CN112307346A - Courseware management system based on big data - Google Patents
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Abstract
The invention relates to the field of big data and intelligent education, and discloses a courseware management system based on big data. The education cloud platform comprises a database, a courseware recommendation module, a courseware analysis module and a courseware pushing module. After receiving courseware request data sent by a first education terminal, a courseware recommendation module of the education cloud platform generates a first data flow according to the courseware request data. And the courseware recommending module analyzes the courseware adaptation degree of the education consumer according to the first data flow and the education consumer information. And when the courseware adaptation degree is greater than the courseware learning degree, the courseware pushing module processes the courseware request data and the education consumer information to obtain a second data stream and sends the second data stream to the corresponding second education terminal. The courseware analysis module obtains courseware learning information of education consumers to obtain a courseware learning dictionary, and analyzes the courseware learning dictionary to obtain courseware analysis data.
Description
Technical Field
The invention relates to the field of big data and intelligent education, in particular to a courseware management system based on big data.
Background
The intelligent education refers to the modern education system which is characterized in that novel technologies represented by the internet, the internet of things, cloud computing, big data and the like are comprehensively and deeply utilized by relying on modern information technologies in the education field (education management, education teaching and education interaction), the education teaching quality and benefits are improved by innovative education modes and education means, and digitization, networking, intellectualization and multimedia are comprehensively constructed.
The intelligent education comprehensive application solution is large in user number and high in use frequency, in order to support large-scale application in an internet environment and meet continuous expansion of education service application software, a cloud service support platform needs to be constructed, an elastic deployment environment is provided for upper-layer cloud application, global data integration and integration, unified identity management and unified authentication of users, interaction and collaborative environment support based on a virtual community, large-scale content management and service, interface service and management support of upper-layer application are born at the same time, and operation and maintenance support such as operation monitoring and resource pool management of the cloud service platform is provided.
At present, the number teaching resources related to network education are increasing. The digital teaching resources are beneficial to better understanding of teaching contents of students and improving teaching effects. However, as digital teaching resources become more abundant, the difficulty of educating users in finding matching or appropriate courseware also increasing.
Disclosure of Invention
Because the traditional courseware searching mode is to search according to courseware names, the searched courseware content is often different from the courseware content desired by the user, which is not beneficial to quickly and accurately searching the courseware needed to be used. In addition, in order to meet the personalized learning requirements of the education users, accurate recommendation of education courseware needs to be realized.
In order to solve the defects of the prior art, the invention provides a courseware management system based on big data, which comprises: the education cloud platform is in communication connection with the first education terminal and the second education terminal respectively, the education cloud platform comprises a database, a courseware recommendation module, a courseware analysis module and a courseware pushing module, the first education terminal is terminal equipment used by an education provider, and the second education terminal is terminal equipment used by an education consumer;
the education cloud platform receives courseware request data sent by a first education terminal, wherein the courseware request data comprise courseware content, courseware basic information, courseware tags and target education consumer information;
a courseware recommendation module of the education cloud platform generates a first data flow according to courseware request data, wherein the first data flow comprises courseware labels, courseware basic information and target education consumer information;
the courseware recommending module analyzes the courseware adaptation degree of the education consumer according to the first data flow and the education consumer information;
when the courseware adaptation degree is greater than the courseware learning degree, the courseware pushing module processes the courseware request data and the education consumer information to obtain a second data stream and sends the second data stream to a corresponding second education terminal, and the second data stream comprises courseware content and an equipment identifier of the second education terminal;
the courseware analysis module obtains courseware learning information of education consumers to obtain a courseware learning dictionary, and analyzes the courseware learning dictionary to obtain courseware analysis data.
The first education terminal comprises a smart phone, a tablet computer and a notebook computer; the second educational terminal comprises a smart phone, a desktop computer, a tablet computer and a notebook computer.
In a further embodiment, a courseware recommendation module of the education cloud platform obtains a courseware recommendation dictionary according to the first data flow, wherein the courseware recommendation dictionary comprises an identifier of each courseware recommendation index and a courseware recommendation vector P corresponding to each courseware recommendation index.
The courseware recommendation module acquires an education consumer dictionary according to the education consumer information, wherein the education consumer dictionary comprises an identifier of each courseware recommendation index and an education consumer vector Q corresponding to each courseware recommendation index. The courseware recommendation indexes comprise: age, interest, school calendar.
In a further embodiment, the courseware recommendation module is configured to recommend a courseware according to a courseware recommendation vector P ═ P1,p2…pn]And educating consumer vector Q ═ Q1,q2,…qn]Calculating the adaptation degree h of each courseware recommendation index,
wherein the content of the first and second substances,
i is a characteristic index, n is the characteristic number of each courseware recommendation index, and q isiEducational Consumer characteristic value, p, for the ith characteristic of the corresponding courseware recommendation indexiAnd recommending a characteristic value for the courseware corresponding to the ith characteristic of the courseware recommendation index.
In a further embodiment, the courseware recommending module calculates the courseware suitability r according to the suitability corresponding to all courseware recommending indexes,
wherein j is the index of courseware recommendation indexes, m is the number of courseware recommendation indexes, e is the natural base number, hjAdaptation degree, s corresponding to jth courseware recommendation indexjAnd the weighting coefficient corresponding to the jth courseware recommendation index.
In a further embodiment, the education consumer information includes a name, a gender, an age, a scholarly, an interest, historical learning data of the education consumer, and a device identifier of a second education terminal corresponding to the education consumer.
In further embodiments, the target educational consumer is a target audience for a courseware; the target education consumer information includes age, academic history, and interests of the target education consumer.
The courseware learning dictionary includes the device identifier of the second educational terminal and courseware learning information corresponding to the educational consumer.
Courseware analysis data includes courseware pushing success rate, courseware watching user number, courseware playing number and courseware consumer feature dictionary.
In a further embodiment, the courseware basic information comprises courseware type, courseware expression form and courseware format.
The courseware types include: the system comprises a webpage text class, a multimedia class and an interactive class, wherein the webpage text class courseware is a courseware developed by a webpage making tool in a text form; the multimedia courseware is a multimedia courseware represented by video, audio and animation modes; the interaction class courseware is courseware that interacts with the educational consumer through a remote or local application.
In further embodiments, the courseware expression includes text, images, audio, video, and animation. The courseware tag comprises subject to which courseware belongs, courseware titles and courseware knowledge points.
The courseware adaptation degree is obtained according to the courseware request data sent by the first education terminal and the education consumer information sent by the second education terminal, and courseware is pushed to the education consumers with the courseware adaptation degree larger than the courseware learning degree, so that the courseware recommendation efficiency is improved, and accurate courseware recommendation is realized.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 schematically illustrates a block diagram of a big data based courseware management system;
fig. 2 schematically shows a flow chart of a method of intelligent educational courseware management.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments herein without making any creative effort, shall fall within the scope of protection.
As shown in FIG. 1, in one embodiment, the big data based courseware management system of the present invention comprises: the system comprises an education cloud platform, at least one first education terminal and at least one second education terminal. The first educational terminal is a terminal device used by an educational provider, and the second educational terminal is a terminal device used by an educational consumer. The first educational terminal may include a smart phone, a tablet computer, and a notebook computer, and the second educational terminal may include a smart phone, a desktop computer, a tablet computer, and a notebook computer.
The education cloud platform is respectively in communication connection with the first education terminal and the second education terminal. Specifically, the education cloud platform comprises a database, a courseware recommending module, a courseware analyzing module and a courseware pushing module, wherein the courseware pushing module is in communication connection with the database, the courseware recommending module and the courseware analyzing module respectively.
The first education terminal is used for sending courseware request data to the education cloud platform. The second education terminal is used for sending education consumer information to the education cloud platform.
The courseware recommendation module is used for calculating courseware adaptation degree of each education consumer according to the first data flow and the education consumer information.
And when the courseware adaptation degree is greater than the courseware learning degree, the courseware pushing module processes the courseware request data and the education consumer information to obtain a second data stream and sends the second data stream to the corresponding second education terminal.
And the courseware pushing module is used for processing according to the courseware request data and the education consumer information to obtain a second data stream and sending the second data stream to the corresponding second education terminal.
The courseware analysis module is used for obtaining a courseware learning dictionary according to the courseware learning information of the education consumers and analyzing the courseware learning dictionary to obtain courseware analysis data.
For the purposes of promoting an understanding, the principles and operation of the present invention are described in detail below.
Specifically, in an embodiment, as shown in fig. 2, the intelligent educational course management method may specifically include the following steps:
s1, the education cloud platform receives courseware request data sent by the first education terminal, wherein the courseware request data comprise courseware content, courseware basic information, courseware labels and target education consumer information.
The courseware request data is data sent by the first education terminal and used for instructing the education cloud platform to push courseware to education consumers suitable for learning. The first education terminal is terminal equipment of an education provider and comprises a smart phone, a tablet computer, a notebook computer and a smart watch.
The target education consumer is the target audience of the courseware, and the target education consumer information comprises the age, the academic history and the interest of the target education consumer and the related knowledge mastery degree. The courseware content is that the courseware label includes subject, courseware title and courseware knowledge point that the courseware belongs to.
Optionally, the courseware basic information includes courseware type, courseware expression form and courseware format. The courseware types include: the system comprises a webpage text class, a multimedia class and an interactive class, wherein the webpage text class courseware is a text-form courseware developed by a webpage making tool. The multimedia courseware is a multimedia courseware embodied in a video mode, an audio mode and an animation mode. The interaction class courseware is courseware that interacts with the educational consumer through a remote or local application.
Courseware expressions include text, images, audio, video, and animation. Courseware formats include JPG, GIF, WAV, MIDI, MP3, WMA, FLASH, AVI, ASF, and Quick Time.
And S2, generating a first data stream by the courseware recommendation module of the education cloud platform according to the courseware request data, wherein the first data stream comprises courseware labels, courseware basic information and target education consumer information.
For example, in one embodiment, a math teacher at a college uploads higher math learning courseware relating to learning high numbers, which is a teaching video of the teacher recording a differential in a classroom. The courseware recommendation module of the education cloud platform generates a first data flow according to courseware request data sent by an education terminal used by a teacher, wherein the first data flow comprises courseware labels, courseware basic information and target education consumer information, the subject of the courseware is mathematics, courseware knowledge points are differential, and courseware titles are function differential mathematics in the courseware labels of the courseware. The courseware type in the courseware basic information is multimedia, the courseware expression form is video, and the courseware format is AVI. The target of the courseware educates consumers as college students in science and technology.
In the embodiment, the first data stream is used for prompting the relevant information of the advanced mathematic courseware, the target education consumers of the courseware are specified to be students reading the major for the science and technology, the range of the education consumers is greatly reduced, the education cloud platform does not recommend the courseware to each education consumer blindly, accurate pushing is achieved, and cloud computing resources and network transmission bandwidth are saved.
Therefore, the first data stream generated according to the courseware request data only comprises information related to courseware adaptation degree calculation, data irrelevant to the courseware adaptation degree calculation is reduced in transmission, and the efficiency of the courseware adaptation degree calculation is improved.
And S3, the courseware recommending module analyzes the first data flow and the education consumer information to obtain the courseware adaptation degree of the second education terminal.
The second education terminal is a terminal device for educating the consumer. The second educational terminal includes, but is not limited to, a smartphone, a desktop computer, a tablet computer, a laptop computer, and a smart watch.
Optionally, the education consumer information includes a name, a gender, an age, a study, an interest, historical learning data of the education consumer, and a device identifier of a corresponding second education terminal of the education consumer.
Optionally, the education provider is a relevant group providing courseware resources over a network, including relevant educational institution personnel, school teachers, or courseware makers. The education consumers are related groups for learning by acquiring courseware resources through the network, and the related groups comprise students and other people with learning requirements in school reading.
The courseware recommendation module of the education cloud platform obtains a courseware recommendation dictionary according to the first data flow, wherein the courseware recommendation dictionary comprises an identifier of each courseware recommendation index and a courseware recommendation vector P corresponding to each courseware recommendation index.
The courseware recommendation module acquires an education consumer dictionary according to the education consumer information, wherein the education consumer dictionary comprises an identifier of each courseware recommendation index and an education consumer vector Q corresponding to each courseware recommendation index. The courseware recommendation indexes comprise: age, interest, academic history, and knowledge mastery.
Optionally, the courseware recommendation module sets [ P ] according to the courseware recommendation vector P1,p2…pn]And educating consumer vector Q ═ Q1,q2,…qn]Calculating the adaptation degree h of each courseware recommendation index,
wherein the content of the first and second substances,
i is a characteristic index, n is the characteristic number of each courseware recommendation index, and q isiEducational Consumer characteristic value, p, for the ith characteristic of the corresponding courseware recommendation indexiAnd recommending a characteristic value for the courseware corresponding to the ith characteristic of the courseware recommendation index.
Optionally, the suitability of the courseware recommendation index is the matching degree of the education consumer and the courseware when the specific courseware recommendation index is aimed at. For example, when calculating the matching degree of the course recommendation index, which is the knowledge point mastery degree of an english course, the english course is specified in the course request data to be suitable for educational consumers whose english level is above the english level. If the education consumer does not go through the fourth grade of English, the matching degree of the education consumer and the courseware recommendation index of knowledge point mastering degree of the English courseware is lower.
The courseware recommendation module calculates courseware adaptation degrees according to the adaptation degrees corresponding to all courseware recommendation indexes:
wherein r is courseware adaptation degree, j is courseware recommendation index, m is number of courseware recommendation indexes, e is natural base number, hjAdaptation degree, s corresponding to jth courseware recommendation indexjAnd the weighting coefficient corresponding to the jth courseware recommendation index.
S4, when the courseware adaptation degree is larger than the courseware learning degree, the courseware pushing module processes the courseware request data and the education consumer information to obtain a second data stream, and sends the second data stream to the corresponding second education terminal; the second data stream includes courseware content and a device identifier of the second educational terminal.
The device identifier of the second educational terminal is used to uniquely identify the second educational terminal. The process of generating the second data stream includes: the courseware pushing module acquires education consumer information with courseware adaptation degree greater than courseware learning degree;
the courseware pushing module acquires the equipment identifier of the second education terminal according to the education consumer information; the courseware pushing module acquires courseware contents according to the courseware request data;
and the courseware pushing module carries out mapping processing on courseware content and the equipment identifier of the second education terminal to obtain a second data stream.
Alternatively, an english teacher of a college uploads english courseware relating to english learning, which is a section of explanation video recorded by the teacher relating to foreign classical culture. And a courseware recommendation module of the education cloud platform generates a first data stream according to courseware request data sent by a first education terminal used by the teacher. The first data flow comprises courseware labels, courseware basic information and target education consumer information, wherein in the courseware labels of the courseware, the subject of the courseware is English, the courseware knowledge point is classical culture, and the courseware title is foreign classical culture appreciation. In the courseware basic information, the courseware type is multimedia, the courseware expression form is video, and the courseware format is AVI. The target education consumers of the courseware are college students of English major and crowds with English level reaching more than eight.
The educational consumers obtained by the courseware pushing module are students of English major of colleges, the English level is more than eight specialties, and the interest and the historical learning data of the educational consumers are related to foreign classical culture. The courseware pushing module obtains courseware adaptation degree of education consumers larger than courseware learning degree according to the first data flow and the education consumer information, obtains a second data flow according to courseware request data and the education consumer information, and pushes the second data flow to corresponding education consumers. The second data stream includes the courseware content for the english courseware and the device identifier for the second educational terminal.
The courseware pushing module obtains that a certain education consumer is a mathematic specialty, college students of English level four, courseware pushing module is less than courseware learning degree according to the courseware adaptation degree of the second education terminal obtained by the first data flow and the education consumer information analysis, and the courseware pushing module can not push the English courseware for the courseware pushing module.
The courseware learning degree is a preset adaptation degree threshold value and is used for representing the adaptation degree which at least needs to be reached by the adaptation degree of the courseware and the education consumer when the courseware is learned by the education consumer and smoothly ends a course. In this way, the second data stream generated according to the courseware request data only comprises courseware contents and the equipment identifier of the second education terminal, so that the transmission of other non-relevant data during courseware recommendation is avoided, and the purposes of saving bandwidth and network resources and improving courseware pushing efficiency are achieved.
In another embodiment, the method further comprises: the courseware analysis module obtains courseware learning information of education consumers with courseware adaptation degree larger than courseware learning degree to obtain a courseware learning dictionary, and analyzes the courseware learning dictionary to obtain courseware analysis data.
The courseware learning information includes the time the educational consumer watched the courseware, the number of completed courseware and the average progress of courseware watching.
The courseware learning dictionary comprises an equipment identifier of the second education terminal and corresponding courseware learning information; courseware analysis data includes courseware pushing success rate, courseware watching user number, courseware playing number and courseware consumer feature dictionary.
The courseware pushing success rate is the total number of education consumers with courseware adaptation degree larger than courseware learning degree and the number of education consumers actually learning the courseware. The number of courseware watching users is the number of educational consumers watching the courseware. The courseware consumer profile dictionary is the educational consumer information for the educational consumers who actually view the courseware.
In another embodiment, the first educational terminal updates the targeted educational consumer information in the original courseware request data according to a courseware consumer profile dictionary in the courseware analysis data.
In this embodiment, the targeted education consumer information in the course request data is updated by the relevant characteristic information of the education consumer actually learned to improve the course recommendation accuracy at the next course recommendation.
Although specific functionality is discussed above with reference to particular modules, it should be noted that the functionality of the various modules discussed herein may be divided into multiple modules and/or at least some of the functionality of multiple modules may be combined into a single module. Additionally, a particular module performing an action discussed herein includes the particular module itself performing the action, or alternatively the particular module invoking or otherwise accessing another component or module that performs the action (or performs the action in conjunction with the particular module). Thus, a particular module that performs an action can include the particular module that performs the action itself and/or another module that the particular module that performs the action calls or otherwise accesses.
The principles and embodiments of this document are explained herein using specific examples, which are presented only to aid in understanding the methods and their core concepts; meanwhile, for the general technical personnel in the field, according to the idea of this document, there may be changes in the concrete implementation and the application scope, in summary, this description should not be understood as the limitation of this document.
Claims (10)
1. The courseware management system based on the big data is characterized by comprising an education cloud platform, a first education terminal and a second education terminal, wherein the education cloud platform is in communication connection with the first education terminal and the second education terminal respectively, the education cloud platform comprises a database, a courseware recommendation module, a courseware analysis module and a courseware pushing module, the first education terminal is terminal equipment used by an education provider, and the second education terminal is terminal equipment used by an education consumer;
the education cloud platform receives courseware request data sent by a first education terminal, wherein the courseware request data comprise courseware content, courseware basic information, courseware tags and target education consumer information;
a courseware recommendation module of the education cloud platform generates a first data flow according to courseware request data, wherein the first data flow comprises courseware labels, courseware basic information and target education consumer information;
the courseware recommending module analyzes the courseware adaptation degree of the education consumer according to the first data flow and the education consumer information;
when the courseware adaptation degree is greater than the courseware learning degree, the courseware pushing module processes the courseware request data and the education consumer information to obtain a second data stream and sends the second data stream to a corresponding second education terminal, and the second data stream comprises courseware content and an equipment identifier of the second education terminal;
the courseware analysis module obtains courseware learning information of education consumers to obtain a courseware learning dictionary, and analyzes the courseware learning dictionary to obtain courseware analysis data.
2. The system of claim 1, wherein the first educational terminal comprises a smartphone, a tablet computer, and a laptop computer;
the second educational terminal comprises a smart phone, a desktop computer, a tablet computer and a notebook computer.
3. The system of claim 2, wherein the courseware recommendation module of the education cloud platform obtains a courseware recommendation dictionary according to the first data flow, the courseware recommendation dictionary comprising an identifier for each courseware recommendation index and a courseware recommendation vector corresponding to each courseware recommendation index;
the courseware recommendation module obtains an education consumer dictionary according to education consumer information, the education consumer dictionary comprises an identifier of each courseware recommendation index and an education consumer vector corresponding to each courseware recommendation index, and the courseware recommendation indexes comprise: age, interest, school calendar.
4. The system of claim 3, wherein the courseware recommendation module calculates the courseware suitability according to the suitability corresponding to all the courseware recommendation indexes,
wherein r is courseware adaptation degree, j is courseware recommendation index, m is number of courseware recommendation indexes, e is natural base number, hjAdaptation degree, s corresponding to jth courseware recommendation indexjAnd the weighting coefficient corresponding to the jth courseware recommendation index.
5. The system of claim 4, wherein the education consumer information includes a name, a gender, an age, a scholarly calendar, an interest, historical learning data of the education consumer and a device identifier of the corresponding second education terminal.
6. The system of claim 5, wherein the target educational consumer is a target audience for a courseware, and the target educational consumer information comprises age, academic history, and interests of the target educational consumer;
the courseware learning dictionary includes a device identifier of the second educational terminal and courseware learning information corresponding to the educational consumer.
7. The system of claim 6, wherein the courseware analysis data includes courseware push success rate, courseware view count, and courseware consumer profile dictionary.
8. The system of any one of claims 1 to 7, wherein the courseware base information comprises courseware type, courseware expression form and courseware format.
9. The system of claim 8, wherein the courseware types include: a web page text class, a multimedia class, an interactive class, wherein,
the webpage text courseware is a courseware in a text form developed by a webpage making tool; the multimedia courseware is a multimedia courseware represented by video, audio and animation modes; the interaction class courseware is courseware that interacts with the educational consumer through a remote or local application.
10. The system of claim 9, wherein the courseware tags include subject to which the courseware belongs, courseware titles and courseware knowledge points.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7526458B2 (en) * | 2003-11-28 | 2009-04-28 | Manyworlds, Inc. | Adaptive recommendations systems |
| CN102508846A (en) * | 2011-09-26 | 2012-06-20 | 深圳中兴网信科技有限公司 | Internet based method and system for recommending media courseware |
| CN103514162A (en) * | 2012-06-15 | 2014-01-15 | 上海蓝卓教育信息科技有限公司 | Intelligent courseware recommending system |
| US20160055242A1 (en) * | 2014-08-20 | 2016-02-25 | Luceo Social, Inc. | Systems and methods for analyzing content from digital content sources |
| CN105741628A (en) * | 2016-04-29 | 2016-07-06 | 广西犇云科技有限公司 | Autonomous learning platform system |
| CN106528656A (en) * | 2016-10-20 | 2017-03-22 | 杨瀛 | Student history and real-time learning state parameter-based course recommendation realization method and system |
| CN107403398A (en) * | 2017-07-18 | 2017-11-28 | 广州市沃迩德文化教育咨询服务有限公司 | A kind of English education internet platform and its application method |
| CN107741978A (en) * | 2017-10-13 | 2018-02-27 | 北京中教在线科技有限公司 | A kind of Pushing personality study resource method and its system |
| CN109035930A (en) * | 2017-06-08 | 2018-12-18 | 深圳市鹰硕技术有限公司 | A kind of recorded broadcast data recommendation method Internet-based |
| CN110223206A (en) * | 2019-06-11 | 2019-09-10 | 广州蓝鸽软件有限公司 | Text major field determines method and system and parsing courseware matching process and system |
| CN111832952A (en) * | 2020-07-18 | 2020-10-27 | 广元量知汇科技有限公司 | Education courseware pushing system |
-
2020
- 2020-11-09 CN CN202011242019.9A patent/CN112307346B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7526458B2 (en) * | 2003-11-28 | 2009-04-28 | Manyworlds, Inc. | Adaptive recommendations systems |
| CN102508846A (en) * | 2011-09-26 | 2012-06-20 | 深圳中兴网信科技有限公司 | Internet based method and system for recommending media courseware |
| CN103514162A (en) * | 2012-06-15 | 2014-01-15 | 上海蓝卓教育信息科技有限公司 | Intelligent courseware recommending system |
| US20160055242A1 (en) * | 2014-08-20 | 2016-02-25 | Luceo Social, Inc. | Systems and methods for analyzing content from digital content sources |
| CN105741628A (en) * | 2016-04-29 | 2016-07-06 | 广西犇云科技有限公司 | Autonomous learning platform system |
| CN106528656A (en) * | 2016-10-20 | 2017-03-22 | 杨瀛 | Student history and real-time learning state parameter-based course recommendation realization method and system |
| CN109035930A (en) * | 2017-06-08 | 2018-12-18 | 深圳市鹰硕技术有限公司 | A kind of recorded broadcast data recommendation method Internet-based |
| CN107403398A (en) * | 2017-07-18 | 2017-11-28 | 广州市沃迩德文化教育咨询服务有限公司 | A kind of English education internet platform and its application method |
| CN107741978A (en) * | 2017-10-13 | 2018-02-27 | 北京中教在线科技有限公司 | A kind of Pushing personality study resource method and its system |
| CN110223206A (en) * | 2019-06-11 | 2019-09-10 | 广州蓝鸽软件有限公司 | Text major field determines method and system and parsing courseware matching process and system |
| CN111832952A (en) * | 2020-07-18 | 2020-10-27 | 广元量知汇科技有限公司 | Education courseware pushing system |
Non-Patent Citations (4)
| Title |
|---|
| CHIH-MING CHEN等: "A personalized courseware recommendation system based on fuzzy item response theory", 《 IEEE INTERNATIONAL CONFERENCE ON E-TECHNOLOGY》 * |
| 李晓敏: "四川建筑职业技术学院课件管理***的设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 王孟: "基于教育云平台的个性化推荐***设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 赵呈领: "适应性学习路径推荐算法及应用研究", 《中国电化教育》 * |
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