A management system and method for online teaching resource library based on big data

Abstract

The present application is applicable to the field of teaching resource library management technology, and in particular to a management system and method for an online teaching resource library based on big data, the method comprising: obtaining login information; obtaining a user tag set based on the login information; obtaining a first resource recommendation set based on the user tag set; obtaining a trigger signal, and obtaining an operation state based on the trigger signal; obtaining a second resource recommendation set based on the operation state and the first resource recommendation set; wherein the second resource recommendation set includes at least one teaching resource; and modifying the user tag set based on the first resource recommendation set and the second resource recommendation set. The embodiment of the present application provides a management system and method for an online teaching resource library based on big data, which can improve the problem that students find it difficult to obtain teaching resources of interest from an online teaching resource library in a timely manner.

Description

Technical Field

[0001] The present application belongs to the technical field of teaching resource library management, and in particular, relates to a management system and method for an online teaching resource library based on big data. Background Art

[0002] When students encounter difficulties in the learning process or want to improve themselves, they can obtain corresponding teaching resources through the online teaching resource library for learning. However, the teaching resources in the online teaching resource library are complicated and it is difficult for students to obtain the teaching resources they are interested in in a timely manner. Summary of the invention

[0003] The embodiment of the present application provides a management system and method based on a big data online teaching resource library, which can improve the problem that students have difficulty in obtaining teaching resources of interest from the online teaching resource library in a timely manner.

[0004] In a first aspect, the present application embodiment provides a method for managing an online teaching resource library based on big data, including:

[0005] Obtaining login information; wherein each of the login information corresponds to a user, and the login information includes account information and password information;

[0006] A user tag set is obtained based on the login information; wherein the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one of the resource tags;

[0007] Obtaining a first resource recommendation set based on the user tag set; wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to send and display on a user terminal;

[0008] Acquire a trigger signal, and obtain an operation state based on the trigger signal; wherein the trigger signal is a signal sent when a user touches the screen of the user terminal, and the operation state reflects the operation of the user on the user terminal;

[0009] Obtaining a second resource recommendation set based on the operation state and the first resource recommendation set; wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to be sent and displayed on the user terminal;

[0010] The user tag set is modified based on the first resource recommendation set and the second resource recommendation set.

[0011] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0012] The embodiment of the present application provides a method for managing an online teaching resource library based on big data. By first obtaining login information corresponding to a user including account information and password information, the identity of the user is confirmed, and a basis is provided for providing teaching resources suitable for the user. Then, based on the login information, a user tag set including at least one user tag is obtained to provide a basis for providing teaching resources suitable for the user. After that, a first resource recommendation set including at least one teaching resource is obtained based on the user tag set to ensure that the pushed teaching resources meet the user's interests and hobbies. Then, a trigger signal is obtained, and based on the trigger signal, an operation state reflecting the user's operation on the user terminal is obtained, and the user's interest in each pushed teaching resource is analyzed to provide a basis for pushing the teaching resources of interest to the user. Then, based on the operation state and the first resource recommendation set, a second resource recommendation set including at least one teaching resource is obtained to ensure that the teaching resources pushed to the user meet the user's interests and hobbies. Finally, the user tag set is modified based on the first resource recommendation set and the second resource recommendation set to optimize the user experience, so that the user can directly push the teaching resources of interest to the user when the user logs in next time.

[0013] In a second aspect, the embodiment of the present application provides a management system for an online teaching resource library based on big data, including:

[0014] A login unit, used to obtain login information, and obtain a user tag set based on the login information; wherein each of the login information corresponds to a user, and the login information includes account information and password information; the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one of the resource tags;

[0015] A resource push unit, the resource push unit includes a first analysis module, a collection module, a second analysis module and a push module; wherein the first analysis module is used to obtain a first resource recommendation set based on the user tag set, wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to send and display on the user terminal; the collection module is used to obtain a trigger signal and obtain an operation state based on the trigger signal, wherein the trigger signal is a signal sent when the user touches the screen of the user terminal, and the operation state reflects the user's operation on the user terminal; the second analysis module is used to obtain a second resource recommendation set based on the operation state and the first resource recommendation set, wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to send and display on the user terminal; the push module is used to push the first resource recommendation set or the second resource recommendation set to the user terminal;

[0016] A feedback unit is used to modify the user tag set based on the first resource recommendation set and the second resource recommendation set.

[0017] In a third aspect, an embodiment of the present application provides a device for managing an online teaching resource library based on big data, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the methods described in the first aspect when executing the computer program.

[0018] In a fourth aspect, 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 method described in any one of the above-mentioned first aspects is implemented.

[0019] It can be understood that the beneficial effects of the second to fourth 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

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a flowchart of a method for managing an online teaching resource library based on big data provided by an embodiment of the present application;

[0022] Figure 2 It is a flowchart of step S300 in a method for managing an online teaching resource library based on big data provided by an embodiment of the present application;

[0023] Figure 3 It is a flowchart of step S440 in a method for managing an online teaching resource library based on big data provided by an embodiment of the present application;

[0024] Figure 4 It is a flowchart of step S500 in a method for managing an online teaching resource library based on big data provided by an embodiment of the present application;

[0025] Figure 5 It is a flowchart of step S600 in a method for managing an online teaching resource library based on big data provided by an embodiment of the present application;

[0026] Figure 6This is a structural diagram of a big data online teaching resource library management system provided by an embodiment of the present application;

[0027] Figure 7 It is a structural diagram of a big data online teaching resource library management device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0028] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0029] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0030] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0031] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0032] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0033] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0034] In the related art, when students encounter difficulties in the learning process or want to improve themselves, they can obtain corresponding teaching resources for learning through the online teaching resource library. However, the teaching resources in the online teaching resource library are complicated and it is difficult for students to obtain the teaching resources they are interested in in a timely manner.

[0035] To solve the above problems, the embodiment of the present application provides a management system and method for an online teaching resource library based on big data. In the method, by first obtaining login information corresponding to a user including account information and password information, the identity of the user is confirmed, and a basis is provided for providing teaching resources suitable for the user. Then, based on the login information, a user tag set including at least one user tag is obtained, and a basis is provided for providing teaching resources suitable for the user. After that, a first resource recommendation set including at least one teaching resource is obtained based on the user tag set to ensure that the pushed teaching resources meet the user's interests and hobbies. Then, a trigger signal is obtained, and based on the trigger signal, an operation state reflecting the user's operation on the user terminal is obtained, and the user's interest in each pushed teaching resource is analyzed, so as to provide a basis for pushing the teaching resources of interest to the user. Then, based on the operation state and the first resource recommendation set, a second resource recommendation set including at least one teaching resource is obtained to ensure that the teaching resources pushed to the user meet the user's interests and hobbies. Finally, the user tag set is modified based on the first resource recommendation set and the second resource recommendation set, so as to optimize the user experience, so that the teaching resources of interest to the user can be directly pushed when the user logs in next time.

[0036] The skin care product formula development method provided in the embodiment of the present application can be applied to a terminal device. In this case, the terminal device is the executor of a method for managing an online teaching resource library based on big data provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the terminal device.

[0037] For example, the terminal device may be a mobile phone, a tablet computer, a laptop computer, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, etc.

[0038] In order to better understand the management method of an online teaching resource library based on big data provided in an embodiment of the present application, the specific implementation process of the management method of an online teaching resource library based on big data provided in an embodiment of the present application is exemplarily introduced below.

[0039] Figure 1 A schematic flow chart of a method for managing an online teaching resource library based on big data provided by an embodiment of the present application is shown. The method for managing an online teaching resource library based on big data includes:

[0040] S100, obtaining login information; wherein each login information corresponds to a user, and the login information includes account information and password information.

[0041] It is understood that the method of obtaining login information can be based on Web application login information acquisition, or based on operating system login information acquisition, etc., but not limited thereto. Acquiring login information including account information and password information can confirm the identity of the user and provide a basis for providing teaching resources suitable for the user.

[0042] S200, obtaining a user tag set based on login information; wherein the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one resource tag.

[0043] It can be understood that the method of obtaining the user tag set based on the login information can be to search the account included in the account information in the login information in a preset database, and confirm all the user tags reflecting the user's interests corresponding to the account obtained by the search as the user tag set, or to search the location information included in the account information in the login information in a preset database, and confirm all the user tags corresponding to other account information with the same location information obtained by the search as the user tag set, etc., but not limited to this. Obtaining a user tag set including at least one user tag and a tag weight corresponding to the user tag based on the login information can provide a basis for providing teaching resources suitable for the user.

[0044] In a possible implementation, S200, obtaining a user tag set based on login information includes:

[0045] S210, query the account information in the user database to obtain a verification password corresponding to the account information.

[0046] It can be understood that a user database is a database that can store account information, password information, user tags corresponding to the account information, and tag weights corresponding to the user tags of multiple users. For example, the user database can be a relational database (MySQL, PostgreSQL, etc.) or a lightweight database (SQLite, etc.), but is not limited thereto. Querying the account information in the user database and obtaining the verification password corresponding to the account information can provide a basis for subsequent steps.

[0047] S220, comparing the password information with the verification password, if the password information is completely consistent with the verification password, confirming at least one user tag corresponding to the account information in the user database and the tag weight corresponding to the user tag as a user tag set.

[0048] It is understood that the way to compare the password information and the verification password may be to use a conditional statement for comparison or to use a hash function for verification, but is not limited thereto. If the password information is completely consistent with the verification password, it means that the user's identity is normal. Confirming at least one user tag corresponding to the account information in the user database and the tag weight corresponding to the user tag as a user tag set can provide a basis for subsequent steps.

[0049] S230: If the password information is not completely consistent with the verification password, a user tag set with empty content is obtained.

[0050] It can be understood that if the password information is not completely consistent with the verification password, it means that the user's identity is abnormal or the user is a guest user, and obtaining a user tag set with empty content can provide a basis for subsequent steps.

[0051] S300, obtaining a first resource recommendation set based on a user tag set; wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to be sent and displayed on a user terminal.

[0052] It can be understood that the first resource recommendation set can be a database table or an Excel table, etc., but is not limited to this. The method of obtaining the first resource recommendation set based on the user tag set can be to search the user tags in the user tag set in the resource database, and confirm the retrieved teaching resources as the first resource recommendation set, or to mix the teaching resources corresponding to the user tags and some teaching resources that do not correspond to the user tags and confirm them as the first resource recommendation set, etc., but is not limited to this. Obtaining the first resource recommendation set including at least one teaching resource based on the user tag set can ensure that the pushed teaching resources are in line with the user's interests and hobbies.

[0053] In one possible implementation, see Figure 2, S300, obtaining a first resource recommendation set based on the user tag set, including:

[0054] S310, dividing the preset push quantity by the total weight to obtain a push ratio; wherein the total weight is the sum of the weights corresponding to the various user tags in the user tag set.

[0055] It is understandable that the preset push quantity may be 100, 500, etc., but is not limited thereto. Dividing the preset push quantity by the total weight to obtain the push proportion can provide a basis for subsequent steps.

[0056] For example, assuming that the preset number of pushes is 500, and the weights corresponding to the user tags in the user tag set are 11, 2, 6, 4, and 7 respectively, the total weight = 11+2+6+4+7=30, and the push ratio = 500 / 30=16.67.

[0057] S320, round down the values ​​obtained by multiplying the weight corresponding to each user tag in the user tag set by the push proportion to obtain a plurality of push values ​​corresponding to each user tag.

[0058] It can be understood that the value obtained by multiplying the weight corresponding to each user tag in the user tag set by the push proportion is rounded down to the push value corresponding to the user tag, which can provide a basis for subsequent steps.

[0059] For example, assuming that the push ratio is 16, and the weight corresponding to a user tag in the user tag set is 11, then the push value corresponding to the user tag = 16*11 = 176.

[0060] S330, selecting teaching resources corresponding to resource tags with the same number of push values ​​as the user tag in the teaching resource library, and confirming all selected teaching resources as the first resource recommendation set.

[0061] It can be understood that the teaching resource library is a database including multiple teaching resources and resource tags corresponding to the teaching resources. For example, the user database can be a relational database (MySQL, PostgreSQL, etc.) or a lightweight database (SQLite, etc.), but is not limited thereto. Selecting teaching resources corresponding to resource tags with the same number of push values ​​as the user tag and confirming all selected teaching resources as the first resource recommendation set can ensure that the pushed teaching resources meet the user's interests.

[0062] For example, assume that the teaching resource library includes teaching resources A, B, and C, the resource tag corresponding to teaching resource A is a, the resource tag corresponding to teaching resource B is b, and the resource tag corresponding to teaching resource C is c. The user tags include a, b, and c. The push value corresponding to user tag a is 50, the push value corresponding to user tag b is 20, and the push value corresponding to user tag c is 30. Then the first resource recommendation set includes 50 teaching resources A, 20 teaching resources B, and 30 teaching resources C.

[0063] S400, acquiring a trigger signal, and obtaining an operation status based on the trigger signal; wherein the trigger signal is a signal sent when a user touches a screen of a user terminal, and the operation status reflects the user's operation on the user terminal.

[0064] It can be understood that the way to obtain the trigger signal can be to receive a trigger signal sent by a user terminal, or to receive a trigger signal sent by an APP that is connected to the teaching resource library, etc., but it is not limited to this. The way to obtain the operation status based on the trigger signal can be to determine the movement trajectory of the trigger signal, or to determine the duration of the trigger signal, etc., but it is not limited to this. Obtaining the trigger signal and obtaining the operation status based on the trigger signal can analyze the user's interest in each pushed teaching resource, and provide a basis for pushing teaching resources of interest to the user.

[0065] In one possible implementation, see Figure 2 , S400, obtaining a trigger signal, and obtaining an operation state based on the trigger signal, including:

[0066] S410, upon receiving a trigger signal, confirming the position of the contact point as the starting position, and starting timing; wherein the contact point is the position where the user touches the screen of the user terminal.

[0067] It can be understood that confirming the position of the contact point as the starting position when the trigger signal is received can provide a basis for subsequent steps.

[0068] S420, when the trigger signal disappears, the position of the contact point is confirmed as the end position, and the timing ends.

[0069] It can be understood that confirming the position of the contact point as the end position when the trigger signal disappears can provide a basis for subsequent steps.

[0070] S430: The straight-line distance between the starting position and the end position is determined as the trigger distance, and the time period recorded from the start timing to the end timing is determined as the trigger duration.

[0071] It can be understood that the straight-line distance between the starting point and the end point can be determined by calculating the number of pixels passed by the straight line segment between the two points, or by calculating the straight-line distance between the two points through an image processing library (such as OpenCV), but is not limited to this.

[0072] S440, obtaining an operation state based on the trigger distance and the trigger duration.

[0073] It is understandable that the method of obtaining the operation state based on the trigger distance and the trigger duration can be to determine the length of the trigger distance, or to determine the length of the trigger duration, etc., but is not limited thereto. Obtaining the operation state based on the trigger distance and the trigger duration can provide a basis for subsequent steps.

[0074] In one possible implementation, see Figure 3 , S440, obtaining an operation state based on the trigger distance and the trigger duration, including:

[0075] S441, determine whether the trigger distance is greater than the preset distance and whether the trigger duration is greater than the preset duration; wherein the trigger distance is the straight-line distance between the starting position and the end position, and the trigger duration is the duration from when the trigger signal is received to when the trigger signal disappears.

[0076] It is understood that the preset distance may be 10 mm, 20 mm, etc., but not limited thereto. The preset duration may be 1 second, 0.5 second, etc., but not limited thereto. Determining whether the trigger distance is greater than the preset distance and determining whether the trigger duration is greater than the preset duration can provide a basis for subsequent steps.

[0077] S442: If the trigger distance is greater than the preset distance and the trigger duration is less than the preset duration, the user's operation from the time the trigger signal is obtained to the time when the trigger signal disappears is confirmed as a sliding operation.

[0078] It can be understood that if the trigger distance is greater than the preset distance and the trigger duration is less than the preset duration, it means that the user's finger is sliding on the screen. The user's operation from the acquisition of the trigger signal to the disappearance of the trigger signal will be confirmed as a sliding operation, which can provide a basis for subsequent steps.

[0079] S443, if the trigger duration is greater than the preset duration, or the trigger distance is greater than the preset distance and the trigger duration is greater than the preset duration, the user's operation from the acquisition of the trigger signal to the disappearance of the trigger signal is confirmed as an observation operation.

[0080] It can be understood that if the trigger duration is longer than the preset duration, or the trigger distance is greater than the preset distance and the trigger duration is longer than the preset duration, it means that the user's finger is in contact with the screen for a long time. Confirming the user's operation from the acquisition of the trigger signal to the disappearance of the trigger signal as an observation operation can provide a basis for subsequent steps.

[0081] S444: If the trigger distance is less than the preset distance and the trigger duration is less than the preset duration, the user's operation from the time the trigger signal is obtained to the time when the trigger signal disappears is confirmed as a selection operation.

[0082] It can be understood that if the trigger distance is less than the preset distance and the trigger duration is less than the preset duration, it means that the user's finger clicks the screen. Confirming the user's operation from the acquisition of the trigger signal to the disappearance of the trigger signal as a selection operation can provide a basis for subsequent steps.

[0083] S445: confirming one operation type among a sliding operation, an observation operation, and a selection operation as the operation state.

[0084] It can be understood that confirming one operation type among the sliding operation, the observing operation and the selecting operation as the operation state can provide a basis for subsequent steps.

[0085] S500, obtaining a second resource recommendation set based on the operation state and the first resource recommendation set; wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to be sent and displayed on a user terminal.

[0086] It is understandable that the second resource recommendation set can be a database table or an Excel table, etc., but is not limited to this. The method of obtaining the second resource recommendation set based on the operation status and the first resource recommendation set can be to add teaching resources to the first resource recommendation set according to the operation type in the operation status to obtain the second resource recommendation set, or to delete teaching resources from the first resource recommendation set according to the operation type in the operation status to obtain the second resource recommendation set, etc., but is not limited to this. Obtaining the second resource recommendation set including at least one teaching resource based on the operation status and the first resource recommendation set can ensure that the pushed teaching resources are in line with the user's interests and hobbies.

[0087] In one possible implementation, see Figure 4 S500, obtaining a second resource recommendation set based on the operation state and the first resource recommendation set, including:

[0088] S510, obtaining an adjustment resource set based on the operation status; wherein the adjustment resource set includes an operation type reflected by the operation status and at least one teaching resource and a resource tag corresponding to the teaching resource.

[0089] It is understandable that the adjustment resource set can be a database table, or an Excel table, etc., but is not limited thereto. The method of obtaining the adjustment resource set based on the operation state can be to select multiple teaching resources according to the operation type in the operation state to obtain the adjustment resource set, or it can be to confirm the teaching resources displayed or displayed on the user terminal as the adjustment resource set according to the operation type in the operation state. Obtaining the adjustment resource set based on the operation state can provide a basis for subsequent steps.

[0090] In one possible implementation, see Figure 4 , S510, obtaining an adjustment resource set based on the operation state, including:

[0091] S511, determine the operation type reflected by the operation status. If the operation type reflected by the operation status is a sliding operation, the resource labels corresponding to the sliding operation and the teaching resources displayed / displayed on the display screen of the user terminal from the beginning of the sliding operation to the end of the sliding operation are confirmed as the adjusted resource set.

[0092] It can be understood that if the operation type reflected by the operation status is a sliding operation, then the resource labels corresponding to the sliding operation and the teaching resources displayed / displayed on the display screen of the user terminal from the beginning to the end of the sliding operation are confirmed as adjusting the resource set, which can provide a basis for subsequent steps.

[0093] S512: If the operation type reflected by the operation status is an observation operation, the observation operation and the resource labels corresponding to the teaching resources displayed on the display screen of the user terminal from the start of the observation operation to the end of the observation operation are confirmed as an adjusted resource set.

[0094] It can be understood that if the operation type reflected by the operation status is an observation operation, the observation operation and the resource labels corresponding to the teaching resources displayed on the display screen of the user terminal from the beginning of the observation operation to the end of the observation operation are confirmed as adjusting the resource set to provide a basis for subsequent steps.

[0095] S513: If the operation type reflected by the operation status is a selection operation, the selection operation and the resource label corresponding to the teaching resource corresponding to the selection operation are confirmed as an adjusted resource set.

[0096] It can be understood that if the operation type reflected by the operation status is a selection operation, confirming the selection operation and the resource tags corresponding to the teaching resources corresponding to the selection operation as adjusting the resource set can provide a basis for subsequent steps.

[0097] S520: Obtain a second resource recommendation set based on the adjusted resource set and the first resource recommendation set.

[0098] It can be understood that the method of obtaining the second resource recommendation set based on the adjusted resource set and the first resource recommendation set can be to add teaching resources with the same resource tags as those in the adjusted resource set to the first resource recommendation set according to the operation type in the adjusted resource set, or to delete teaching resources with the same resource tags as those in the adjusted resource set from the first resource recommendation set according to the operation type in the adjusted resource set, but is not limited thereto. Obtaining the second resource recommendation set based on the adjusted resource set and the first resource recommendation set can ensure that the pushed teaching resources meet the interests and hobbies of the user.

[0099] In one possible implementation, see Figure 4 S520, obtaining a second resource recommendation set based on the adjusted resource set and the first resource recommendation set, including:

[0100] S521, determine the operation type in the adjustment resource set. If the operation type is a sliding operation, the teaching resources included in the pre-display area and having the same resource tags as the teaching resources included in the adjustment resource set are sorted at the back in the pre-display area, or the number of teaching resources included in the pre-display area and having the same resource tags as the teaching resources included in the adjustment resource set is reduced; wherein the pre-display area includes teaching resources in the first resource recommendation set or the second resource recommendation set that have not been displayed / displayed on the display screen of the user terminal.

[0101] It can be understood that the position ranking reflects the position of the teaching resources in the pre-display area. Each teaching resource in the pre-display area corresponds to a position ranking. The teaching resources with smaller position rankings are displayed earlier when the user slides the screen, and the teaching resources with larger position rankings are displayed later when the user slides the screen. If the operation type is a sliding operation, it means that the user is not interested in the teaching resources displayed / displayed on the user terminal. Putting the position ranking of the teaching resources with the same resource tags as the teaching resources included in the adjusted resource set at the back or reducing the number can effectively reduce the number of teaching resources that the user is not interested in, thereby making it more likely that the user will see the teaching resources of interest.

[0102] S522, if the operation type is an observation operation or a selection operation, then the teaching resources included in the pre-display area and having the same resource label as the teaching resources included in the adjusted resource set are sorted in advance in the pre-display area, or a preset incremental amount of teaching resources are added from the teaching resource library into the pre-display area.

[0103] It can be understood that if the operation type is an observation operation or a selection operation, it means that the user is interested in the teaching resources displayed on the user terminal. The method of advancing the position sorting of the teaching resources included in the pre-display area and having the same resource tag as the teaching resources included in the adjusted resource set in the pre-display area can be to subtract the preset sorting value from the position sorting corresponding to the teaching resources, or to subtract the ratio of the number of times the resource tag corresponding to the teaching resource appears in the pre-display area to the sum of the number of resource tags corresponding to other teaching resources in the pre-display area from the position sorting corresponding to the teaching resources, but is not limited to this. Advancing the position sorting of the teaching resources included in the pre-display area and having the same resource tag as the teaching resources included in the adjusted resource set, or adding preset incremental teaching resources from the teaching resource library into the pre-display area can effectively increase the probability of users seeing the teaching resources of interest.

[0104] S600: Modify a user tag set based on a first resource recommendation set and a second resource recommendation set.

[0105] It can be understood that the method of modifying the user tag set based on the first resource recommendation set and the second resource recommendation set can be to determine whether the resource tag in the second resource recommendation set exists in the first resource recommendation set, or to determine the number of times the resource tag appears in the second resource recommendation set and the first resource recommendation set, etc., but is not limited thereto. Modifying the user tag set based on the first resource recommendation set and the second resource recommendation set can optimize the user experience, so that the teaching resources that the user is interested in can be directly pushed when the user logs in next time.

[0106] In one possible implementation, see Figure 5 S600, modifying the user tag set based on the first resource recommendation set and the second resource recommendation set, including:

[0107] S610, receiving a termination signal; wherein the termination signal is a signal sent by the user terminal when the user logs out.

[0108] It is understood that the termination signal may be received by receiving a signal sent by an APP when the user exits the APP that is connected to the teaching resource library, or by receiving a signal sent by a user terminal when the user locks the screen or shuts down the device, but is not limited thereto. Receiving the termination signal can provide a basis for subsequent steps.

[0109] S620, respectively add up various identical resource tags in the pre-display area of ​​the second resource recommendation set to obtain a second resource table; wherein the second resource table includes a plurality of resource tags and quantities corresponding to each resource tag.

[0110] It is understandable that the second resource table can be a database table or an Excel table, but is not limited thereto. The second resource table can be obtained by adding up the various identical resource tags in the pre-display area of ​​the second resource recommendation set to provide a basis for subsequent steps.

[0111] Exemplarily, assuming that the pre-display area of ​​the second resource recommendation set includes resource tags (A, B, C, B, C, A, A, B), the second resource table is (A: 3, B: 3, C: 2).

[0112] S630: Add up various identical resource tags in the first resource recommendation set to obtain a first resource table; wherein the first resource table includes a plurality of resource tags and quantities corresponding to each resource tag.

[0113] It is understandable that the first resource table can be a database table or an Excel table, but is not limited thereto. Adding up various identical resource tags in the first resource recommendation set to obtain the first resource table can provide a basis for subsequent steps.

[0114] Exemplarily, assuming that the pre-display area of ​​the first resource recommendation set includes resource tags (A, C, C, B, C, A, B, B), the first resource table is (A: 2, B: 3, C: 3).

[0115] S640: Search each resource tag in the second resource table in the first resource table respectively. If a resource tag in the second resource table does not appear in the first resource table, add the resource tag that does not appear in the first resource table into the user tag set.

[0116] It is understandable that if there is a resource tag in the second resource table that does not appear in the first resource table, it means that the user has found the teaching resources that he is interested in during this use. Adding resource tags that do not appear in the first resource table to the user tag set can optimize the user experience, so that the teaching resources that the user is interested in can be directly pushed when the user logs in next time.

[0117] S650, if a resource tag appears in both the first resource table and the second resource table, and the number of the resource tag in the second resource table is greater than the number of the resource tag in the first resource table, then the weight corresponding to the resource tag in the user tag set is increased.

[0118] It can be understood that if a resource tag appears in both the first resource table and the second resource table, and the number corresponding to the resource tag in the second resource table is greater than the number corresponding to the resource tag in the first resource table, it means that the user is more interested in the teaching resources corresponding to the resource tag during this use, and the number of pushes needs to be increased. Increasing the weight corresponding to the resource tag in the user tag set can effectively increase the number of pushes of this type of teaching resources, ensuring that the teaching resources pushed to the user are in line with the user's interests and hobbies. The way to increase the weight corresponding to the resource tag in the user tag set can be to increase the weight corresponding to the resource tag by a preset value, or to add the weight corresponding to the resource tag to the sum of the number of the resource tag in the first resource table and the second resource table and the ratio of the sum of the number of other resource tags in the first resource table and the second resource table, etc., but is not limited to this.

[0119] S660, if a resource tag appears in both the first resource table and the second resource table, and the number corresponding to the resource tag in the second resource table is less than the number corresponding to the resource tag in the first resource table, then reduce the weight corresponding to the resource tag in the user tag set.

[0120] It can be understood that if a resource tag appears in both the first resource table and the second resource table, and the number corresponding to the resource tag in the second resource table is less than the number corresponding to the resource tag in the first resource table, it means that the user's interest in the teaching resources corresponding to the resource tag has decreased during this use, and the number of pushes needs to be reduced. Reducing the weight corresponding to the resource tag in the user tag set can effectively reduce the number of pushes of this type of teaching resources, ensuring that the teaching resources pushed to the user are in line with the user's interests and hobbies. The method of reducing the weight corresponding to the resource tag in the user tag set can be to reduce the weight corresponding to the resource tag by a preset value, or to reduce the weight corresponding to the resource tag by the ratio of the sum of the number of the resource tag in the first resource table and the second resource table to the sum of the number of other resource tags in the first resource table and the second resource table, etc., but is not limited to this.

[0121] 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.

[0122] Corresponding to the above embodiment of a method for managing an online teaching resource library based on big data, the embodiment of the present application also provides a management system for an online teaching resource library based on big data, and each unit of the system can implement each step of a method for managing an online teaching resource library based on big data. Figure 6A structural block diagram of a big data online teaching resource library management system provided in an embodiment of the present application is shown. For the sake of ease of explanation, only the parts related to the embodiment of the present application are shown.

[0123] Reference Figure 6 , the system comprises:

[0124] A login unit, used to obtain login information, and obtain a user tag set based on the login information; wherein each of the login information corresponds to a user, and the login information includes account information and password information; the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one of the resource tags;

[0125] A resource push unit, the resource push unit includes a first analysis module, a collection module, a second analysis module and a push module; wherein the first analysis module is used to obtain a first resource recommendation set based on the user tag set, wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to send and display on the user terminal; the collection module is used to obtain a trigger signal and obtain an operation state based on the trigger signal, wherein the trigger signal is a signal sent when the user touches the screen of the user terminal, and the operation state reflects the user's operation on the user terminal; the second analysis module is used to obtain a second resource recommendation set based on the operation state and the first resource recommendation set, wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to send and display on the user terminal; the push module is used to push the first resource recommendation set or the second resource recommendation set to the user terminal;

[0126] A feedback unit is used to modify the user tag set based on the first resource recommendation set and the second resource recommendation set.

[0127] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0128] Those skilled in the art 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 system 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.

[0129] The present application also provides a big data-based online teaching resource library management device. Figure 7 This is a schematic diagram of a structure of a big data online teaching resource library management device provided in one embodiment of the present application. Figure 7 As shown, a big data-based online teaching resource library management device of this embodiment includes: at least one processor 60 ( Figure 7 Only one is shown), at least one memory 61 ( Figure 7 Only one is shown in the figure) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the device for managing a big data online teaching resource library implements the steps in any one of the above-mentioned embodiments of the method for managing a big data online teaching resource library, or the management system for managing a big data online teaching resource library implements the functions of each unit in the above-mentioned method embodiments.

[0130] Exemplarily, 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 big data-based online teaching resource library management device 6.

[0131] The big data-based online teaching resource library management device 6 can be a computing device such as a desktop computer, a notebook, a handheld computer, and a cloud server. The big data-based online teaching resource library management device 6 can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Figure 7It is only an example of a management device for an online teaching resource library based on big data, and does not constitute a limitation on a management device for an online teaching resource library based on big data. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0132] The processor 60 may be a central processing unit (CPU), or 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.

[0133] In some embodiments, the memory 61 may be an internal storage unit of the big data online teaching resource library management device 6, such as a hard disk or memory based on the big data online teaching resource library management device 6. In other embodiments, the memory 61 may also be an external storage device based on the big data online teaching resource library management device 6, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the big data online teaching resource library management device 6. Further, the memory 61 may also include both the internal storage unit based on the big data online teaching resource library management device 6 and the external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data and other programs, such as the program code of the computer program, etc. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0134] 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 steps in any of the above method embodiments are implemented.

[0135] An embodiment of the present application provides a computer program product. When the computer program product runs on a big data online teaching resource library management device, the big data online teaching resource library management device implements the steps in any of the above-mentioned method embodiments.

[0136] 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, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. 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 at least include: any entity or device that can carry the computer program code to a big data online teaching resource library management device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0137] 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.

[0138] 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.

[0139] In the embodiments provided in the present application, it should be understood that the disclosed management system and device based on big data online teaching resource library can be implemented in other ways. For example, the above-described embodiment of a management system based on big data online teaching resource library is 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.

[0140] The units described as separate components may or may not be physically separated, and the components shown 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 solution of this embodiment.

[0141] 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. A method for managing an online teaching resource library based on big data, characterized in that: include: Obtaining login information; wherein each of the login information corresponds to a user, and the login information includes account information and password information; A user tag set is obtained based on the login information; wherein the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one of the resource tags; Obtaining a first resource recommendation set based on the user tag set; wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to send and display on a user terminal; Acquire a trigger signal, and obtain an operation state based on the trigger signal; wherein the trigger signal is a signal sent when a user touches the screen of the user terminal, and the operation state reflects the user's operation on the user terminal; Obtaining a second resource recommendation set based on the operation state and the first resource recommendation set; wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to be sent and displayed on the user terminal; Modify the user tag set based on the first resource recommendation set and the second resource recommendation set; The obtaining of a first resource recommendation set based on the user tag set includes: The preset push quantity is divided by the total weight to obtain the push proportion; wherein the total weight is the sum of the weights corresponding to each user tag in the user tag set; The values ​​obtained by multiplying the weight corresponding to each user tag in the user tag set by the push proportion are rounded down to obtain a plurality of push values ​​corresponding to each user tag; In the teaching resource library, selecting the teaching resources corresponding to the resource tags with the same number of push values ​​as the user tag and the same number as the user tag, and confirming all the selected teaching resources as the first resource recommendation set; The obtaining the operation state based on the trigger signal comprises: When the trigger signal is received, the position of the contact point is confirmed as the starting position, and timing is started; wherein the contact point is the position where the user touches the screen of the user terminal; When the trigger signal disappears, the position of the contact point is confirmed as the end position, and the timing is ended; The straight-line distance between the starting point and the end point is determined as the trigger distance, and the time period recorded from the start of timing to the end of timing is determined as the trigger duration; Obtaining the operation state based on the trigger distance and the trigger duration; The obtaining the operation state based on the trigger distance and the trigger duration includes: Determine whether the trigger distance is greater than a preset distance and whether the trigger duration is greater than a preset duration; wherein the trigger distance is the straight-line distance between the starting position and the end position, and the trigger duration is the duration from when the trigger signal is received to when the trigger signal disappears; If the trigger distance is greater than the preset distance and the trigger duration is less than the preset duration, the user's operation from the time when the trigger signal is obtained to the time when the trigger signal disappears is confirmed as a sliding operation; If the trigger duration is longer than the preset duration, or the trigger distance is greater than the preset distance and the trigger duration is longer than the preset duration, the user's operation from the time the trigger signal is acquired to the time the trigger signal disappears is confirmed as an observation operation; If the trigger distance is less than the preset distance and the trigger duration is less than the preset duration, the user's operation from the time when the trigger signal is obtained to the time when the trigger signal disappears is confirmed as a selection operation; confirming one operation type among the sliding operation, the observing operation and the selecting operation as the operation state; The obtaining a second resource recommendation set based on the operation state and the first resource recommendation set includes: Based on the operation state, an adjustment resource set is obtained; wherein the adjustment resource set includes the operation type reflected by the operation state and at least one of the teaching resources and the resource label corresponding to the teaching resource; Obtaining the second resource recommendation set based on the adjusted resource set and the first resource recommendation set; The obtaining the second resource recommendation set based on the adjusted resource set and the first resource recommendation set includes: Determine the operation type in the adjustment resource set, if the operation type is a sliding operation, then sort the teaching resources included in the pre-display area, and the teaching resources with the same resource tags as the teaching resources included in the adjustment resource set, to the back of the order in the pre-display area, or reduce the number of teaching resources included in the pre-display area, and the teaching resources with the same resource tags as the teaching resources included in the adjustment resource set; wherein the pre-display area includes the teaching resources in the first resource recommendation set or the second resource recommendation set that have not been displayed / displayed on the display screen of the user terminal; If the operation type is the observation operation or the selection operation, the teaching resources included in the pre-display area and the teaching resources with the same resource tags as the teaching resources included in the adjustment resource set are arranged in advance in the pre-display area, or the teaching resources with a preset increment are added from the teaching resource library into the pre-display area; The modifying the user tag set based on the first resource recommendation set and the second resource recommendation set includes: Receiving a termination signal; wherein the termination signal is a signal sent by the user terminal when the user logs out; Counting the number of various identical resource tags in the pre-display area of ​​the second resource recommendation set respectively to obtain a second resource table; wherein the second resource table includes a plurality of the resource tags and the number corresponding to each of the resource tags; Calculate the number of different identical resource tags in the first resource recommendation set respectively to obtain a first resource table; wherein the first resource table includes a plurality of the resource tags and the number corresponding to each of the resource tags; Retrieve each resource tag in the second resource table from the first resource table respectively, and if a resource tag in the second resource table does not appear in the first resource table, add the resource tag that does not appear in the first resource table into the user tag set; If a resource tag appears in both the first resource table and the second resource table, and the number of the resource tag in the second resource table is greater than the number of the resource tag in the first resource table, the weight corresponding to the resource tag in the user tag set is increased; If a resource tag appears in both the first resource table and the second resource table, and the number corresponding to the resource tag in the second resource table is less than the number corresponding to the resource tag in the first resource table, the weight corresponding to the resource tag in the user tag set is reduced.

2. A method for managing an online teaching resource library based on big data as claimed in claim 1, characterized in that: The obtaining of a user tag set based on the login information includes: Querying the account information in a user database to obtain a verification password corresponding to the account information; Comparing the password information with the verification password, if the password information is completely consistent with the verification password, confirming at least one of the user tags corresponding to the account information in the user database and the tag weight corresponding to the user tag as the user tag set; If the password information is not completely consistent with the verification password, the user tag set with empty content is obtained.

3. A method for managing an online teaching resource library based on big data as claimed in claim 1, characterized in that: The obtaining of an adjustment resource set based on the operation state includes: Determine the operation type reflected by the operation state, and if the operation type reflected by the operation state is the sliding operation, confirm the sliding operation and the resource label corresponding to the teaching resource displayed / displayed on the display screen of the user terminal from the start of the sliding operation to the end of the sliding operation as the adjustment resource set; If the operation type reflected by the operation status is the observation operation, the observation operation and the resource label corresponding to the teaching resource displayed on the display screen of the user terminal from the start of the observation operation to the end of the observation operation are confirmed as the adjustment resource set; If the operation type reflected by the operation status is the selection operation, the selection operation and the resource tag corresponding to the teaching resource corresponding to the selection operation are confirmed as the adjustment resource set.

4. A big data-based online teaching resource library management system, characterized in that: For implementing the method for managing an online teaching resource library based on big data according to any one of claims 1 to 3, the system comprises: A login unit, used to obtain login information, and obtain a user tag set based on the login information; wherein each of the login information corresponds to a user, and the login information includes account information and password information; the user tag set includes at least one user tag and a tag weight corresponding to the user tag, the user tag corresponds to a resource tag, and the teaching resource corresponds to at least one of the resource tags; A resource push unit, the resource push unit includes a first analysis module, a collection module, a second analysis module and a push module; wherein the first analysis module is used to obtain a first resource recommendation set based on the user tag set, wherein the first resource recommendation set includes at least one teaching resource, and the first resource recommendation set is used to send and display on the user terminal; the collection module is used to obtain a trigger signal and obtain an operation state based on the trigger signal, wherein the trigger signal is a signal sent when the user touches the screen of the user terminal, and the operation state reflects the user's operation on the user terminal; the second analysis module is used to obtain a second resource recommendation set based on the operation state and the first resource recommendation set, wherein the second resource recommendation set includes at least one teaching resource, and the second resource recommendation set is used to send and display on the user terminal; the push module is used to push the first resource recommendation set or the second resource recommendation set to the user terminal; A feedback unit is used to modify the user tag set based on the first resource recommendation set and the second resource recommendation set.

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