CAJ | 학술논문

借鉴Web2．0、社交网络、复杂网络、本体论和云计算等理论，设计了基于用户兴趣图谱的个性化推荐系统结构，阐明了基于用户兴趣图谱的推荐原理，提出了用户兴趣图谱生成与集成方法，以及用户兴趣图谱的动态演化与反馈机制，提高了推荐系统的推荐质量和精度。
차감Web2．0、사교망락、복잡망락、본체론화운계산등이론，설계료기우용호흥취도보적개성화추천계통결구，천명료기우용호흥취도보적추천원리，제출료용호흥취도보생성여집성방법，이급용호흥취도보적동태연화여반궤궤제，제고료추천계통적추천질량화정도。
Web2.0, social network, complex network, ontology theory and cloud computing were used as sources of refer-ence to design personalized recommendation system structure .The theory of recommendation based on user interest graph was ex-plained .The methods of user interest graph generation and integration were put forward ;dynamic evolution and feedback mecha-nism were discussed .The recommendation quality and accuracy of the recommendation system were improved .