發(fā)布時(shí)間：2018-12-19 20:03

【摘要】：目前信息化的高校選課系統(tǒng)在高校選課中的應(yīng)用非常普遍,幾乎所有高校都采用了教務(wù)網(wǎng)絡(luò)管理信息系統(tǒng)來(lái)為學(xué)生提供各種服務(wù)。學(xué)生使用選課系統(tǒng)在網(wǎng)上進(jìn)行選課時(shí),可以根據(jù)系統(tǒng)中提供的各種選修課,選擇自己感興趣的課程,修滿(mǎn)學(xué)分完成學(xué)業(yè)。盡管目前絕大多數(shù)的高校選課系統(tǒng)可以實(shí)現(xiàn)為學(xué)生提供基本的選課功能,但是選課系統(tǒng)的智能化程度不夠,不能為學(xué)生選課提供推薦功能。學(xué)生在選課的時(shí)候都存在很大的盲目性,對(duì)自己所學(xué)專(zhuān)業(yè)了解不夠,沒(méi)有方向性。很多同學(xué)通常都是為了修滿(mǎn)學(xué)分,選課的目的性不明確,所選課程是否對(duì)自己的專(zhuān)業(yè)發(fā)展有幫助也不會(huì)去考慮。導(dǎo)致所選課程對(duì)他們的整個(gè)學(xué)業(yè)規(guī)劃幫助不大,所以高校教務(wù)系統(tǒng)迫切需要有更加智能化的選課系統(tǒng),系統(tǒng)可以通過(guò)智能推薦來(lái)解決學(xué)生選課時(shí)存在的盲目性的問(wèn)題,方便學(xué)生選課,為學(xué)生提供更便利的服務(wù)。本文主要研究將協(xié)同過(guò)濾技術(shù)融合到高校選課系統(tǒng)中,通過(guò)課程之間的相關(guān)性,學(xué)生之間的相關(guān)性,根據(jù)學(xué)生對(duì)所學(xué)課程的評(píng)分,構(gòu)建評(píng)分矩陣。根據(jù)協(xié)同過(guò)濾算法產(chǎn)生預(yù)測(cè)評(píng)分矩陣,產(chǎn)生推薦列表,實(shí)現(xiàn)智能化的為學(xué)生推薦他可能喜愛(ài)的課程。學(xué)生通過(guò)系統(tǒng)提供的推薦課程進(jìn)行選課,所推薦課程往往是學(xué)生更感興趣的,有一定的專(zhuān)業(yè)導(dǎo)向性,目的性更明確。學(xué)生通過(guò)學(xué)習(xí)選修課程對(duì)學(xué)生的整個(gè)學(xué)習(xí)體系更加有幫助,達(dá)到了通過(guò)選修課程來(lái)幫助學(xué)生擴(kuò)展知識(shí)面,完善專(zhuān)業(yè)知識(shí)體系的目的。實(shí)驗(yàn)結(jié)果表明,在傳統(tǒng)協(xié)同過(guò)濾推薦技術(shù)的基礎(chǔ)上,采用改進(jìn)的基于項(xiàng)目和用戶(hù)同時(shí)加權(quán)的用戶(hù)協(xié)同過(guò)濾算法實(shí)現(xiàn)課程推薦,推薦精度更高。本文所實(shí)現(xiàn)的改進(jìn)的協(xié)同過(guò)濾技術(shù)在高校選課推薦系統(tǒng)中的應(yīng)用很好的為學(xué)生智能推薦選修課程,為學(xué)生所推薦的課程具有很好的合理性和準(zhǔn)確性,實(shí)現(xiàn)了更加智能化的為學(xué)生選課,具有很大的實(shí)用性和現(xiàn)實(shí)意義。
[Abstract]:At present, the application of the information-based course selection system in colleges and universities is very common. Almost all colleges and universities use the educational administration network management information system to provide various services for students. Students can choose the courses they are interested in according to the various elective courses offered by the system, and complete their studies with credit. Although most of the courses selection systems in colleges and universities can provide students with basic course selection functions, the intelligent degree of the course selection system is not enough to provide the recommended function for students to choose courses. Students in the selection of courses are very blind, their own professional understanding is not enough, there is no direction. Many students are usually to complete the credit, the purpose of the course is not clear, whether the course is helpful to their professional development and will not be considered. As a result, the selected courses are of little help to their entire academic planning. Therefore, the educational administration system in colleges and universities urgently needs a more intelligent course selection system. The system can solve the blindness problems existing in the course selection of students through intelligent recommendation. It is convenient for students to choose classes and provide more convenient service for students. This paper mainly studies the integration of collaborative filtering technology into the course selection system of colleges and universities. Through the correlation between courses and the correlation between students, the scoring matrix is constructed according to the students' scores on the courses they have learned. According to the collaborative filtering algorithm, the prediction score matrix is generated, the recommendation list is generated, and the course that he may like to be recommended to the student is intelligently recommended. Students choose courses through the recommended courses provided by the system. The recommended courses are often more interesting, professional oriented and more purposeful. Through the study of elective courses, students are more helpful to the whole learning system of students, and achieve the goal of helping students expand their knowledge and improve their professional knowledge system through elective courses. The experimental results show that, based on the traditional collaborative filtering recommendation technology, the improved user collaborative filtering algorithm based on item and user weights is used to realize the course recommendation, and the recommendation accuracy is higher. The application of the improved collaborative filtering technology in the course selection recommendation system of colleges and universities is very good for the students to recommend intelligent elective courses, the recommended courses for students have good rationality and accuracy. It realizes more intelligent course selection for students, which has great practicability and practical significance.
【學(xué)位授予單位】：華僑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.3

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