| 基于模糊逻辑的多代理推荐系统 |
| 投稿时间：2011-04-26 修订日期：2011-09-02 点此下载全文 |
| 引用本文：施笑畏,宓为建,苌道方,张艳.基于模糊逻辑的多代理推荐系统[J].上海海事大学学报,2011,32(4):71-75. |
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| 基金项目:交通运输部科技项目（2009 329 810 020）；上海市教育委员会重点学科建设项目（J50604）；上海海事大学校基金（20110316） |
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| 中文摘要:为模拟人的思维，向用户推荐高质量、个性化的电视节目，在TV Anytime 环境下提出一个基于模糊逻辑的多代理推荐系统.该系统包括模糊用户喜好档案、模糊筛选代理、模糊推荐代理、交互代理和档案修正代理.模糊用户喜好档案用于描述用户喜好和厌恶特征；模糊筛选代理基于模糊逻辑推理，将即将播放节目的元数据与用户喜好档案进行匹配，筛选出用户可能感兴趣的节目；模糊推荐代理根据预计的用户对推荐节目感兴趣程度排序，列出节目推荐表；交互代理收集用户清晰和隐含的反馈信息；档案修正代理根据用户的反馈，动态修正用户喜好档案中的特征参数值.实验结果显示该系统推荐效果可靠. |
| 中文关键词:多代理推荐系统 潜在需求 喜好档案 自学习 TV-Anytime |
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| Multi-agent recommendation system based on fuzzy logic |
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| Abstract:In order to imitate human’s thinking mode to recommend personalized TV program of high quality to users, a multi agent recommendation system based on fuzzy logic is proposed under TV Anytime environment. The system includes user’s fuzzy preference archive, fuzzy filtering/ranking agent, fuzzy recommendation agent, user interaction agent, and archive updating agent. The user’s fuzzy preference archive is used to describe both “like” and “dislike” features of users. Based on fuzzy logic inference, the filtering/ranking agent matches metadata of the incoming programs with user’s fuzzy preference archive, and selects programs that the user may be interested in. The fuzzy recommendation agent sorts the programs according to the degree of the expected user’s interest, and then presents recommended program list. The user interaction agent collects user’s both explicit and implicit feedback. The archive updating agent modifies the characteristic parameters in the user’s archive dynamically according to the user’s feedback. Results of the experiments show that the recommendation effect of the system is reliable. |
| keywords:multi-agent recommendation system potential need preference archive self learning TV-Anytime |
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