CAJ | 학술논문

研究学习者学习兴趣，并根据学习者兴趣相似性的方法获得目标学习者的最近邻居集合，可更好地为学习者提供自适应学习服务并产生相应学习推荐。首先从学习者的兴趣度入手，采用相似性度量方法计算目标学习者的最近邻居；最后依据邻居学习者的兴趣度来预测目标学习者对学习页面的兴趣度，并产生推荐。实验结果表明，基于学习者兴趣相似性的推荐方法，提高了最近邻居计算的准确性和推荐质量。
연구학습자학습흥취，병근거학습자흥취상사성적방법획득목표학습자적최근린거집합，가경호지위학습자제공자괄응학습복무병산생상응학습추천。수선종학습자적흥취도입수，채용상사성도량방법계산목표학습자적최근린거；최후의거린거학습자적흥취도래예측목표학습자대학습혈면적흥취도，병산생추천。실험결과표명，기우학습자흥취상사성적추천방법，제고료최근린거계산적준학성화추천질량。
Study on learners’learning interest and acquisition of target users’nearest neighbor set based on learners’interest similarity provide learners with self-adapted learning service and corresponding recommendation.From learners’leaning interestingness and by similarity calculation method the target users’nearest neighbor was calculated.Based on page access behavior,the page interestingness of target users was predicted and recommendation was given.The experimental results show that the application of the learners’interestingness similarity improves calculation accuracy of nearest neighbors and commenda-tion efficiency.