HiBO is a bookmark management system that incorporates a number of Web mining techniques and offers new ways to search, browse, organize and share Web data. One of the most challenging features that HiBO incorporates is the automated hierarchical structuring of bookmarks that are shared across users. One way to go about organizing shared files is to use one of the existing collaborative filtering techniques, identify the common patterns in the user preferences and organize bookmarked files accordingly. However, collaborative filtering suffers from some intrinsic limitations, the most critical of which is the complexity of the collaborative filleting algorithms that inevitably leads to the latency in updating the user profiles. In this paper, we address the dynamic maintenance of personalized views to shared files from a bookmark management system perspective and we study ways of assisting Web users share their information space with the community. To evaluate the contribution of HiBO, we applied our Web mining techniques to manage a large pool of bookmarked pages that are shared across community members. Results demonstrate that HiBO has a significant potential in assisting users organize and manage their shared data across web-based social networks.