基于Web2.0的社会性标签推荐系统附视频

被引：13

作者：

杨丹

曹俊

机构：

[1] 重庆大学软件学院

来源：

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：

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

页码：51 / 55

页数：5

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