基于改进的隐马尔可夫模型的网页预取  

Web Pre-Fetching Based on Improved Hidden Markov Model

作　　者：王秀坤[1] 王宇宁[1] 陈浩[1] 

机构地区：[1]大连理工大学软件学院,辽宁大连116024

出　　处：《吉林大学学报（信息科学版）》2008年第1期89-93,共5页Journal of Jilin University（Information Science Edition）

摘　　要：为提高基于隐马尔可夫模型(HMM:Hidden Markov Model)的网页预取精度,对经典隐马尔可夫模型的两个前提假设进行了扩展,推导出新模型中计算观测序列概率的公式。由此构建出可用于网页预取的高阶隐马尔可夫模型,同时为降低高阶隐马尔可夫模型的空间复杂度,给出了构建树状状态空间存储访问序列的算法。介绍了将改进的隐马尔可夫模型应用于网页预取的具体方法,通过对比实验证实该方法的预取准确度提高了7%。In order to improve the accuracy of the predictions, we expand two premises of the traditional hidden markov model, and calculate new formulas of the observing sequences＇probabilities in new high-order modal used for web pre-fetching. To reduce the space complexity of the high-order model, an algorithm used to store the visited sequences by tree-like structure is given. Finally the method of using expansive hidden markov model in web pre-fetching is shown. The experiment confirms that the accuracy of new method is 7% higher than old one.

关 键 词：网页预取 隐马尔可夫模型 树状状态空间 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]