electronic device, and storage medium, which can improve the accuracy of application recommendations.

[0004] A first aspect of an embodiment of the present application provides an application recommendation method, including:

[0005] Get the current page image of the book the user is reading;

[0006] Determine the target tool application according to the page features of the current page image;

[0007] Recommend target tool applications to users.

[0008] In the embodiment of the present application, an electronic device such as a learning machine can obtain the current page image of the book that the user is reading, then identify the page features of the current page image, and determine the corresponding target tool application based on the page features, and finally recommend the target tool application to the user. Through such a setting, the electronic device can infer the user's current learning needs based on the page features of the current book page, thereby recommending tool applications related to the current book page, thereby improving the accuracy of application recommendations.

[0009] In an implementation of the embodiment of the present application, determining the target tool application according to the page features of the current page image may include:

[0010] Determining the page content type of the current page image according to the page feature;

[0011] The target tool application is determined according to the page content type.

[0012] Furthermore, determining the target tool application according to the page content type may include:

[0013] If the page content type is a text page, determining the scene mode to enter according to the page features;

[0014] Each tool application associated with the scene mode is determined as the target tool application.

[0015] Further, determining the scene mode to be entered according to the page feature may include:

[0016] Determining whether there is handwriting of the user in the text area of ​​the current page image according to the page feature;

[0017] If the handwriting of the user exists, determining that the scene mode entered is the review mode;

[0018] If there is no handwriting of the user, it is determined that the entered scene mode is the preview mode.

[0019] Further, determining each tool application associated with the scene mode as the target tool application may include:

[0020] Determine the subject corresponding to the current page image;

[0021] Each tool application associated with the scene mode and the subject is determined as the target tool application.

[0022] Furthermore, determining the target tool application according to the page content type may include:

[0023] If the page content type is a non-text page, each tool application associated with the page content type is determined as the target tool application.

[0024] In an implementation of the embodiment of the present application, the method may further include:

[0025] Recording the user's learning behavior data;

[0026] Determining the user's learning problem based on the learning behavior data;

[0027] Recommending learning materials associated with the learning problem to the user.

[0028] A second aspect of an embodiment of the present application provides an application recommendation device, including:

[0029] An image acquisition module is used to acquire the current page image of the book that the user is reading;

[0030] An application determination module, used to determine a target tool application according to page features of the current page image;

[0031] An application recommendation module is used to recommend the target tool application to the user.

[0032] A third aspect of an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the application recommendation method provided in the first aspect of the embodiment of the present application is implemented.

[0033] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the application recommendation method provided in the first aspect of the embodiment of the present application is implemented.

[0034] A fifth aspect of the embodiments of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the application recommendation method provided in the first aspect of the embodiments of the present application.

[0035] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of an application recommendation method provided in an embodiment of the present application;

[0037] Figure 2 This is a schematic diagram of an operation flow of an electronic device provided in an embodiment of the present application when performing application recommendation;

[0038] Figure 3 This is a schematic diagram of a display effect of the application recommendation method provided in an embodiment of the present application;

[0039] Figure 4 This is another display effect diagram of the application recommendation method provided in the embodiment of the present application;

[0040] Figure 5 It is a structural framework diagram of an application recommendation device provided in an embodiment of the present application;

[0041] Figure 6 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures, technologies, etc. are proposed, so as to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed description of well-known systems, devices, circuits and methods is omitted to prevent unnecessary details from hindering the description of the present application. In addition, in the description of the present application specification and the attached claims, the terms "first", "second", "third" etc. are only used to distinguish the description, and cannot be interpreted as indicating or suggesting relative importance.

[0043] Electronic devices such as tutoring machines and learning tablets can provide high-quality learning resources and have rich tool applications such as dictation, recitation, translation, question search and point reading. However, at present, such electronic devices generally recommend tool applications to users randomly, and there is a problem of low accuracy in application recommendation. To address this problem, the embodiments of the present application provide an application recommendation method, device, electronic device and storage medium, which can infer the user's current learning needs based on the page features of the current book page, and improve the accuracy of application recommendation. For more specific technical implementation details of the embodiments of the present application, please refer to the various embodiments described below.

[0044] It should be understood that the execution subjects of the various method embodiments of the present application are various types of electronic devices, such as mobile phones, tablet computers, wearable devices, learning machines, tutoring machines, learning tablets, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), large-screen TVs, etc. The embodiments of the present application do not impose any restrictions on the specific types of the electronic devices.

[0045] See also Figure 1 , showing an application recommendation method provided by an embodiment of the present application, including:

[0046] 101. Obtain the current page image of the book that the user is reading;

[0047] The executor of the embodiment of the present application may be an electronic device with teaching functions such as a tutoring machine or a learning tablet. When a user reads a book in front of the electronic device, the front image can be captured through the front camera of the electronic device, thereby obtaining the current page image of the book read by the user in real time.

[0048] In an implementation of the embodiment of the present application, before acquiring the current page image of the book read by the user, the following steps may also be included:

[0049] (1) Detect whether there is an obstruction in front of the electronic device;

[0050] (2) If there is an obstruction in front of the electronic device, detect whether there is a face or a book in front of the electronic device;

[0051] (3) If there is a face or a book in front of the electronic device, the electronic device is controlled to enter the operation mode.

[0052] The electronic device can detect in real time whether there is an obstruction in front of it. When there is an obstruction, face detection is started to further determine whether the obstruction is a person. When there is no obstruction, it means that there is definitely no person in front of the electronic device, so there is no need to start face detection, which can reduce the consumption of device resources. Specifically, when detecting whether there is an obstruction in front of the electronic device, an infrared pair tube or a distance sensor can be used, and a detection method based on direct measurement of flight time (dtof) or a detection method based on indirect measurement of flight time (itof), etc., and the embodiment of the present application does not limit the specific method of detecting the obstruction. If an obstruction is detected in front of the electronic device, the front camera of the electronic device can be turned on to start face detection and book detection. In actual operation, the image can be analyzed and processed to identify whether there are faces and books in the image at the same time, wherein various face detection algorithms can be used to identify faces, and book target detection algorithms based on deep learning can be used to identify books. If the electronic device detects that there are faces and books in front of it at the same time, it can be determined with a high probability that the user is doing homework, thereby controlling the electronic device to enter the operation mode. In addition, the judgment can also be made based on the user's working time pattern. For example, when a face and a book are detected in front of the electronic device at the same time, and the current time is within the user's regular working time range, the electronic device is controlled to enter the working mode.

[0053] Furthermore, after controlling the electronic device to enter the operation mode, the following steps may also be included:

[0054] (1) Detect the type of book;

[0055] (2) Control the electronic device to enter the functional mode corresponding to the type.

[0056] The electronic device can also further detect the type of book that the user is currently reading, and thus enter a functional mode corresponding to the type of the book. For example, if the type of book is a textbook, it enters functional mode one: textbook learning mode; if the type of book is an exercise book, it enters functional mode two: exercise book learning mode, and so on. After entering different functional modes, the electronic device can recommend targeted tool applications respectively. For example, in the textbook learning mode, it can recommend knowledge point summarization, point reading and other applications. When detecting the type of book, the current page image captured can be used to perform a full-page image search, and matched with a book database stored locally or on a server (such as a textbook library or an exercise book library), and the type of book can be determined based on the matching results.

[0057] In addition, after entering the homework mode and matching the corresponding functional mode, the electronic device can start the homework guarding function. For example, when the user is using a textbook to do homework, the electronic device can start the homework mode and enter the textbook learning mode. After that, the electronic device can enter the black screen state and silently guard while the user is doing homework without disturbing the user. At this time, the front camera of the electronic device will continue to monitor the book the user is reading and the user's posture. When the user asks a question, the electronic device can immediately answer it. When the user has a bad sitting posture, the electronic device can also immediately remind the user.

[0058] 102. Determine the target tool application according to the page features of the current page image;

[0059] After obtaining the current page image of the book that the user is reading, the corresponding target tool application can be determined based on the page features of the current page image. For example, based on the page features such as pictures, texts and other elements contained in the current page image, the content type of the book page corresponding to the current page image can be inferred, and then the user's real learning purpose can be predicted, and the tool application that matches the real learning purpose can be recommended as the target tool application.

[0060] In an implementation of the embodiment of the present application, determining the target tool application according to the page features of the current page image may include:

[0061] (1) Determine the page content type of the current page image based on page features;

[0062] (2) Determine the target tool application based on the page content type.

[0063] According to the page features of the current page image, the page content type of the current page image can be determined, and then the corresponding target tool application is determined based on the page content type. Among them, the page content type may include but is not limited to: text page, unit review page, word training page, composition practice page and exercise page, etc. Specifically, the electronic device can match the page features of the current page image with the page features of the stored page images of various different page content types (for example, pages of different page content types of various books stored locally or on the server of the electronic device), and the page content type of the current page image can be determined according to the matching results. In addition, the electronic device can pre-store tool applications corresponding to each page content type, for example, the text page corresponds to tool applications such as text reading, listening to the text and text annotation, and the composition practice page corresponds to tool applications such as composition diagnosis and composition guidance, and so on. Through such settings, the corresponding target tool application can be determined according to the page content type of the current page image.

[0064] Furthermore, determining the target tool application according to the page content type may include:

[0065] (1) If the page content type is a text page, the scene mode to be entered is determined according to the page features;

[0066] (2) Each tool application associated with the scene mode is determined as a target tool application.

[0067] If the page content type of the current page image is a text page, the electronic device can determine the scene mode to enter according to the page features of the current page image, and after entering the determined scene mode, determine each tool application associated with the scene mode as the target tool application. In actual operation, the electronic device can pre-set multiple scene modes, page features corresponding to entering each scene mode, and tool applications associated with each scene mode.

[0068] Furthermore, determining the scene mode to be entered according to the page features may include:

[0069] (1) determining whether there is a user's handwriting in the text area of ​​the current page image according to page features;

[0070] (2) If there is handwriting of the user, determining that the scene mode entered is the review mode;

[0071] (3) If there is no handwriting of the user, it is determined that the scene mode entered is the preview mode.

[0072] When determining the scene mode to be entered according to the page features of the current page image, it can be determined based on the page features whether there is a user's handwriting in the text area of ​​the current page image (since the current page image belongs to the text page, there must be a text area), such as various types of writing marks such as stroke lines and frame selection lines of the text content. If the user's handwriting exists in the text area, it means that the user has read and learned the text content of the current page image before, so it can be determined that the scene mode entered is the review mode. If the user's handwriting does not exist in the text area, it means that the user has not read and learned the text content of the current page image before, so it can be determined that the scene mode entered is the preview mode. In addition, a threshold value (for example, 3 places) for the number of handwriting can also be set. When the number of handwritings in the text area exceeds the threshold, the review mode is entered, otherwise the preview mode is entered. When the electronic device enters the review mode, each tool application associated with the review mode will be determined as a target tool application and recommended to the user. For example, the review mode can be associated with tool applications such as reading and reciting, dictation, text interpretation, and video explanation. When the electronic device enters the preview mode, the various tool applications associated with the preview mode will be identified as target tool applications and recommended to the user. For example, the preview mode can be associated with tool applications such as text word marking, text reading, text annotation, and after-class word copying.

[0073] Furthermore, determining each tool application associated with the scene mode as a target tool application may include:

[0074] (1) Determine the subject corresponding to the current page image;

[0075] (2) Each tool application associated with the scene mode and the subject is determined as a target tool application.

[0076] After the electronic device determines and enters the corresponding scene mode according to the page features of the current page image, it can determine the recommended target tool application in combination with the scene mode and the subject corresponding to the current page image, that is, the recommended tool application is not only related to the scene mode, but also to the subject corresponding to the current page image, which can further improve the accuracy of application recommendation. Specifically, in the process of determining the page content type of the current page image according to the page features described above, the subject corresponding to the current page image can also be identified based on the page features, such as Chinese, mathematics, and English, and the electronic device can preset the tool application associated with each subject.

[0077] Exemplarily, assuming that the scene mode entered by the electronic device is the preview mode and the subject corresponding to the current page image is Chinese, then tool applications such as marking new words in the text, reading the text aloud, annotating the text, and copying new words after class can be determined as target tool applications; assuming that the scene mode entered by the electronic device is the preview mode and the subject corresponding to the current page image is English, then tool applications such as learning words, reading aloud, listening to the text, and synchronized video can be determined as target tool applications; assuming that the scene mode entered by the electronic device is the review mode and the subject corresponding to the current page image is Chinese, then tool applications such as reading aloud and reciting, dictation, text interpretation, and video explanation can be determined as target tool applications; assuming that the scene mode entered by the electronic device is the review mode and the subject corresponding to the current page image is English, then tool applications such as word dictation, reading the text, practicing oral English, and synchronized practice can be determined as target tool applications.

[0078] Furthermore, determining the target tool application according to the page content type may include:

[0079] If the page content type is a non-text page, each tool application associated with the page content type is determined as a target tool application.

[0080] If the page content type of the current page image is a non-text page such as a unit review page, a word training page, a composition practice page, and an exercise page, the electronic device will not enter a scene mode such as a preview mode or a review mode, and at this time, each tool application associated with the page content type can be directly determined as a target tool application for recommendation. In actual operation, the electronic device can pre-set tool applications corresponding to each page content type, for example, a composition practice page corresponds to tool applications such as composition diagnosis and composition guidance, and a word training page corresponds to tool applications such as literacy, writing, and dictation.

[0081] 103. Recommend target tool applications to users.

[0082] After the target tool applications are determined according to the page features of the current page image, these target tool applications can be recommended to the user. Since the target tool applications are tool applications related to the current book page, the accuracy of application recommendation can be improved to a certain extent compared to the random recommendation method. There are many ways to recommend the target tool applications, such as outputting the names of the target tool applications on the screen of the electronic device, or displaying the startup icons of the target tool applications, etc.

[0083] In one implementation of the embodiment of the present application, the current page image can be displayed on the screen of the electronic device, and the startup icons of various target tool applications can be displayed in sequence on the right side of the current page image. For example, if the scene mode entered is the preview mode and the subject corresponding to the current page image is Chinese, the startup icons of tool applications such as text word marking, text reading, text annotation, and after-class word copying can be displayed in a column on the right side of the current page image; if the scene mode entered by the electronic device is the review mode and the subject corresponding to the current page image is English, the startup icons of tool applications such as word dictation, text reading, oral practice, and synchronous practice can be displayed in a column on the right side of the current page image.

[0084] Furthermore, the startup icons of each target tool application can be arranged in a certain order, so as to achieve a guided application recommendation effect with a certain order. For example, if the scene mode entered is the preview mode and the subject corresponding to the current page image is Chinese, the target application tools include text word marking, text reading, text annotation and after-class word copying, and in the process of the user's preview, it is generally necessary to complete the preview in the order of text word marking - text reading - text annotation - after-class word copying, then the startup icons of each target tool application can be displayed in order from top to bottom in the order of text word marking - text reading - text annotation - after-class word copying, so as to achieve a guided preview effect. Similarly, for the review mode, the same method can be used to achieve a guided review effect.

[0085] In an implementation of the embodiment of the present application, the method may further include:

[0086] (1) Record users’ learning behavior data;

[0087] (2) Determine the user’s learning problems based on learning behavior data;

[0088] (3) Recommend learning materials related to learning problems to users.

[0089] In the process of learning by the user using the electronic device, the electronic device can also record the user's learning behavior data in real time, evaluate according to the learning behavior data, determine the user's learning problems, and then recommend learning materials associated with the learning problems to the user, so as to assist the user in solving the learning problems. Exemplarily, in the process of the user using the electronic device to preview or review the teaching materials, the electronic device can record the user's learning behavior data in real time, and evaluate the corresponding learning problems, such as recitation effect evaluation, dictation result evaluation and video explanation completion, etc., which can capture the user's learning problems in different knowledge specialties. Specifically, in the process of reciting by the user, the electronic device can record the voice signal emitted by the user and recognize it, compare the recognition result with the standard recitation text, so as to evaluate the accuracy and pronunciation of the recitation, and record the time taken by the user to recite, so as to evaluate the user's recitation efficiency. After the user finishes the dictation, the electronic device can obtain the user's writing results, and compare the writing results with the standard dictation answers, so as to complete the dictation result evaluation. If it is determined through the evaluation that the user has learning problems such as low recitation efficiency and low recitation accuracy, relevant recitation skills solutions and pronunciation improvement solutions and other learning materials can be recommended to the user. If the assessment determines that the user has a learning problem of poor dictation performance, relevant learning materials such as spelling correction schemes, stroke order schemes, writing practice schemes and word shorthand schemes can be recommended to the user.

[0090] In the embodiment of the present application, an electronic device such as a learning machine can obtain the current page image of the book that the user is reading, then identify the page features of the current page image, and determine the corresponding target tool application based on the page features, and finally recommend the target tool application to the user. Through such a setting, the electronic device can infer the user's current learning needs based on the page features of the current book page, thereby recommending tool applications related to the current book page, thereby improving the accuracy of application recommendations.

[0091] like Figure 2 FIG. 1 is a schematic diagram of an operation flow of an electronic device provided in an embodiment of the present application when performing application recommendation. Figure 2In the process of learning, the electronic device can actively detect whether there are obstructions, faces and books in front of it, so as to start the learning mode. Scene recognition means that the electronic device can detect the image of the book page on the desk, identify the type of book by searching the whole page, and enter the learning mode corresponding to the book type, such as textbook learning mode, exercise book learning mode, etc. Homework protection means that when the electronic device enters the corresponding learning mode, the screen will be black and silent, but the camera will keep working, and the book page and the user's sitting posture will be monitored in real time. Pre-review mode determination means that the electronic device can determine whether to enter the preview mode or review mode according to the page characteristics of the textbook page, and recommend the corresponding tool application for each mode. Pre-review problem capture means that the electronic device can record the user's learning behavior data in the pre-review process in real time, and evaluate the learning problems that the user has in different knowledge projects. Special project recommendation means that the electronic device can recommend corresponding problem solutions and other learning materials according to the learning problems that the user has in different knowledge projects.

[0092] like Figure 3 The figure is a schematic diagram of a display effect of the application recommendation method provided in an embodiment of the present application. Figure 3 What is displayed is the current page image of the book read by the user obtained by the electronic device. The current page image belongs to the textbook page and there is no handwriting of the user in the text content, so the electronic device enters the preview mode. It can be seen that the launch icons of various tool applications associated with the preview mode are displayed in a column from top to bottom in sequence on the right side of the current page image, namely tool application 1 to tool application 6.

[0093] like Figure 4 , which is another schematic diagram of the display effect of the application recommendation method provided in an embodiment of the present application. Figure 4 What is displayed is the current page image of the book that the user is reading, which is obtained by the electronic device. The current page image belongs to the textbook page and the text content contains the user's handwriting, so the electronic device enters the review mode. It can be seen that the launch icons of various tool applications associated with the review mode are displayed in a column from top to bottom, that is, tool application A to tool application D.

[0094] In summary, the embodiments of the present application can judge the different learning needs of users according to the characteristics of different pages in the book, and recommend tool applications related to the current book page, thereby improving the accuracy of application recommendation. In addition, the embodiments of the present application can provide a guided pre-review process, and can also obtain the user's learning problems based on the user's behavior evaluation during the pre-review process, and provide corresponding problem solutions.

[0095] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0096] The above mainly describes an application recommendation method, and the following will describe an application recommendation device.

[0097] See also Figure 5 , an embodiment of an application recommendation device in the embodiment of the present application includes:

[0098] The image acquisition module 501 is used to acquire the current page image of the book that the user is reading;

[0099] An application determination module 502, used to determine a target tool application according to the page features of the current page image;

[0100] The application recommendation module 503 is used to recommend the target tool application to the user.

[0101] In an implementation of the embodiment of the present application, the application determination module may include:

[0102] A page content type determination unit, used to determine the page content type of the current page image according to the page feature;

[0103] The application determination unit is used to determine the target tool application according to the page content type.

[0104] Further, the application determination unit may include:

[0105] A scene mode control subunit, for determining a scene mode to be entered according to the page characteristics if the page content type is a text page;

[0106] The first application determination subunit is used to determine each tool application associated with the scene mode as the target tool application.

[0107] Furthermore, the scene mode control subunit may include:

[0108] A handwriting determination subunit, used for determining whether there is handwriting of the user in the text area of ​​the current page image according to the page feature;

[0109] A review mode control subunit, configured to determine that the scene mode entered is the review mode if there is handwriting of the user;

[0110] The preview mode control subunit is used to determine that the entered scene mode is the preview mode if there is no handwriting of the user.

[0111] Furthermore, the first application determination subunit may include:

[0112] A subject determination subunit, used to determine the subject corresponding to the current page image;

[0113] The second application determination subunit is used to determine each tool application associated with the scene mode and the subject as the target tool application.

[0114] Further, the application determination unit may include:

[0115] The third application determination subunit is used to determine each tool application associated with the page content type as the target tool application if the page content type is a non-text page.

[0116] In one implementation of the embodiment of the present application, the application recommendation device may further include:

[0117] A learning behavior data recording module, used to record the learning behavior data of the user;

[0118] A learning problem determination module, used to determine the user's learning problem based on the learning behavior data;

[0119] The learning material recommendation module is used to recommend learning materials associated with the learning problem to the user.

[0120] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the application recommendation method described in any of the above embodiments is implemented.

[0121] An embodiment of the present application also provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the application recommendation method described in any of the above embodiments.

[0122] Figure 6 is a schematic diagram of an electronic device provided by an embodiment of the present application. Figure 6 As shown, the electronic device 6 of this embodiment includes: a processor 60, a memory 61, and a computer program 62 stored in the memory 61 and executable on the processor 60. When the processor 60 executes the computer program 62, the steps in the above-mentioned embodiments of the application recommendation method are implemented, for example Figure 1 Alternatively, when the processor 60 executes the computer program 62, the functions of each module / unit in the above-mentioned device embodiments are realized, for example, Figure 5 Functions of modules 501 to 503 are shown.

[0123] The computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the electronic device 6.

[0124] The processor 60 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0125] The memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. The memory 61 may also be an external storage device of the electronic device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the electronic device 6. The memory 61 is used to store the computer program and other programs and data required by the electronic device. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0126] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0128] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0130] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0131] 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 distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0132] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0133] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0134] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An application recommendation method, characterized in that: include: Get the current page image of the book the user is reading; Determining a target tool application according to page features of the current page image; The target tool application is recommended to the user.

2. The method according to claim 1, characterized in that The step of determining a target tool application according to the page features of the current page image includes: Determining the page content type of the current page image according to the page feature; The target tool application is determined according to the page content type.

3. The method according to claim 2, characterized in that The step of determining the target tool application according to the page content type includes: If the page content type is a text page, determining the scene mode to enter according to the page features; Each tool application associated with the scene mode is determined as the target tool application.

4. The method according to claim 3, characterized in that The step of determining the scene mode to be entered according to the page feature includes: Determining whether there is handwriting of the user in the text area of ​​the current page image according to the page feature; If the handwriting of the user exists, determining that the scene mode entered is the review mode; If there is no handwriting of the user, it is determined that the entered scene mode is the preview mode.

5. The method according to claim 3, characterized in that The step of determining each tool application associated with the scene mode as the target tool application includes: Determine the subject corresponding to the current page image; Each tool application associated with the scene mode and the subject is determined as the target tool application.

6. The method according to claim 2, characterized in that The step of determining the target tool application according to the page content type includes: If the page content type is a non-text page, each tool application associated with the page content type is determined as the target tool application.

7. The method according to any one of claims 1 to 6, characterized in that: Also includes: Recording the user's learning behavior data; Determining the user's learning problem based on the learning behavior data; Recommending learning materials associated with the learning problem to the user.

8. An application recommendation device, characterized in that: include: An image acquisition module is used to acquire the current page image of the book that the user is reading; An application determination module, used to determine a target tool application according to page features of the current page image; An application recommendation module is used to recommend the target tool application to the user.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the application recommendation method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the application recommendation method according to any one of claims 1 to 7 is implemented.

Images