| 摘要: |
| 传统信息检索技术满足了人们一定的需要,但由于其通用的性质,仍然不能满足不同背景、不同目的和不同时期的查询请求.提出了一种基于内容过滤的个性化搜索算法.利用领域分类模型上的概率分布表达了用户的兴趣模型,然后给出了相似性计算和用户兴趣模型更新的方法.对比实验表明,概率模型比矢量空间模型更好地表达了用户的兴趣和变化. |
| 关键词: 个性化 基于内容过滤 搜索算法 用户模型 推荐系统 |
| DOI： |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60221120146 (国家自然科学基金); the National Grand Fundamental Research 973 Program of China under Grant No.G1999032704 (国家重点基础研究发展规划(973)) |
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| A Personalized Search Algorithm by Using Content-Based Filtering |
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ZENG Chun,XING Chun-Xiao,ZHOU Li-Zhu
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| Abstract: |
| Traditional information retrieval technologies satisfy users’ need to a great extent. However, for their all-purpose characteristics, they can not satisfy any query from the different background, with the different intention and at the different time. A personalized search algorithm by using content-based filtering is presented in this paper. The user model is represented as the probability distribution over the domain classification model. A method of computing similarity and a method of revising user model are provided. Compared with the vector space model, the probability model is more effective on describing a user’s interests. |
| Key words: personalization content-based filtering search algorithm user model recommendation system |
