基于Web2.0的社会性标签推荐系统

被引:13
作者
杨丹
曹俊
机构
[1] 重庆大学软件学院
关键词
推荐算法; 社会性标签; folksonomy; 社会性书签;
D O I
暂无
中图分类号
TP393.092 [];
学科分类号
080402 ;
摘要
利用社会性书签作为用户在互联网上的操作数据,通过分析用户所做的社会性书签,来构建基于整个互联网的推荐系统,在对社会性标签数据分析的基础上,提出一种新的方法来展现用户的喜好项.实验表明,基于social tag的网页推荐系统在很大程度上能满足用户的兴趣需求.
引用
收藏
页码:51 / 55
页数:5
相关论文
共 10 条
[1]  
An introduction to genetic algorithms for numericaloptimization. Paul C. http://www.hao.ucar.edu/modeling/pikaia/tutorial/probsec1.ps . 2006
[2]  
An experimental comparisonof binary and floating point representations in genetic algo-rithms. Janikow C Z,Michalewicz Z. Proceedings of the Fourth Intl.Conf . 1991
[3]  
Genetic Algorithms in Search, Optimization and Machine. Goldberg D.E. Optimization and Machine . 1989
[4]  
Gene expression programming:A new adaptive algorithm for solving problems. Ferreira C. Complex Systems . 2001
[5]  
Reducing bias and inefficiency in the selectionalgorithm. Baker J E. Proceedings of the Second InternationalConference on Genetic Algorithms,.pages . 1987
[6]  
Web 2.0 Principles and Best Practices. .
[7]  
Lucene in Action. Erik H,Otis G. . 2004
[8]  
An experimental study ofbenchmarking functions for Genetic Algorithms. Digalakis J G,Margaritis K G. IEEEInt Conf on Systems,Man and Cybernetics . 2000
[9]  
Sphinx4:A Flexible OpenSouseFramework for Speech Recogniti0n. Willie W,Paul L,Philip K,et a1. http:H cmusphinx.sourceforge.netsphinx4/doc/Sphinx4W hitepaper.pdf . 2006
[10]  
Modern Information Retrieval. Baeza-Yates R,Ribeiro-Neto B. . 1999