CAJ | 학술논문

经典推荐系统主要根据用户对项目的评价或者用户与项目之间的关键字相似度进行推荐，存在信息结构化程度低、语义缺乏、信息利用不充分等问题。为此，提出一种基于本体的推荐系统模型。将本体引入到推荐系统中，使用OWL语言对用户和项目信息进行描述，使用户和项目具有语义信息的同时，提高信息的结构化描述水平。在推荐过程中，通过规则分析用户行为信息并综合考虑以提高模型的推荐质量。实验结果证明，与传统推荐模型相比，该模型在信息结构化水平、语义描述等方面具有优势。采用该模型为用户推荐项目能够有效提高推荐的召回率和准确率。
경전추천계통주요근거용호대항목적평개혹자용호여항목지간적관건자상사도진행추천，존재신식결구화정도저、어의결핍、신식이용불충분등문제。위차，제출일충기우본체적추천계통모형。장본체인입도추천계통중，사용OWL어언대용호화항목신식진행묘술，사용호화항목구유어의신식적동시，제고신식적결구화묘술수평。재추천과정중，통과규칙분석용호행위신식병종합고필이제고모형적추천질량。실험결과증명，여전통추천모형상비，해모형재신식결구화수평、어의묘술등방면구유우세。채용해모형위용호추천항목능구유효제고추천적소회솔화준학솔。
The classic recommendation system is mainly based on the users for the project evaluation or the keywords similarity between the user and the item for recommendation, there is a low degree of information structure, lack of semantic and other issues. To solve these problems, this paper proposes an ontology-based recommender system model. This model uses OWL language describe the user and project information by introducing ontology to bear more semantic information and improve the degree of information structure. In the recommendation process, the results of analyzing user behavior information by rules is considered for improve the quality of recommendation. Experimental results show that the model has better effect in degree of information structure and semantics. It can effectively improve the recall and precision rates by using this model for recommendation.