CN106980691A - A kind of method for auto constructing in on-line teaching resources storehouse - Google Patents
A kind of method for auto constructing in on-line teaching resources storehouse Download PDFInfo
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- CN106980691A CN106980691A CN201710211689.6A CN201710211689A CN106980691A CN 106980691 A CN106980691 A CN 106980691A CN 201710211689 A CN201710211689 A CN 201710211689A CN 106980691 A CN106980691 A CN 106980691A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
Abstract
The invention discloses a kind of method for auto constructing in on-line teaching resources storehouse, on-line teaching resources database is first built, the on-line teaching resources database crawls table, teaching resource tables of data, teaching resource classification chart and teaching resource grade form comprising data；Then the resource information to above-mentioned on-line teaching resources database carries out information extraction and quality testing, and on-line teaching resources detailed data is stored in teaching resource tables of data；Using the SVM algorithm in machine learning, on-line teaching resources are classified automatically；And classification results are stored in teaching resource classification chart；Pageview, user finally according to on-line teaching resources storehouse are evaluated, the number of participant scores on-line teaching resources, teaching resource are sorted from high to low according to scoring, and appraisal result is stored in into teaching resource grade form.The present invention has conformability, continuation and the uniformity of height, greatly facilitates client and resource is searched and evaluated.
Description
Technical field
The present invention relates to online teaching field, more particularly to a kind of method for auto constructing in on-line teaching resources storehouse.
Background technology
With the gradually popularization of internet, online education turns into the new way that people obtain knowledge., the top in the U.S. in 2012
Sharp university sets up Network Learning Platform successively, and free course, Coursera (https are provided on the net://
www.coursera.org/)、Udacity(https://www.udacity.com/)、edX(https://
Www.edx.org/) rise of three big course providers provides the possibility of systematic learning to more students.People can pass through
On-line teaching resources distance learning relevant knowledge or technology are watched, transmission of knowledge is greatly facilitated.The country also went out in recent years
Show many online education platforms, large-scale open network course, i.e. MOOC's (massive open online courses)
Concept is known by increasing people., MOOC institutes (http under shell net in 2013://mooc.guokr.com/) reach the standard grade.
MOOC institutes are maximum Chinese MOOC Learning Community, have included the course on 1500 multi-door major MOOC platforms.There are 500,000
Habit person comments on course, share note, exchange is discussed herein.In May, 2014, the national fine work of the Ministry of Education is accepted by Netease's cloud classroom
Open Course task, with love curriculum net cooperation release " Chinese Universities MOOC " projects are formally reached the standard grade.
Enriching for online education resource gives people more chance learning knowledges, but from numerous online education communities how
Resource needed for positioning and searching oneself be active user using online education resource when the major issue that faces.In different communities
The organizational form of online resource is had nothing in common with each other, and the information such as description, label, classification of educational resource is different because of the community where it.
Therefore how to effectively integrate the on-line teaching resources of magnanimity turns into current urgent problem to be solved with classification and ordination.
At present, there are hundreds thousand of online education resources in major online education communities, effective classification of resource, which turns into, to be used
Family quickly positions the important way of its required resource.Although all having been carried out in major online teaching websites to educational resource tentatively
Classification, but major websites, to the classification degree disunity of educational resource, criteria for classification is also not quite similar.Especially from foreign network
There is very big difference with website in the country in the mode classification for the online education resource stood.Directly by the mode classification of the original community of resource
The confusion of final classification can be caused by carrying out simple synthesis.Therefore, during the resource from multiple communities is integrated,
Need to reclassify resource, the resource needed for it is searched by rationally effective classification help user.In addition, how right
Online education resource, which is evaluated and sorted, also turns into another significant problem after resource consolidation.
The content of the invention
It is an object of the invention to for a large amount of on-line teaching resources present in internet, propose that one kind can be automatic
On-line teaching resources are obtained from different communities and the automatic of the on-line teaching resources storehouse of homogeneous classification and sequence is carried out to resource
Construction method.
To achieve the above object, the present invention provides a kind of method for auto constructing in on-line teaching resources storehouse, including following step
Suddenly：
S1, structure on-line teaching resources database, the on-line teaching resources database crawl table, teaching money comprising data
Source data table, teaching resource classification chart and teaching resource grade form；
S2, the resource information to above-mentioned on-line teaching resources database carry out information extraction and quality testing, and will be online
Teaching resource detailed data is stored in teaching resource tables of data；
S3, using the SVM algorithm in machine learning, on-line teaching resources are classified automatically；And deposit classification results
Storage is in teaching resource classification chart；
S4, the pageview according to on-line teaching resources storehouse, user's evaluation, the number of participant are commented on-line teaching resources
Point, teaching resource is sorted from high to low according to scoring, and appraisal result is stored in teaching resource grade form.
In step S1, using general Web crawler technologies timing acquisition from disclosed online teaching community on internet
Resource information needed for on-line teaching resources database, and be stored in and crawled in tables of data in the way of html text；Pass through Web
The on-line teaching resources information that crawler technology is obtained is stored in data in the mode of [url, page HTML] and crawled in table.If in the presence of
The page of mistake is crawled, page URL is marked, can be crawled again when next time crawls；The wrong page includes：HTML
The page be 404 pages, or important information field missing page link.
In step S2, extract and the information of quality testing includes：The titles of on-line teaching resources, description, institutional affiliation or
School, teacher, course beginning and ending time, label, language, the number of participant, comment, user evaluate.
Carry out the data after information extraction and quality testing and teaching money is stored in [course id, url, title, description ...]
In source data table.
In step S3, according to the title of on-line teaching resources database, description, label, body release, lecturer's information to
Line teaching resource is classified automatically；And criteria for classification is the discipline classification that the Ministry of Education announces.
In step S4, appraisal result is stored in teaching resource grade form with the form of [course id, scoring].The scoring knot
Fruit score computational methods are：Score=α × v+ β × p+ γ × r, wherein, v is the pageview of on-line teaching resources, and p is ginseng
Plus number, r is user's evaluation；
During calculating, three indexs are first normalized to the scope of [0,100], three coefficients are then set to represent
The weight of each index is stated, the value of three coefficients can be adjusted according to actual sequence needs.
Further, SVM algorithm includes：
S301, the data mark of machine learning：Some on-line teaching resources crawled are selected first as sample, it is artificial right
The classification of sample is labeled；The sample of selection will uniformly cover all categories as far as possible, and each resource is pertaining only to a class；
S302, grader feature extraction：By the analysis to on-line teaching resources data, the type genus of teaching resource is chosen
Property, include title, label, body release, description and the teacher of teaching resource, and the original sample to being marked in step 301
This progress respective handling；
S303, training grader：The sample data training SVM classifier marked is inputted, java is used during specific implementation
The libsvm bags of language are trained；
S304, other sample classifications；After the completion of classifier training, the teaching resource data input grader not marked is entered
Row classification, final classification results are stored in course grouped data table, and storage format is [course id, classification].
Compared with prior art, the present invention has the advantages that：
(1) conformability, the present invention has crawled the teaching resource of multiple online education communities, and the teaching resource disperseed is effective
Integrate so that user need not go to browse other online education communities respectively, can directly from the present invention build it is online
The resource needed for it is positioned and searched in teaching resources library, is had great convenience for the user, and is that user saves the time；
(2) continuation, the present invention is crawled to teaching resource timed increase, continuously obtains newest from other communities
Teaching resource；
(2) homogeneous classification, different community has different criteria for classification and mode classification, and the present invention is with the Ministry of Education
Section is categorized as standard and on-line teaching resources has been carried out with unified classification using the mode of machine learning；
(3) it is unified to evaluate, the present invention by user to the evaluation of teaching resource, the number of visits of user, participate in course
The information such as number have carried out unified evaluation and sequence to on-line teaching resources.
Brief description of the drawings
Fig. 1 is method flow schematic diagram of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Referring to Fig. 1, the present invention provides a kind of technical scheme：
A kind of method for auto constructing in on-line teaching resources storehouse, comprises the following steps：
S1, structure on-line teaching resources database, the on-line teaching resources database crawl table, teaching money comprising data
Source data table, teaching resource classification chart and teaching resource grade form；
S2, the resource information to above-mentioned on-line teaching resources database carry out information extraction and quality testing, and will be online
Teaching resource detailed data is stored in teaching resource tables of data；
S3, using the SVM algorithm in machine learning, on-line teaching resources are classified automatically；And deposit classification results
Storage is in teaching resource classification chart；
S4, the pageview according to on-line teaching resources storehouse, user's evaluation, the number of participant are commented on-line teaching resources
Point, teaching resource is sorted from high to low according to scoring, and appraisal result is stored in teaching resource grade form.
In step S1, using general Web crawler technologies timing acquisition from disclosed online teaching community on internet
Resource information needed for on-line teaching resources database, and be stored in and crawled in tables of data in the way of html text；Pass through Web
The on-line teaching resources information that crawler technology is obtained is stored in data in the mode of [url, page HTML] and crawled in table.If in the presence of
The page of mistake is crawled, page URL is marked, can be crawled again when next time crawls；The wrong page includes：HTML
The page be 404 pages, or important information field missing page link.
In step S2, extract and the information of quality testing includes：The titles of on-line teaching resources, description, institutional affiliation or
School, teacher, course beginning and ending time, label, language, the number of participant, comment, user evaluate.
Carry out the data after information extraction and quality testing and teaching money is stored in [course id, url, title, description ...]
In source data table.
In step S3, according to the title of on-line teaching resources database, description, label, body release, lecturer's information to
Line teaching resource is classified automatically；And criteria for classification is the discipline classification that the Ministry of Education announces.
In step S4, appraisal result is stored in teaching resource grade form with the form of [course id, scoring].The scoring knot
Fruit score computational methods are：Score=α × v+ β × p+ γ × r, wherein, v is the pageview of on-line teaching resources, and p is ginseng
Plus number, r is user's evaluation；
During calculating, three indexs are first normalized to the scope of [0,100], three coefficients are then set to represent
The weight of each index is stated, the value of three coefficients can be adjusted according to actual sequence needs.
In step S3, SVM algorithm includes：
S301, the data mark of machine learning：Some on-line teaching resources crawled are selected first as sample, it is artificial right
The classification of sample is labeled；The sample of selection will uniformly cover all categories as far as possible, and each resource is pertaining only to a class；
S302, grader feature extraction：By the analysis to on-line teaching resources data, the type genus of teaching resource is chosen
Property, include title, label, body release, description and the teacher of teaching resource, and the original sample to being marked in step 301
This progress respective handling；
S303, training grader：The sample data training SVM classifier marked is inputted, java is used during specific implementation
The libsvm bags of language are trained；
S304, other sample classifications；After the completion of classifier training, the teaching resource data input grader not marked is entered
Row classification, final classification results are stored in course grouped data table, and storage format is [course id, classification].
To sum up, the present invention has crawled the teaching resource of multiple online education communities, and scattered teaching resource is effectively integrated
Get up so that user need not go to browse other online education communities respectively, the online teaching that directly can be built from the present invention
The resource needed for it is positioned and searched in resources bank, is had great convenience for the user, and is that user saves the time, with conformability；This
Invention is crawled to teaching resource timed increase, newest teaching resource is continuously obtained from other communities, with continuation；
Different communities has different criteria for classification and mode classification, and the present invention uses machine using the discipline classification of the Ministry of Education as standard
The mode of study has carried out unified classification to on-line teaching resources；Evaluation of the present invention by user to teaching resource, user
Number of visits, the information such as number that participates in course on-line teaching resources have been carried out with unified evaluation and sequence.
It should be noted that herein, such as first and second or the like relational terms are used merely to a reality
Body or operation make a distinction with another entity or operation, and not necessarily require or imply these entities or deposited between operating
In any this actual relation or order.Moreover, term " comprising ", "comprising" or its any other variant are intended to
Nonexcludability is included, so that process, method, article or equipment including a series of key elements not only will including those
Element, but also other key elements including being not expressly set out, or also include being this process, method, article or equipment
Intrinsic key element.In the absence of more restrictions, by sentence " including one ... the key element limited, it is not excluded that
Also there is other identical element in process, method, article or equipment including the key element ".
Although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of changes, modification can be carried out to these embodiments, replace without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (10)
1. a kind of method for auto constructing in on-line teaching resources storehouse, it is characterised in that comprise the following steps：
S1, structure on-line teaching resources database, the on-line teaching resources database crawl table, teaching resource number comprising data
According to table, teaching resource classification chart and teaching resource grade form；
S2, carry out information extraction and quality testing to the resource information of above-mentioned on-line teaching resources database, and by online teaching
Resource detailed data is stored in teaching resource tables of data；
S3, using the SVM algorithm in machine learning, on-line teaching resources are classified automatically；And be stored in classification results
Teaching resource classification chart；
S4, the pageview according to on-line teaching resources storehouse, user's evaluation, the number of participant score on-line teaching resources, root
Teaching resource is sorted from high to low according to scoring, and appraisal result is stored in teaching resource grade form.
2. the method as described in claim 1, it is characterised in that in step S1, using general Web crawler technologies regularly from mutual
The resource information needed for on-line teaching resources database is obtained in networking in disclosed online teaching community, and with html text
Mode, which is stored in, to be crawled in tables of data.
3. the method as described in claim 1, it is characterised in that in step S2, is extracted and the information of quality testing includes：Online
Title, description, institutional affiliation or the school of teaching resource, teacher, the course beginning and ending time, label, language, the number of participant, comment,
User evaluates.
4. the method as described in claim 1, it is characterised in that in step S3, according to the title of on-line teaching resources database,
Description, label, body release, lecturer's information are classified automatically to on-line teaching resources；And criteria for classification is announced for the Ministry of Education
Discipline classification.
5. the method as described in claim 1, it is characterised in that in step S4, appraisal result is with the form of [course id, scoring]
It is stored in teaching resource grade form.
6. method as claimed in claim 5, it is characterised in that the computational methods of the appraisal result score are：Score=α
× v+ β × p+ γ × r, wherein, v is the pageview of on-line teaching resources, and p is the number of participant, and r evaluates for user；
During calculating, three indexs are first normalized to the scope of [0,100], then set three coefficients to represent described each
The weight of individual index, the value of three coefficients can be adjusted according to actual sequence needs.
7. method as claimed in claim 2, it is characterised in that the on-line teaching resources information obtained by Web crawler technologies
Data are stored in the mode of [url, page HTML] to crawl in table.
8. method as claimed in claim 7, it is characterised in that if in the presence of the page for crawling mistake, rower is entered to page URL
Note, can be crawled again when next time crawls；The wrong page includes：Html page be 404 pages, or important information field lack
The page link of mistake.
9. method as claimed in claim 3, it is characterised in that in step S2, carries out the number after information extraction and quality testing
[course id, url, title, description ...] is stored in teaching resource tables of data according to this.
10. the method as described in claim 1, it is characterised in that in step S3, SVM algorithm includes：
S301, the data mark of machine learning：Some on-line teaching resources crawled are selected first as sample, manually to sample
Classification be labeled；The sample of selection will uniformly cover all categories as far as possible, and each resource is pertaining only to a class；
S302, grader feature extraction：By the analysis to on-line teaching resources data, the Representative properties of teaching resource are chosen,
Title, label, body release, description and teacher including teaching resource, and the original sample marked in step 301 is entered
Row respective handling；
S303, training grader：The sample data training SVM classifier marked is inputted, java language is used during specific implementation
Libsvm bags be trained；
S304, other sample classifications；After the completion of classifier training, the teaching resource data input grader not marked is divided
Class, final classification results are stored in course grouped data table, and storage format is [course id, classification].
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| CN108734370A (en) * | 2017-12-27 | 2018-11-02 | 上海储翔信息科技有限公司 | A kind of intelligent curriculum points-scoring system excavated based on machine learning, big data |
| CN109409642A (en) * | 2018-09-04 | 2019-03-01 | 四川文轩教育科技有限公司 | A kind of teaching resource ranking method based on big data |
| CN110020041A (en) * | 2017-08-21 | 2019-07-16 | 北京国双科技有限公司 | A kind of method and device tracking the process that crawls |
| CN111460261A (en) * | 2020-04-13 | 2020-07-28 | 同济大学 | Multi-platform network recording and playing course integration platform and method |
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