Collaborative Information Filtering by Using Categorized Bookmarks on the Web
Collaborative Information Filtering by Using Categorized Bookmarks on the Web
复制标题
使用Web分类书签进行协同信息过滤
DOI：
10.1007/3-540-36524-9_20
复制
发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Geun
中科院分区：
文献类型：
--
作者：
Jason J. Jung;Jeong;Geun
书签是指为了记住用户自己的足迹并重新访问该网站而存储的 URL 信息。本文将这个书签视为代表用户偏好的最有意义的信息之一。仅指示地址信息的原始书签被分类以通过使用公共网络目录服务来合并语义。这些分类书签以分层树结构表示。然而，大多数当前的 Web 目录服务无法规范和管理主题层次结构。存在多种结构不完整性，例如多重引用和异构树结构。为了提取用户偏好，本文提出了一种驱动这些问题的方法以及基于贝叶斯网络的影响力传播方法。因此，代表用户兴趣的偏好图也被建立为树结构。在用户聚类方面，采用近似树匹配方法来映射（重叠）用户的偏好图。可以根据类别进行查询和高效处理。最后，本文应用于实现协作式网页浏览，能够高效、自适应地引导和探索网页。
A bookmark means the URL information stored for memorizing a user’s own footprints and revisiting that website. This paper regards this bookmark as one of the most meaningful information representing user preferences. An original bookmark indicating only address information is categorized for merging semantic meanings by using public web directory services. These categorized bookmarks are expressed in a hierarchical tree structure. However, most current web directory services cannot afford to normalize and manage the topic hierarchy. There are several kinds of structural incompleteness such as multiple references and heterogeneous tree structures. In order to extract user preferences, this paper proposes a method for driving these problems and the influence propagation methods based on Bayesian networks. Therefore, the preference maps representing users’ interests are also established as tree structures. With respect to the user clustering, an approximate tree matching method is used for mapping (overlapping) users’ preference maps. It is possible to make queries and process them efficiently according to categories. Finally, this paper is applied to implement collaborative web browsing that can guide and explore the web efficiently and adaptively.