中文摘要：

用户智能导航模式发现已经成为电子商务领域中的一个研究热点。为此,结合电子商务站点用户网页访问时间与网页关键字信息对用户访问兴趣进行定义,借鉴经典隐马尔可夫链模型,建立用户兴趣导航模型。给出在此模型中用户兴趣导航路径的发现方法及算法描述。通过模拟数据、某B2C在线图书销售站点中的真实数据以及与经典方法的对比等方面的实验验证,结果表明：给出的模型方法能够准确、高效地找到带有用户访问兴趣的关联路径信息。这个方法可以作为一种应用于电子商务领域更为有效、实用的智能导航发现工具。

英文摘要：

Intelligent discovery of users＇ navigation pattern has been a hot research issue in the E-Commerce field in recent years.In this paper,users＇ access interests are defined by combining the information of users＇ time duration on a page with the keywords on the pages in the E-Commerce Website.The Interest Navigational Path Model is constructed based on the classical Hidden Markov Chains Model.Next,the discovery method for user＇s interest navigational paths and corresponding mining algorithm are presented. Finally,the experiments are conducted with simulative data,real datasets collected from an online Bookselling B-to-C E-commerce site.Furthermore,the comparative experiment with a classical algorithm is conducted.The experimental results show that the presented model and algorithm can accurately and efficiently find the paths information associated with users＇ access interests.The method can be adopted as a more effective and practical tool for intelligent navigation discovery oriented to the E-Commerce field.