摘要
基于领域知识与顾客购买倾向相关联的事实,从知识表示、知识获取、系统实现三个方面研究了个性化协同商务推荐系统的实现策略。知识表示研究了自然语言的本体表示,主要包括:知识本体描述、模糊关系设计、概念关联抽象和公理修正四个部分;知识获取采用多层次领域知识获取和基于数据挖掘的智能知识获取两种方法,对知识的形式化和结构化进行了研究;基于J2EE技术创建了由客户端、服务器端、存储系统组成的协同商务推荐系统的结构模型。最后通过测试网站对系统的有效性进行了验证。
Based on the relativity between domain knowledge and purchase trends 3 typical areas including knowledge representation,knowledge acquisition and system achievement are studied for personalized collaborative commerce recommendation system.Knowledge representation studied ontology representation of natural language, which includes knowledge ontology representation,fuzzy relationship design,concept connection abstract and axiom revises.Knowledge acquisition studied formalization and structurization of domain knowledge through multi-level domain knowledge acquisition and intelligent knowledge acquisition based on data mining.In order to develop collaborative commerce system,a model including client,server and storage system is designed based on J2EE.To demonstrate the practical usefulness of this methodology ,a real-life case is illustrated.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第6期29-32,61,共5页
Computer Engineering and Applications
基金
上海市自然科学基金(the Natural Science Foundation of Shanghai of Chinaunder Grant No.06zr14079)。
关键词
协同商务
个性化推荐
算法设计
collaborative commerce
personalized recommendation
algorithm design
