Design And Implementation Of Learning Resource Collection And Classification System

With the rapid development of information technology,to promote the country to develop educational information business,the construction of digital,intelligent campus,to achieve regional integration of deep integration of learning resources,build,sharing,so that learners and users in the massive information access to learning resources to zero distance.Universal Web crawler is to collect massive web information,collecting information content disorderly,low utilization,loss of storage space.Focused reptiles are collected according to certain rules,and the collected resources(TXT,Word,Excel,PPT,PDF,HTML format)are ordered and high quality.As the network learning resources and constructivism theory support,combined with the Blended Learning way,fully mobilize the enthusiasm of learners and users,initiative,creativity.At the same time,learning resources are distance education,mobile education,pervasive learning resources,and low cost,easy to manage the characteristics of people concerned about the hot spots.Learners,users and educational research institutions on the demand for information learning resources growing,but the Internet resources are massive,loose distribution,learners and users access to the required learning resources such as haystack,and access to learning resources similar to the style of repeated,less innovative,Practicality is poor.Therefore,the application of learning resource theme acquisition model to eliminate irrelevant interference information;combined with KNN text classification method to organize and manage the massive,heterogeneous,semi-heterogeneous,dynamic characteristics of learning resources for learners and users quickly and accurately query,Sharing learning resources.This is the focus of attention of learners and users,but also learning resources collection and classification of urgent research and solve the problem.This paper first summarizes the research background and significance of learning resource collection and classification,briefly introduces the present situation and existing problems of learning resources collection and classification at home and abroad.The research and analysis of this paper involves the collection and classification of learning resources,classification theory and key technologies,including: learning Resource meaning,type,format concept definition;learning resources web crawler,information extraction,page weighting technology;learning resources Chinese word segmentation,feature selection,VSM model,KNN text classification.This paper elaborates the requirements analysis of learning resource collection and classification,system frame design,learning resource theme acquisition structure design,learning resource classification structure design,system function design,detailed description of learning resources collection and classification of the module implementation.Finally,through the experimental verification of learning resource acquisition model and classification algorithm,the system evaluation based on its accuracy rate,recall rate,F value and analysis of classification results,confirmed the learning resource acquisition and classification system application effect is remarkable.At the same time,the LDA model is proposed for large-scale learning resource acquisition,and the optimization of local sensitive hash and KNN algorithm is used to improve the system classification speed and accuracy.