【摘要】：隨著信息技術(shù)的發(fā)展，高等院校的教學(xué)管理體制發(fā)生了相應(yīng)的變化。我國頒布的《中共中央關(guān)于教育體制改革的決定》明確指出：要增加選修課，減少必修課，實(shí)行學(xué)分制教學(xué)和雙學(xué)位制，而選課是學(xué)分制實(shí)施的重要環(huán)節(jié)。各高校的教學(xué)管理實(shí)踐中，，為學(xué)生提供了大量的選修課程，門數(shù)眾多，并且存在課程門類、專業(yè)等結(jié)構(gòu)性的不足和缺憾，諸如課程資源中心的組織和管理方式及現(xiàn)今多數(shù)的選課方式下，學(xué)生難以選擇到適合的、符合個(gè)人專業(yè)發(fā)展及個(gè)性需求的課程。目前國內(nèi)不少高校實(shí)際實(shí)施的是不完全學(xué)分制，學(xué)生選課的余地較小。鑒于此，我們將個(gè)性化推薦技術(shù)應(yīng)用到選課系統(tǒng)中，根據(jù)學(xué)生的學(xué)習(xí)需求和興趣偏好，為學(xué)生提供合理、科學(xué)和個(gè)性的選課推薦，從而避免學(xué)生選課的盲目性，提高課程資源的利用率和選課質(zhì)量。 本文主要深入研究協(xié)同過濾技術(shù)和選課推薦系統(tǒng)的設(shè)計(jì)，其研究工作如下： 首先對個(gè)性化推薦技術(shù)的優(yōu)缺點(diǎn)進(jìn)行分析，提出了基于課程屬性和屬性值偏好矩陣的協(xié)同過濾改進(jìn)算法。對于協(xié)同過濾算法的數(shù)據(jù)稀疏和冷啟動(dòng)問題，采用課程特征屬性和屬性值偏好矩陣來加以解決，并采用離線方式計(jì)算相似度，從而實(shí)現(xiàn)課程的實(shí)時(shí)推薦。其次針對如何合理的分配項(xiàng)目間的推薦比例，本文將構(gòu)建一個(gè)包含個(gè)性化推薦、排行榜推薦和新課程推薦三大模塊的系統(tǒng)架構(gòu)。 利用課程屬性和屬性值偏好矩陣的協(xié)同過濾改進(jìn)算法架構(gòu)具有個(gè)性化推薦功能的選課系統(tǒng)，同時(shí)要能減少課程推薦的誤差，提高推薦的實(shí)時(shí)性，從而擴(kuò)展學(xué)生的視野、提高學(xué)生學(xué)習(xí)的自主性和培養(yǎng)學(xué)生的創(chuàng)新型思維。
[Abstract]:With the development of information technology, the teaching management system of colleges and universities has changed accordingly. The decision of the CPC Central Committee on the Reform of the Education system promulgated by our country clearly points out that the elective courses should be increased, the required courses should be reduced, the credit system teaching and the double degree system should be implemented, and the elective course is an important link in the implementation of the credit system. In the practice of teaching management in colleges and universities, a large number of elective courses have been offered to students. Such as the organization and management of the curriculum resource center and most of the methods of selecting courses nowadays, it is difficult for students to choose suitable courses that meet the needs of individual professional development and personality. At present, many colleges and universities in China actually implement the incomplete credit system, and the students have less leeway to choose courses. In view of this, we apply the personalized recommendation technology to the course selection system, according to the students' learning needs and interest preferences, to provide students with reasonable, scientific and individual course selection recommendations, so as to avoid the blindness of students' choice of courses. Improve the utilization of curriculum resources and the quality of course selection. This paper mainly studies the collaborative filtering technology and the design of the course selection recommendation system. The research work is as follows: firstly, the advantages and disadvantages of the personalized recommendation technology are analyzed. An improved collaborative filtering algorithm based on curriculum attributes and attribute preference matrix is proposed. For the problem of data sparsity and cold start of collaborative filtering algorithm, curriculum characteristic attribute and attribute value preference matrix are used to solve the problem, and offline method is used to calculate the similarity so as to realize the real-time course recommendation. Secondly, in view of how to allocate the recommended proportion among items reasonably, this paper will construct a system architecture which includes three modules: personalized recommendation, ranking recommendation and new curriculum recommendation. Based on the collaborative filtering of curriculum attribute and attribute preference matrix, the course selection system with personalized recommendation function should be constructed. At the same time, the error of course recommendation should be reduced, and the real-time performance of course recommendation should be improved, so as to expand the students' vision. Improve students' learning autonomy and cultivate students' innovative thinking.
【學(xué)位授予單位】：云南師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：G647

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