摘要
随着网络信息的飞速增长,互联网已成为人们获取信息的重要来源.但是,受限于网络带宽,用户往往需要忍受较长的访问延时.为了缓解这种情况,人们提出了网页预取技术,用于降低用户的访问延迟,提高Web服务器的服务质量.提出一种基于用户访问路径分析的服务器端网页预取模型.模型通过对用户访问序列进行语义分析,提取路径中蕴含的信息需求,依此进行网页预取决策.为了实现用户访问序列中潜在意图的挖掘,模型还引入了隐马尔可夫模型.性能测试实验的结果表明,该模型具有较好的整体性能.
With the enormous growth of information on the Web, Internet has become one of the most important information sources. However, limited by the network bandwidth, users always suffer from long time waiting. Web pre-fetching is one of the most popular strategies, which are proposed for reducing the perceived access delay and improving the service quality of Web server (QoS). A semantics-based pre-fetching model is presented in this paper. This model predicts future requests based on latent intention that the user抯 current access path implies in semantics, rather than on the temporal relationships between URL accesses, which overcomes the limitation of previous pre-fetching approaches. The hidden Markov model (HMM) is employed for mining actual intention from access patterns. Experimental results show that the proposed pre-fetching model has better general performance.
出处
《软件学报》
EI
CSCD
北大核心
2003年第6期1142-1147,共6页
Journal of Software
基金
国家自然科学基金~~
