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现代图书情报技术  2011, Vol. Issue (11): 31-37    DOI: 10.11925/infotech.1003-3513.2011.11.05
  知识组织与知识管理 本期目录 | 过刊浏览 | 高级检索 |
一种提高过滤用户偏好精度的数据采集方法
赵妍1, 苏玉召2,3, 管涛1
1. 郑州航空工业管理学院计算机科学与应用系 郑州 450015;
2. 中国科学院国家科学图书馆 北京 100190;
3. 中国科学院研究生院 北京 100049
A Method of Data Collecting to Improve the Precision of Filtering User Preference
Zhao Yan1, Su Yuzhao2,3, Guan Tao1
1. Department of Computer Science & Application, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015, China;
2. National Science Library, Chinese Academy of Sciences, Beijing 100190, China;
3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
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摘要 采用数据挖掘技术中的关联分析和聚类方法,重点研究Web日志兴趣发现的理论和方法,指出普通日志记录方法的局限性,提出过滤用户偏好的定制Web日志方法,实验结果验证通过该方法采集的数据,可以发现隐藏在日志数据中的关联规则,同时找到相似用户的兴趣和偏好,并且能够提高过滤用户兴趣偏好的精度。
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赵妍
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管涛
关键词 信息过滤用户偏好个性化推荐系统数据采集定制Web日志    
Abstract:Using the methods of association analysis and clustering in the field of data mining, the paper focuses on the theories and methods of discovering user interests and points out the limitations of standard Web log. So it proposes a method of customized Web log in order to enhance the precision of user interests and preferences. The outcome of experiment shows that,by the method,Web log data hidden in the association rules as well as interests and preferences of similar users can be found, the precision of filtering user interest can be improved at the same time.
Key wordsInformation filtering    User preferences    Personalization recommending system    Data collecting
收稿日期: 2011-09-05     
:  G350 TP311  
基金资助:本文系河南省教育厅基金项目“高斯混合模型及其在图像处理中的应用”(项目编号:2011B520038)和郑州市科技局基金项目“基于高斯混合模型的图像分割算法研究”(项目编号:112PPTGY248-6)的研究成果之一。
引用本文:   
赵妍, 苏玉召, 管涛. 一种提高过滤用户偏好精度的数据采集方法[J]. 现代图书情报技术, 2011, (11): 31-37.
Zhao Yan, Su Yuzhao, Guan Tao. A Method of Data Collecting to Improve the Precision of Filtering User Preference. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2011.11.05.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2011.11.05
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