摘要
WWW缓冲技术通过将受欢迎的网页放到与客户较近的地方来提高用户存取这些网页的速度.如何有效充分地利用WWW缓冲中的信息,其关键是建立一个合适的用户兴趣模型和构造合适的兴趣挖掘算法.简单兴趣模型通过(词条,权重)来刻画兴趣.它没有深入挖掘这些兴趣之间的关联关系,因而在表达用户兴趣的时候,不能实现兴趣之间的关联.该文在充分分析WWW缓冲模型的基础上提出了实时二维兴趣模型.该模型的实时性可以保证挖掘出来的用户兴趣更能反映当前用户的兴趣状态;该模型引入的二维概念充分地考虑了用户兴趣之间的递推关系.该模型不是简单兴趣模型的简单扩充,而是模型和相关算法的全面改进.文章给出了二维兴趣模型的存储、二维兴趣的有效计算和二维兴趣的实时更新的相关方法.
The popular WWW pages are stored in the users'places.By this WWW Cache technology,the browsers can fetch these pages more rapidly.The information in the WWW Cache shows the users'recent interest.The users'interest can be widely used,for example,customizing the WWW pages,filtering the information,pre-fetching the information,and so on.How to use the information in the WWW Cache effectively lies in how to build an adaptive user interest model and how to construct an adaptive algorithm for interest mining.In simple interest model,the interest can be specialized by a tuple(term,weight),and the association relations are not mined,so the interest cannot be associated when expressing the users'interest.Based on analyzing the WWW Cache model,we bring forward a real time two-dimensional interest model.The property of real time in this model can show the users'current interest states.And the inferential relations between interests are well considered in the model.This model is not the simple extension of the simple interest model,but the round improvement of the model and its related algorithm.In this model,we use rough set method to store the data more effectively,and we use incremental algorithm to compute the interest effectively and to update the interest in real time.
作者
张卫丰
徐宝文
ZHANG Wei-Feng;XU Bao-Wen(Department of Computer Science and Engineering.Southeast University,Nanjing 210096;Department of Computer Science and Engineering.Nanjing University of Posts and Telecommunications,Nanjing 210003;Jiangsu Institute of Software Quality,Nanjing 210096;State Key Laboratory of Softtware Engineering,Wuhan University,Wuhan 430072)
出处
《计算机学报》
EI
CSCD
北大核心
2004年第4期461-470,共10页
Chinese Journal of Computers
基金
国家自然科学基金(60073012)
国家“九七三”重点基础研究发展规划项目基金(2002CB312000)
国家预研基金
江苏省自然科学基金(BK2001004)
江苏省科技攻关项目基金(BE2001025)
教育部跨世纪优秀人才基金
教育部博士点基金
江苏省三三三人才基金
高等学校重点实验室访问学者基金
武汉大学软件工程国家重点实验室开放基金
南京大学软件新技术国家重点实验室基金
苏州大学江苏省计算机信息处理技术重点实验室基金等资助
