CAJ | 학술논문

高速发展的信息技术和迅速增加的数据，给人们的生活带来困惑，推荐系统(Recommender System)可以从海量的用户浏览信息中，根据用户的特点，选择出特定的内容推荐给用户，推荐系统给用户提供了极大的便捷，但是，目前的推荐系统在空间存储的可扩展性与算法的效率存在缺陷，基于Hadoop构架的推荐系统解决了这一缺陷，它经济适用强，效率高，并且极大的提高了基于分布式计算Hadoop构架能够解决推荐系统的可扩展性问题，同时，对于大数据技术在实际中的应用具有实际意义。
고속발전적신식기술화신속증가적수거，급인문적생활대래곤혹，추천계통(Recommender System)가이종해량적용호류람신식중，근거용호적특점，선택출특정적내용추천급용호，추천계통급용호제공료겁대적편첩，단시，목전적추천계통재공간존저적가확전성여산법적효솔존재결함，기우Hadoop구가적추천계통해결료저일결함，타경제괄용강，효솔고，병차겁대적제고료기우분포식계산Hadoop구가능구해결추천계통적가확전성문제，동시，대우대수거기술재실제중적응용구유실제의의。
the rapid development of information technology and the rapid increase of data give the people life confusion, according to the user characteristic the recommendation system can select the specific content from the mass of user browsing information , which provides the user with great convenience, but, at present, the recommendation system has defects in the space storage scal?ability and the algorithm deficiency, the recommendation system based on Hadoop structure solves the defects, and it is afford?able, high efficiency, and greatly improves the scalability problem based on the Hadoop distributed framework ,also which has an important significance for the application of big data technology in practice.