CN110111611B - Information processing method, device, medium and electronic equipment - Google Patents
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Abstract
The invention provides an information processing method. The method comprises the following steps: acquiring behavior data of a user about a learning course; determining a target knowledge point about the learning course according to the behavior data, and acquiring the position information of the target knowledge point in the learning course; acquiring detailed explanation information about the target knowledge point; a first target location is determined based on the location information and the refined interpretation information is associated to the first target location. According to the scheme, the behavior data of multiple users in the learning course is collected, the public doubt point and the public difficulty point about the learning course are determined based on the behavior data of the multiple users, and the corresponding detailed explanation information is further associated to the target position. Therefore, subsequent users do not need to repeat operations such as query marking and the like at public query points and public query points, and can conveniently acquire detailed explanation information related to the target position. Thereby improving the learning efficiency of course learning.
Description
Technical Field
The present invention relates to the field of data processing technology, and more particularly, to an information processing method, an information processing apparatus, and a computer-readable medium and an electronic device that implement the information processing method.
Background
This section is intended to provide a background or context to the invention that is recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
With the rapid development of scientific technology, people have an increasingly strong desire to learn knowledge. Thus, the development of online education platforms in the form of "internet + education" has been in force. The online education platform provides online courses, thereby providing the public with an opportunity to learn knowledge through the network. Wherein, the user (i.e. the student who learns the course) inevitably encounters questions during the learning process.
In the related art, for the case that a teacher giving lessons via recorded videos or courseware, since a user cannot directly interact with the teacher, when the user has a question or encounters difficulty, the user may think about the problem by pausing the course playing, and may also solve the above-mentioned question or study the difficulty or evaluate the course by recording notes or leaving a message for discussion (refer to fig. 1).
In the method provided by the prior art, the question points and the question points put forward by the users are not counted, and the users who subsequently learn the course (which can be called as 'subsequent users') cannot know the question knowledge points accumulated by the previous learning users in the learning process, the problems encountered by the previous learning users and the like. That is, when the subsequent user encounters the same question, the question needs to be raised again. Meanwhile, the teacher may be asked repeatedly for the same question.
Therefore, the information processing method in the prior art has the defect of low learning efficiency.
Disclosure of Invention
For this reason, an improved information processing method is highly required to effectively improve the learning efficiency as a whole.
In this context, embodiments of the present invention are intended to provide an information processing method, an information processing apparatus, a computer-readable medium, and an electronic device.
In a first aspect of embodiments of the present invention, there is provided an information processing method including:
acquiring behavior data of a user about a learning course;
determining a target knowledge point of the learning course according to the behavior data, and acquiring the position information of the target knowledge point in the learning course;
acquiring detailed explanation information about the target knowledge point;
a first target location is determined based on the location information and the refined interpretation information is associated to the first target location.
In some embodiments of the present invention, based on the foregoing solution, the acquiring behavior data of the user about the learning course includes:
in the playing process of the learning course, behavior data of the user on the learning course is obtained, and the behavior data comprises pause duration, pause position and marked content.
In some embodiments of the present invention, based on the foregoing solution, the determining, according to the behavior data, a target knowledge point about the learning course and acquiring location information of the target knowledge point in the learning course include:
clustering the behavior data and the learning course identification, and determining a plurality of knowledge point clusters related to the learning course;
determining at least one knowledge point cluster meeting preset conditions in the plurality of knowledge point clusters as a target knowledge point of the learning course, and acquiring the position information of the target knowledge point in the learning course.
In some embodiments of the present invention, based on the foregoing solution, the obtaining of refined interpretation information about the target knowledge point includes:
extracting keywords from the marked content, and determining the keywords as the keywords corresponding to the target knowledge point;
and acquiring detailed explanation information about the target knowledge point according to the target knowledge point and the keyword corresponding to the target knowledge point.
In some embodiments of the present invention, based on the foregoing solution, the acquiring behavior data of the user about the learning course includes:
receiving data sent by a first data interface, and acquiring behavior data of the user about the learning course;
the obtaining of the refined interpretation information about the target knowledge point comprises:
and sending the target knowledge point and the keywords corresponding to the target knowledge point to a second data interface, and receiving detailed explanation information which is returned by the second data interface and is about the target knowledge point.
In some embodiments of the present invention, based on the foregoing solution, the determining a first target location based on the location information and associating the refined interpretation information to the first target location includes:
determining a hyperlink about the target knowledge point according to the refined interpretation information;
and setting the hyperlink at the first target position so that a user can obtain the refined interpretation information according to the hyperlink.
In some embodiments of the present invention, based on the foregoing scheme, the associating the refined interpretation information to the first target location includes:
and setting an identifier at the first target position so that a user clicks the identifier to acquire the detailed explanation information.
In a second aspect of embodiments of the present invention, there is provided an information processing apparatus comprising:
the behavior data acquisition module is used for acquiring behavior data of the user about the learning course;
the target knowledge point determining module is used for determining a target knowledge point related to the learning course according to the behavior data and acquiring the position information of the target knowledge point in the learning course;
the interpretation information acquisition module is used for acquiring detailed interpretation information about the target knowledge point;
and the information association module is used for determining a first target position based on the position information and associating the detailed explanation information to the first target position.
In a third aspect of embodiments of the present invention, there is provided a computer-readable medium on which a computer program is stored, the program, when executed by a processor, implementing the information processing method as described in the first aspect above.
In a fourth aspect of embodiments of the present invention, there is provided an electronic apparatus comprising: a processor and a memory, the memory storing executable instructions, the processor being configured to invoke the memory stored executable instructions to perform the information processing method as described in the above first aspect.
According to the embodiment provided by the invention, on one hand, behavior data of multiple users in a learning course is collected, and common question points about the learning course are determined based on the behavior data of the multiple users. Therefore, subsequent users do not need to repeatedly perform operations such as question marking and the like at the public question points and the public question points. Therefore, the learning efficiency of course learning is improved.
On the other hand, the target knowledge point of the learning course is determined based on the public question points and the public difficulty points, the position information of the target knowledge point in the learning course is obtained, further, the detailed explanation information about the target knowledge point is obtained, and the detailed explanation information is related to the target position based on the position information. Thereby enabling the user to conveniently obtain the public question points, the public difficulty points and the detailed interpretation information associated to the target position. Therefore, the learning efficiency of course learning is further improved. Meanwhile, the teacher is prevented from repeatedly answering the same question.
Drawings
The above and other objects, features and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description, which proceeds with reference to the accompanying drawings. Several embodiments of the present invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which:
fig. 1 is a schematic view showing an information processing method provided according to the background of the invention;
FIG. 2 schematically shows a flow diagram of an information processing method according to an embodiment of the invention;
FIG. 3 schematically illustrates a learning lesson interface diagram according to an embodiment of the invention;
FIG. 4 schematically shows a flow diagram of a method of determination of a target knowledge point according to an embodiment of the invention;
FIG. 5 schematically shows a flowchart of a determination method of refining interpretation information according to an embodiment of the present invention;
fig. 6 schematically shows a flowchart of a determination method of detailed interpretation information according to another embodiment of the present invention;
fig. 7 schematically shows a structural diagram of an information processing apparatus according to an embodiment of the present invention;
FIG. 8 schematically shows a schematic view of a computer-readable medium according to an example embodiment of the invention; and the number of the first and second groups,
fig. 9 schematically shows a block diagram of an electronic device according to an exemplary embodiment of the invention.
In the drawings, like or corresponding reference characters designate like or corresponding parts.
Detailed Description
The principles and spirit of the present invention will be described with reference to several exemplary embodiments. It is understood that these embodiments are given only to enable those skilled in the art to better understand and to implement the present invention, and do not limit the scope of the present invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, or computer program product. Thus, the present invention may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
According to an embodiment of the present invention, an information processing method, an information processing apparatus, a computer-readable medium, and an electronic device are provided.
In this context, it is to be understood that reference to a "user" is a user of an online education platform, and may specifically be a student who is learning a course.
Furthermore, the number of any elements in the drawings is intended to be illustrative and not restrictive, and any nomenclature is used for distinction only and not for any restrictive meaning.
The principles and spirit of the present invention are explained in detail below with reference to several representative embodiments of the invention.
Summary of The Invention
The inventor finds that, in the information processing method provided in the prior art, on one hand, since the user marks or raises questions about the doubts and doubts of the user alone without counting the public doubts and public doubts of a plurality of users, the follow-up user cannot know the doubts and the problems which are accumulated in the learning process of the user who learns in advance. That is, when the subsequent user encounters the same question, the subsequent user needs to ask the question again and wait for the teacher to answer the question, resulting in low overall learning efficiency.
Based on the above, the basic idea of the invention is to collect behavior data of multiple users in a learning course, and determine a public questioning point and a public questioning point of the multiple users about the learning course based on the behavior data of the multiple users, and the subsequent users do not need to repeat operations such as questioning marking and the like at the public questioning point and the public questioning point. Thus, the learning efficiency of the user is improved as a whole.
In addition, a target knowledge point of the learning course is determined based on the public question points and the public difficulty points, position information of the target knowledge point in the learning course is obtained, further, detailed explanation information about the target knowledge point is obtained, and the detailed explanation information is related to the target position based on the position information. Therefore, the user can conveniently acquire the public questioning points, the public questioning points and the detailed explanation information associated to the target position. Therefore, the learning efficiency of course learning is further improved. Meanwhile, repeated answering of the same question by a teacher is avoided.
Having described the general principles of the invention, various non-limiting embodiments of the invention are described in detail below.
Exemplary method
An information processing method according to an exemplary embodiment of the present invention is described below with reference to any one of fig. 2 to 6 in conjunction with the application scenarios described above.
Fig. 2 schematically shows a flow diagram of an information processing method according to an embodiment of the present invention, and with reference to fig. 2, the method includes the steps of:
step S21, acquiring the behavior data of the user about the learning course;
step S22, determining a target knowledge point related to the learning course according to the behavior data, and acquiring the position information of the target knowledge point in the learning course;
step S23, acquiring the detailed explanation information about the target knowledge point; and the number of the first and second groups,
step S24, determining a first target location based on the location information, and associating the refined interpretation information to the first target location.
Implementation details of the various steps shown in FIG. 2 are set forth below:
in an exemplary embodiment, one specific way to obtain the behavior data of the user about the learning course in step S21 may be: in the playing process of the learning course, behavior data of a plurality of users for the learning course is obtained, and the behavior data can comprise pause duration, pause position and marked content.
Illustratively, a dotting timer is set during the playing process of the learning course of the audio-video class. And starting the dotting timer at the playing starting point of the learning course, and determining the pause position and pause duration of the user in the learning process through the dotting timer.
For example, fig. 3 schematically shows a learning course interface diagram according to an embodiment of the present invention, and specifically, a pause position and a pause duration in the behavior data may be described. Starting a dotting timer 32 at the same time of a playing starting point of the learning course Photoshop precise talking 31, and determining a pause position and pause duration implemented by a user in the process of learning the Photoshop precise talking 31 through the dotting timer 32.
Referring to fig. 3, when a user a encounters a question point during the playing of the learning course PhotoShop lecture 31, the punctuation timer 32 determines that the pause position of the user a is at a1 of the PhotoShop lecture 31, and the pause duration is s 1. The user B also encounters a question point in the playing process of the learning course "PhotoShop lecture" 31, the pause position of the user B is determined to be B1 of the "PhotoShop lecture" 31 through the dotting timer 32, and the pause duration is s 2.
For example, the content of the tag in the behavior data may be: the course content marked by the user during the learning process, or the annotation content and online note performed on the learning course by the user during the learning process, and more specifically, the marked content in the behavior data may also be: the user highlights the marked curriculum contents during the pause process, for example, the user bold-faced some piece of contents. The content of the mark in the behavior data may also be: and during the pause, the user annotates the content of the learning course, notes on line, and the like, wherein the notes are made by the user, such as the notes of the teacher and the like.
In an exemplary embodiment, fig. 4 schematically shows a flowchart of a method for determining a target knowledge point according to an embodiment of the present invention, and in particular, may be taken as a specific implementation manner of step S22. Referring to fig. 4, the method includes step S41 and step S42.
In step S41, the behavior data and the learning course identifier are clustered, and a plurality of knowledge point clusters about the learning course are determined.
In an exemplary embodiment, during the process of collecting the behavior data, the account id of the user who generated the behavior data is obtained at the same time, so as to distinguish which account different users come from. And simultaneously, acquiring an action object, namely course identification, aimed at when the behavior data occurs. The course identifier may be specifically determined according to composition information of a learning course, for example: learning course a includes { s1…si…sNJ, lesson saving, the course identification can include "a" and "si"; learning course b includes only one course, its course identification may include "b" and so on.
In an exemplary embodiment, the behavior data with account number identification and course identification of multiple users are clustered, and a plurality of knowledge point clusters about each course participating in clustering can be determined according to a clustering result.
Still taking the learning course "PhotoShop essence" 31 shown in fig. 3 as an example, the knowledge point clusters s' and s "related to the learning course are determined according to the clustering result. Each knowledge point cluster is the curriculum content corresponding to the coincidence part of the pause time periods of at least two users. For example, the pause starting point of the user B is B1 of PhotoShop lecture 31, the pause ending point is B2, the pause duration is s2, the pause starting point of the user C is C1 of PhotoShop lecture 31, the pause ending point is C2, and the pause duration is s 3. And determining that the superposition part of the pause periods of the two parts is from the C1 moment to the B2 moment of Photoshop accurate presentation 31 through a clustering algorithm, and recording the course contents corresponding to the C1 moment to the B2 moment as the knowledge point cluster s'. Similarly, the course contents corresponding to the time point B1 to the time point a2 are recorded as the knowledge point cluster s'. The overlapped parts of the pause time periods of different users are used as knowledge point clusters, so that the statistics of common questioning points or common questioning points of a plurality of users about course learning is facilitated. On the other hand, the teaching teacher can grasp the key point of detailed explanation on the whole according to the common difficulty or the common question. Meanwhile, the teaching teacher is helped to position common difficult points and doubts encountered by multiple users in the learning process, so that courseware can be updated and optimized in a targeted manner, and interactivity is increased to provide personalized teaching service.
In step S42, at least one knowledge point cluster satisfying a preset condition among the plurality of knowledge point clusters is determined as a target knowledge point regarding the learning course, and position information of the target knowledge point in the learning course is acquired.
In an exemplary embodiment, after determining a plurality of knowledge point clusters for each learning course participating in the clustering, a target knowledge point for each learning course is determined from the plurality of knowledge point clusters. Still taking fig. 3 as an example to explain the method for determining a target knowledge point, regarding any knowledge point cluster (taking the knowledge point cluster s ″ as an example) of "PhotoShop lecture" 31, the number of pause periods corresponding to each knowledge point cluster s ″ is counted, and when the number is greater than a preset threshold, it is stated that more users have a question about the course content corresponding to the time from C1 to B2 or think that the content is a doubt, and further, the knowledge point cluster meeting the preset condition is taken as the target knowledge point of the course information.
In an exemplary embodiment, if the knowledge point cluster s "satisfies the preset condition, the knowledge point cluster s" may be used as a target knowledge point of the learning course "PhotoShop speeches" 31. And can obtain the position information of the knowledge point cluster s' in the learning course, including: the starting time C1 of the knowledge point cluster s "and the ending time B2 of the knowledge point cluster s".
The position information may be playing time information of the learning course, or may be course content, for example, the content of the section 2 on the page 2 of the PPT of PhotoShop lecture.
In an exemplary embodiment, one achievable way to obtain the refined interpretation information is: the course identification and the corresponding target knowledge point (for example, in a PPT master training course, in the course of the course 8, the 9 th-12 th minute is the transparent layer) are sent to the teacher, so that the teacher can make corresponding knowledge supplement or detailed explanation (namely detailed interpretation information) on the target knowledge point, and the target knowledge point can be deeply understood by the user who has a question about the target knowledge point or thinks that the target knowledge point is difficult to understand according to the detailed interpretation information added by the teacher.
In an exemplary embodiment, with continued reference to FIG. 2, refined interpretation information about the target knowledge point is obtained in step S23. In step S23, one specific implementation manner is: since the user mark content can more closely reflect the problems encountered in the course learning process, the detailed explanation information can be obtained according to the mark content, the target knowledge point and the course identification. Wherein, as before: the marked content in the behavior data may be: the user-marked course content in the learning process, or the comment content and online note performed on the learning course by the user in the learning process, and more specifically, the marked content in the behavior data may be: the user can highlight the marked course content during the pause process, or the user can annotate the learning course content, take notes on line and the like during the pause process.
Exemplarily, fig. 5 schematically illustrates a flowchart of a method for determining detailed explanatory information according to an embodiment of the present invention, which may be specifically taken as another specific implementation manner of step S23. Referring to fig. 5, the method includes:
step S51, extracting keywords from the marked content, and determining the keywords as the keywords corresponding to the target knowledge points; and step S52, acquiring detailed explanation information about the target knowledge point according to the target knowledge point and the keyword corresponding to the target knowledge point.
In an exemplary embodiment, the course content heavily marked by the user during the learning process/pause process, or the annotation content and online note of the user for the learning course during the learning process/pause process, that is, the keyword extraction is performed on the user reflection content related to the target knowledge point. For example: for course identification: text 8 of PPT master training camp "transparent picture layer" and target knowledge points are: and 9 th to 12 th minutes of the 'transparent layer', acquiring the marked content of the user during the pause of the 9 th to 12 th minutes, and extracting the keywords of the marked content as follows: transparency, coverage, delamination. Further, the detailed explanation information of the target knowledge point can be determined according to the course identification, the target knowledge point and the keyword.
Exemplarily, fig. 6 schematically shows a flow chart of a method of determining detailed interpretation information according to another embodiment of the present invention. Referring to fig. 6, the method includes:
step S61, receiving data sent by a first data interface, and acquiring behavior data of the user about the learning course; and step S62, sending the target knowledge point and the keywords corresponding to the target knowledge point to a second data interface, and receiving the detailed explanation information about the target knowledge point returned by the second data interface.
Illustratively, the first data interface is: and the course platform is used for data communication with the users who study the courses. The second data interface is: the interface for data communication between the course platform and the teacher for teaching or the interface for data communication between the course platform and the preset database.
Illustratively, the course identifier, the target knowledge point and the keyword are sent to the second data interface, and the teacher supplements, refines and adjusts the learning course according to the received course identifier, the target knowledge point and the keyword, so as to form refined explanation information for the target knowledge point. The keywords are beneficial for teachers to more accurately understand the question points and the doubtful points of the users, and further, detailed explanation information about the target knowledge points can be efficiently and accurately made.
Illustratively, the detailed explanation information fed back by the teacher is received through the second data interface, wherein the detailed explanation information is helpful for the user to understand the target knowledge point more deeply, and the learning quality is improved.
In an exemplary embodiment, with continued reference to fig. 2, after determining the target knowledge point, the location information of the target knowledge point in the learning course, and acquiring the refined interpretation information about the target knowledge point, in step S24, a first target location is determined based on the location information and the refined interpretation information is associated to the first target location. Compared with the problem that the user proposes in the comment area in the related prior art, the technical scheme provided by the embodiment associates the detailed explanation information to the target position corresponding to the target knowledge point, so that the user can learn the detailed explanation information in the learning process without searching the comment area to obtain the related solution. Therefore, the technical scheme provided by the embodiment is beneficial to improving the learning efficiency of the user on the whole and saving the learning time.
In an exemplary embodiment, the previous knowledge point cluster s "is used as a target knowledge point of the learning course PhotoShop lecture 31, and the corresponding position information includes: the start time C1 of the knowledge point cluster s "and the end time B2 of the knowledge point cluster s". In addition, if the user performs the marking operation during the pause from the time C1 to the time B2, the position information may further include: the position is marked.
For example, the specific implementation manner of determining the first target position based on the position information may be to determine the mark position of the user as the first target position, may also determine the starting position corresponding to the target knowledge point as the first target position, and may also determine the ending position corresponding to the target knowledge point as the first target position.
Illustratively, the first target position may also be specified by the teacher based on the position information of the target knowledge point in the learning course. Thus, the online education platform receives the first target position designated by the teacher and the detailed interpretation information supplemented by the teacher, and further, the online education platform associates the detailed interpretation information with the first target position.
For example, in order to keep the page display of the learning course neat, the above detailed interpretation information may be made as a hyperlink on the target knowledge point. Further, in order to facilitate the user to obtain the refined explanation content, the hyperlink is set at the first target position, so that the user can click the hyperlink to obtain the refined explanation information.
For example, an identifier may be further set at the first target position (for example, the first target position is highlighted or a highlighted identifier such as a triangular symbol is set) to remind the user that the refining interpretation information has been added here, and the user may click the identifier to obtain the refining interpretation information according to the user's requirement.
Compared with the prior art in which the lecture teacher gives interactive lectures in a live broadcasting mode, the user can ask questions in a live broadcasting comment area in the live broadcasting process. Although real-time interaction is realized, the proposed questions and the answers of the teachers are only displayed in the comment area and are not associated with the target knowledge points. Subsequent users do not readily acquire the questions asked or/and the teacher's answers. In the technical scheme, the target knowledge point is associated with the detailed explanation information, so that the subsequent user can conveniently and quickly acquire the associated content without searching the comment area to acquire the relevant answer, the learning time of the subsequent user is saved, and the learning efficiency is integrally improved.
Exemplary devices
Having described the method of the exemplary embodiment of the present invention, next, an information processing apparatus of an exemplary embodiment of the present invention is explained with reference to fig. 9.
Fig. 7 schematically shows a configuration diagram of an information processing apparatus according to an embodiment of the present invention. Referring to fig. 7, an information processing apparatus 700 includes: a behavior data acquisition module 701, a target knowledge point determination module 702, an interpretation information acquisition module 703 and an information association module 704.
The behavior data acquiring module 701 is configured to acquire behavior data of a user about a learning course; the target knowledge point determining module 702 is configured to determine a target knowledge point about the learning course according to the behavior data, and obtain location information of the target knowledge point in the learning course; the above-mentioned explanation information obtaining module 703 is configured to obtain detailed explanation information about the target knowledge point; and the information association module 704 is configured to determine a first target location based on the location information, and associate the refined interpretation information with the first target location.
In some embodiments of the present invention, based on the foregoing scheme, the behavior data obtaining module 701 is specifically configured to: in the playing process of the learning course, behavior data of the user on the learning course is obtained, and the behavior data comprises pause duration, pause position and marked content.
In some embodiments of the present invention, based on the foregoing solution, the target knowledge point determining module 702 is specifically configured to:
clustering the behavior data and the learning course identification, and determining a plurality of knowledge point clusters related to the learning course; and determining at least one knowledge point cluster which meets a preset condition from the plurality of knowledge point clusters as a target knowledge point of the learning course, and acquiring the position information of the target knowledge point in the learning course.
In some embodiments of the present invention, based on the foregoing solution, the interpretation information obtaining module 703 is specifically configured to:
extracting keywords from the marked content, and determining the keywords as the keywords corresponding to the target knowledge point; and acquiring detailed explanation information about the target knowledge point according to the target knowledge point and the keyword corresponding to the target knowledge point.
In some embodiments of the present invention, based on the foregoing solution, the behavior data obtaining module 701 is further configured to: receiving data sent by a first data interface, and acquiring behavior data of the user about a learning course;
the aforementioned interpretation information obtaining module 703 is further configured to: and sending the target knowledge point and the keywords corresponding to the target knowledge point to a second data interface, and receiving detailed explanation information which is returned by the second data interface and is about the target knowledge point.
In some embodiments of the present invention, based on the foregoing scheme, the information association module 704 is specifically configured to: determining a hyperlink about the target knowledge point according to the refined interpretation information; and setting the hyperlink at the first target position, so that a user can obtain the detailed explanation information according to the hyperlink.
In some embodiments of the present invention, based on the foregoing scheme, the information associating module 704 is further specifically configured to: and setting an identifier at the first target position so that a user clicks the identifier to acquire the detailed explanation information.
Exemplary Medium
Having described the apparatus of the exemplary embodiments of the present invention, the media of the exemplary embodiments of the present invention will now be described.
In some possible embodiments, aspects of the present invention may also be implemented as a medium having stored thereon program code for implementing steps in an information processing method according to various exemplary embodiments of the present invention described in the above-mentioned "exemplary method" section of this specification, when the program code is executed by a processor of a device.
For example, the processor of the device may execute the program code to implement step S21 as described in fig. 2, and obtain behavior data of the user about the learning course; step S22, determining a target knowledge point related to the learning course according to the behavior data, and acquiring the position information of the target knowledge point in the learning course; step S23, acquiring the detailed explanation information about the target knowledge point; and a step S24 of determining a first target position based on the position information and associating the refined interpretation information to the first target position.
Referring to fig. 8, a program product 800 for implementing the above-described information processing method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto.
In some embodiments of the invention, the processor of the device, when executing the program code, is configured to implement the steps as illustrated in fig. 2 or any of fig. 4 to 6.
It should be noted that: the above-mentioned medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take a variety of forms, including, but not limited to: an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, fiber optic, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the consumer electronic device, partly on a remote electronic device, or entirely on the remote electronic device or server. In the case of remote electronic devices, the remote electronic devices may be connected to the consumer electronic device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external electronic device (e.g., through the internet using an internet service provider).
Exemplary electronic device
Having described the information processing method, the information processing apparatus, and the computer-readable medium according to the exemplary embodiments of the present invention, next, an electronic device according to another exemplary embodiment of the present invention is described.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Accordingly, various aspects of the present invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
In some possible embodiments, an electronic device according to embodiments of the present invention may include at least one processor, and at least one memory. Wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps in the information processing method according to various exemplary embodiments of the present invention described in the above section "exemplary method" of the present specification. For example, the processor may execute step S21 as described in fig. 2, acquiring behavior data of the user about the learning course; step S22, determining a target knowledge point related to the learning course according to the behavior data, and acquiring the position information of the target knowledge point in the learning course; step S23, acquiring the detailed explanation information about the target knowledge point; and a step S24 of determining a first target position based on the position information and associating the refined interpretation information to the first target position.
As another example, the processor may also perform the steps illustrated in fig. 2 or any of fig. 4 to 6.
An electronic device 900 according to an example embodiment of the invention is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present invention.
As shown in fig. 9, the electronic device 900 is represented in the form of a general-purpose electronic device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 901, the at least one memory unit 902, the bus 903 connecting different system components (including the memory unit 902 and the processing unit 901), and the display unit 907.
The bus 903 includes a data bus, an address bus, and a control bus.
The storage unit 902 may include readable media in the form of volatile memory, such as a Random Access Memory (RAM)9021 and/or a cache memory 9022, and may further include a Read Only Memory (ROM) 9023.
The electronic device 900 may also communicate with one or more external devices 904 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 900, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 900 to communicate with one or more other electronic devices. Such communication may occur over input/output (I/O) interfaces 905. Also, electronic device 900 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 906. As shown, the network adapter 906 communicates with the other modules of the electronic device 900 over the bus 903. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
It should be noted that although in the above detailed description several units/modules or sub-units/modules of the data processing device are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the units/modules described above may be embodied in one unit/module according to embodiments of the invention. Conversely, the features and functions of one unit/module described above may be further divided into embodiments by a plurality of units/modules.
It should be noted that although in the above detailed description several units or sub-units of the information processing apparatus are mentioned, such division is merely exemplary and not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit according to embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, while the operations of the method of the invention are depicted in the drawings in a particular order, this does not require or imply that the operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
While the spirit and principles of the invention have been described with reference to several specific embodiments, it is to be understood that the invention is not limited to the specific embodiments disclosed, nor is the division of aspects, which is for convenience only as the features in such aspects cannot be combined to advantage. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (8)
1. An information processing method, wherein the method comprises:
the method comprises the steps of obtaining behavior data of a plurality of users about each learning course in a plurality of learning courses, obtaining account identifications of the plurality of users generating the behavior data and course identifications of the learning courses, wherein the behavior data comprise pause time length, pause position and marked content in the learning courses; wherein the marked content comprises a plurality of curriculum contents heavily marked by a plurality of users in the pausing process, a plurality of commenting contents performed on the learning curriculum by the plurality of users in the pausing process and a plurality of online notes;
clustering according to the plurality of behavior data containing account identification and the course identification of the learning course, and determining a plurality of knowledge point clusters of each learning course according to a clustering result, wherein the clustering method comprises the following steps: obtaining pause starting points, pause ending points and pause duration of a plurality of users in the learning course, determining the pause starting points and the pause ending points of the overlapped parts of the pause periods of at least two users, and taking the course content corresponding to the overlapped parts of the pause periods of at least two users as the knowledge point cluster;
counting the number of pause periods corresponding to each knowledge point cluster, and taking the corresponding knowledge point cluster as a target knowledge point corresponding to the learning course in response to the fact that the number is larger than a preset threshold value;
acquiring the position information of the target knowledge point in the learning course and acquiring detailed explanation information about the target knowledge point; the method comprises the following steps: extracting keywords from the marked content, and determining the keywords as the keywords corresponding to the target knowledge point; acquiring detailed explanation information about the target knowledge point according to the target knowledge point and the keywords corresponding to the target knowledge point;
determining a first target location based on the location information and associating the refined interpretation information to the first target location,
said associating said refined interpretation information to said first target location comprises:
and setting an identifier at the first target position, wherein the identifier is used for reminding a user that the detailed explanation information is added at the first target position.
2. The information processing method according to claim 1,
the acquiring of the behavior data of the user about the learning course comprises the following steps:
receiving data sent by a first data interface, and acquiring behavior data of the user about the learning course;
the obtaining of the refined interpretation information about the target knowledge point comprises:
and sending the target knowledge point and the keywords corresponding to the target knowledge point to a second data interface, and receiving detailed explanation information which is returned by the second data interface and is about the target knowledge point.
3. The information processing method according to claim 1,
the determining a first target location based on the location information and associating the refined interpretation information to the first target location comprises:
determining a hyperlink about the target knowledge point according to the refined interpretation information;
and setting the hyperlink at the first target position so that a user can obtain the refined interpretation information according to the hyperlink.
4. An information processing apparatus, wherein the apparatus comprises:
the system comprises a behavior data acquisition module, a data storage module and a data processing module, wherein the behavior data acquisition module is used for acquiring behavior data of a plurality of users about each learning course in the plurality of learning courses, and acquiring account identifications of the plurality of users generating the behavior data and the course identifications of the learning courses, and the behavior data comprises pause duration, pause positions and mark contents in the learning courses; wherein the marked content comprises a plurality of course contents heavily marked by a plurality of users in a pausing process, a plurality of annotation contents of the plurality of users for the learning course in the pausing process and a plurality of online notes;
the target knowledge point determining module is used for clustering according to the plurality of behavior data containing the account number identifications and the course identifications of the learning courses and determining a plurality of knowledge point clusters of each learning course according to a clustering result; counting the number of pause periods corresponding to each knowledge point cluster, and taking the corresponding knowledge point cluster as a target knowledge point corresponding to the learning course in response to the fact that the number is larger than a preset threshold value; the position information of the target knowledge point in the learning course is acquired; wherein the determination of the knowledge point cluster comprises: acquiring pause starting points, pause ending points and pause duration of the plurality of users in the learning course, determining the pause starting points and the pause ending points of the pause time period coincident parts of at least two users, and taking the course contents corresponding to the pause time period coincident parts of at least two users as the knowledge point cluster;
the interpretation information acquisition module is used for acquiring detailed interpretation information about the target knowledge point; the method comprises the following steps: extracting keywords from the marked content, and determining the keywords as the keywords corresponding to the target knowledge point; acquiring refined explanation information about the target knowledge point according to the target knowledge point and the keyword corresponding to the target knowledge point;
an information association module for determining a first target location based on the location information and associating the refined interpretation information to the first target location,
the information association module is further configured to:
and setting an identifier at the first target position, wherein the identifier is used for reminding a user that the detailed explanation information is added at the first target position.
5. The information processing apparatus of claim 4, wherein the behavior data acquisition module is further configured to:
receiving data sent by a first data interface, and acquiring behavior data of the user about the learning course;
the interpretation information obtaining module is further configured to:
and sending the target knowledge point and the keywords corresponding to the target knowledge point to a second data interface, and receiving detailed explanation information which is returned by the second data interface and is about the target knowledge point.
6. The information processing apparatus according to claim 4, wherein the information association module is specifically configured to:
determining a hyperlink about the target knowledge point according to the refined interpretation information;
and setting the hyperlink at the first target position so that a user can obtain the refined interpretation information according to the hyperlink.
7. A computer-readable medium on which a computer program is stored, which program, when executed by a processor, implements the information processing method according to any one of claims 1 to 3.
8. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the information processing method according to any one of claims 1 to 3.
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| CN112687138B (en) * | 2020-12-30 | 2022-05-03 | 江苏传智播客教育科技股份有限公司 | Interactive teaching platform based on Internet of things |
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